A recent report shows what might be the biggest shift in the history of consumer activity: AI is starting to take over shopping. Everything your business has done to build brand loyalty is at stake.
AI agents “can behave differently from human shoppers: they prioritize price, user ratings, delivery speed, and real-time inventory over brand familiarity or loyalty,” Boston Consulting Group reports. “This has the potential to reshape how retailers compete and how purchase decisions are made.”
There’s no time to waste in meeting this new reality. This year, 52% of consumers plan to use generative AI for online shopping, according to Adobe. Some will use it to simply get a list of options, and may pick their favourite brand from among them. But when they see those options listed together without brand identities or logos, price is even more likely to be the differentiator.
And soon, agentic AI will take on even more of the buying process. It’s like having “a personal shopper who deeply understands your preferences, lifestyle, and budget, effortlessly curating tailored product recommendations from thousands of options,” BCG says. “Your shopper seamlessly anticipates your needs, secures the best prices, and completes transactions autonomously.”
The way business works today, organizations will lose a lot through “disintermediation,” in which consumers bypass a brand’s e-commerce platform altogether, the report adds. “The growth of zero-click search and agent-driven interactions is eroding direct traffic—along with the retailer’s ability to observe, influence, and understand consumer behaviour at scale.”
There are steps businesses can and must take now to prepare.
Your Own Agentic Experiences
The most important step is to create your own platforms that make consumers want to come directly to you. These platforms must offer all the same end-to-end shopping as third party AI applications like ChatGPT, Gemini, and Claude.
The good news is that your business has a big advantage in this battle: proprietary information about customers. By combining that information with the power of AI, you can provide experiences that make people want to shop there.
Building an agentic experience requires taking all the data you have about each individual customer and using it to personalize their journey, making them feel recognized and valued. That means leaving nothing on the table. Be sure to gather every piece of information from every interaction your brand has ever had with each customer, across any and all channels.
A well designed Unified Customer Experience Management (UCXM) platform can achieve this. It serves not only as a way to consolidate information, but also as a system for everyone across a company to collaborate. This way, people across different functions access the same records; update them in real time; and contribute to finding solutions to customer challenges.
Since these tools keep learning over time, they become more precise and successful, guiding each customer to their best possible experience. Everything about an agentic experience can be hyper-personalized, from an agent’s voice to its manner of speaking to the products and services it recommends.
Building a ‘moat’
“To drive revenue growth and improve ROI, business leaders may need to commit to transformative AI possibilities,” McKinsey says. “As the hype around AI subsides and the focus shifts to value, there is a heightened attention on practical applications that can create competitive moats.”
Your brand is like its own castle. The experience of going to it can be so enjoyable that customers keep visiting. And by ensuring that competitors can’t get in — that they’re unable to access your precious customer data — you keep the experience distinctive.
Of course, this is not the only part of the solution to the seismic shift ahead in how people shop. BCG notes that brands must also work to ensure discoverability on popular AI tools, through both “earned visibility” and paid opportunities.
On this, brands have an opportunity as well. Adobe found that when people arrive at a retailer’s site from a generative AI source, they are 10% more engaged, with 32% longer visits and a 27% lower bounce rate. “This indicates that with AI tools, shoppers are becoming more informed and focusing on the most relevant retailers during the research/consideration phase,” Adobe’s report said.
With a UCXM in place, your brand can know exactly how a customer arrived at your site each time, and use that to tailor their experience.
As with so many other revolutions, the AI revolution presents an opportunity. By developing new strategies, you can compete and win in new ways. The key is to see the possibility — not just the problem.
The framework behind “Design After the Prompt” moves past the chaotic novelty of text-to-image generation toward a systematic era of creative orchestration. Modern studios now realize that typing words into a box represents only the beginning of a workflow. Design After the Prompt demands that we view artificial intelligence as a precise ingredient rather than a replacement. That’s why Adobe has positioned itself as the architect of this professional shift while competitors prioritize mere spectacle. This report examines why a systemic approach to creative tools determines the future of global brand integrity. Design After the Prompt provides the technical and ethical infrastructure required for the next decade of digital craft.
Does the shift toward Design After the Prompt render current prompting techniques obsolete?
Design After the Prompt forces a fundamental reassessment of how professional creators interact with generative artificial intelligence. Scott Belsky recently noted that the initial Prompt Era actually undermined the craft of experienced creative professionals. He argued that summoning images with simple words cheapens the judgment and taste honed over many decades. Therefore, the industry now enters the Controls Era, where creators demand specific levers and knobs for refinement. Design After the Prompt dictates that professional work requires granular adjustments rather than lucky rolls of the dice. Creators no longer want to manage unpredictable tools but instead wish to direct a personalized creative team. This transition ensures that the human eye remains the ultimate arbiter of every pixels’ final placement.
Evolution Phase
Primary Toolset
Creative Philosophy
Professional Role
Prompt Era
Text Boxes, Discord Commands
Summoning and Random Discovery
Prompt Engineer
Controls Era
Sliders, Nodes, Reference Images
Precision and Iterative Direction
Creative Director
Design After the Prompt
Orchestrated Agents, Graph Workflows
Systemic Logic and Brand Mastery
Creative Orchestrator
The transition toward Design After the Prompt moves the creative process from isolation into deep system integration. Adobe Firefly facilitates this by living inside the applications that designers already use for their daily work. Specifically, tools like Generative Fill in Photoshop allow for non-destructive edits directly on the active canvas. This capability allows designers to add or remove elements while maintaining the original artistic intent. Design After the Prompt focuses on the final mile of production rather than just the initial spark. The software starts to become almost invisible as conversational interfaces handle the tedious technical setup. This transformation empowers creators to spend more time exploring the full surface area of creative possibility.
The infrastructure of professional trust through Content Credentials
Design After the Prompt requires a robust system to verify the authenticity of digital content in a crowded market. Adobe addresses this need through the Content Authenticity Initiative and the development of the C2PA standard. Content Credentials act as a digital nutrition label that records the history and origin of an asset. Specifically, these credentials use cryptographic signing to bind metadata directly to the image or video file. Every manifest includes statements about the capture device, the software used, and any AI involvement. These manifests are tamper-evident, ensuring that any unauthorized changes invalidate the cryptographic signature. Design After the Prompt provides this necessary layer of transparency for brands that value audience trust.
Manifest Component
Technical Description
Impact on Design After the Prompt
Assertions
Labelled data representing specific facts about the asset
Provides granular proof of the human-AI collaboration
Claims
A structure connecting assertions to a specific signer
Ensures that every edit has a verifiable author
Hard Binding
Cryptographic hashes linking manifest to digital content
Prevents the detachment of provenance from pixels
Soft Binding
Watermarks and fingerprints for metadata recovery
Maintains trust even if metadata is stripped
Design After the Prompt relies on a well-defined trust model established through a hierarchy of X.509 certificates. These certificates allow applications to verify the identity of the claim generator and the integrity of the data. An organization can prove that its marketing assets are legitimate and free from malicious tampering. Adobe also introduced the Content Authenticity API to help enterprise customers sign assets at massive scale. This programmatic approach ensures that thousands of files receive tamper-resistant certificates automatically during the production process. Therefore, Design After the Prompt is as much about the content supply chain as it is about aesthetics. This commitment to provenance distinguishes Adobe from competitors who ignore the ethical implications of synthetic media.
Strategic differences between Adobe Firefly and Midjourney
Design After the Prompt highlights the divergent paths taken by the industry’s most prominent generative AI platforms. Midjourney focuses on artistic excellence and has become the aesthetic pioneer of the current AI generation. Its model produces images with exceptional mood, atmosphere, and stylistic coherence that often exceed user expectations. However, Midjourney’s reliance on Discord creates friction for professional teams who need private and organized workspaces. In contrast, Adobe Firefly prioritizes practical utility and seamless integration into the existing creative software suite. Firefly produces consistent, production-ready outputs that fit into a larger, professional brand strategy. Design After the Prompt favours this integrated approach because it solves real-world workflow challenges for designers.
The legal landscape significantly influences how professionals adopt the Design After the Prompt framework in their daily practice. Adobe trains Firefly exclusively on licensed content from its own library and public domain materials. Consequently, the company offers legal indemnification to enterprise users, making it the safest option for big brands. Midjourney faces numerous lawsuits because its crawlers inhaled copyrighted work from the internet without any licensing. While Midjourney is great for ideation, its outputs often lack the commercial safety required for major campaigns. Therefore, professional creators often use Midjourney for initial concepts and Firefly for the final production refinement. Design After the Prompt encourages this strategic multi-tool approach to leverage the unique strengths of each platform.
Ethics and the synthetic laundering controversy
Design After the Prompt does not exist without significant ethical friction and ongoing debates within the creative community. Adobe recently faced criticism when reports revealed that Firefly was partially trained on AI-generated images. These images came from Adobe Stock, which allows contributors to upload assets created with Midjourney. Critics dubbed this practice “synthetic laundering” because it indirectly uses data from models that scraped the web. Although Adobe claims these images represent a small subset, the ethical optics remain problematic for many. Design After the Prompt necessitates a closer look at how datasets are curated and verified for professional use.
Adobe manages these concerns by implementing strict governance processes and mandatory AI ethics courses for its employees. The company uses an ethics advisory board to oversee every new generative tool before its public release. Additionally, Adobe pays a bonus to Stock contributors whose work helps train the first versions of Firefly. This proactive approach contrasts with the “reckless” strategies of startups that offer no compensation to original creators. Design After the Prompt requires this level of accountability to ensure that innovation does not destroy the creator economy. Adobe also enables creators to request that AI models do not train on their personal uploaded content. Consequently, the firm attempts to balance the need for high-quality data with the rights of human artists.
How does Project Graph redefine the architecture of Design After the Prompt?
Design After the Prompt finds its most technical evolution in the upcoming release of Adobe Project Graph. This system introduces a node-based editor that moves beyond the limitations of simple text prompts. Designers can visually connect different AI models, Adobe tools, and custom effects to build complex workflows. This modular architecture allows for the creation of “capsules” that store specific creative logic for reuse. Consequently, a designer can package a proprietary process and share it across an entire creative organization. Design After the Prompt empowers professionals to build scalable systems that maintain perfect brand consistency across thousands of assets.
Graph Element
Functionality
Strategic Advantage
Node
Represents a single operation, model, or tool
Modular control over every creative step
Connection
Defines the data flow between different nodes
Enables complex, multi-stage transformations
Capsule
A self-contained, portable creative workflow
Reusability and easy sharing for teams
Interface
Visual editor for connecting diverse elements
Intuitive design for non-technical creators
The Project Graph system supports a multi-model future by allowing the integration of third-party models. Design After the Prompt embraces the idea that different tasks require different specialized artificial intelligence engines. For example, a creator might use Google Gemini for structure and Runway for motion within one graph. This flexibility prevents platform lock-in and gives designers the best tools for their specific creative goals. Furthermore, Project Graph makes complex tasks reusable, which saves hours of repetitive work for professional agencies. This shift toward systemic creativity ensures that the focus remains on high-level direction rather than manual panels. Design After the Prompt turns the creative process into a sophisticated engineering task that preserves the artist’s soul.
Project Moonlight and agentic creative assistance
Design After the Prompt gains further momentum through Project Moonlight, Adobe’s planned cross-app AI assistant. This assistant operates like a conductor of an orchestra, bringing multiple Adobe applications together in harmony. It carries context across different tasks and understands the creative intent behind every conversational request. For instance, a designer can tell Moonlight to organize a project or apply specific brand styles. The assistant then orchestrates the necessary steps across Photoshop, Premiere, and Illustrator automatically. Design After the Prompt relies on these agentic experiences to handle the tedious “final mile” of production.
The implementation of Project Moonlight allows for a hybrid workflow that combines natural conversation with precise hands-on editing. Users can engage with the assistant for ideation and then transition back to manual tools for refinement. This flexibility ensures that the designer always remains in control of the final creative outcome. Specifically, the assistant learns from user choices and adapts its recommendations to match an individual’s unique style. Design After the Prompt moves toward a world where the software anticipates needs before the user even articulates them. Consequently, creative teams can meet the soaring demand for content without sacrificing the quality of their work. This proactive partnership represents the ultimate realization of a truly human-centric AI strategy.
Why is Generative Engine Optimization crucial for the Design After the Prompt era?
Design After the Prompt also transforms how creators and agencies market their work to a digital audience. As traditional search engines evolve into answer engines, Generative Engine Optimization (GEO) becomes an essential practice. GEO involves structuring content so that AI systems like ChatGPT or Gemini cite it in their responses. In this new landscape, visibility depends on being the “source of truth” for a generated answer. Research indicates that GEO strategies can boost visibility by up to 40% in generative engine summaries. Therefore, designers must optimize their digital footprint to be easily interpreted and summarized by large language models.
To succeed in a GEO-led world, a brand must be understood as a structured entity rather than just a website. This requires using detailed schema markup, clear definitions, and evidence-based writing across all platforms. Specifically, including quantitative statistics and authoritative citations significantly increases the probability of an AI mention. Furthermore, the overlap between traditional top search results and AI-cited sources is now below 20%. This means that ranking first on Google no longer guarantees a place in the AI’s final answer. Design After the Prompt demands a strategy that prioritizes synthesis and authority over simple keyword density.
Strategic tactics for successful GEO implementation
Design After the Prompt forces agencies to document their decision-making logic as transparent and traceable digital content. Creators should publish “how we choose” articles and explainer videos to help machines learn their unique perspective. Additionally, implementing FAQ schema in JSON-LD format improves extraction accuracy for AI bots by 300%. Notably, AI engines track unlinked brand mentions across reputable sites, making digital PR more important than ever. Therefore, Design After the Prompt requires a consistent message and terminology across all social media and portfolios.
GEO Strategy
Primary Action
Expected Benefit
Entity Authority
Optimize about pages and author bios
Increases trust and likelihood of AI citation
Statistical Claims
Use specific numbers in headers and text
Boosts visibility by up to 40%
Extraction Ease
Use TL;DR blocks and short paragraphs
Helps AI engines summarize content faster
Consistency
Use the same phrasing for services everywhere
Strengthens the brand signal for LLMs
Digital PR
Earn mentions in authoritative industry blogs
Validates brand expertise to AI engines
Consistent language around primary services and target audiences helps AI systems connect a business to specific queries. Conversely, swapping terminology or mixing niches breaks the pattern recognition that generative engines rely on. Design After the Prompt demands that creators publish original research and whitepapers to establish topical authority. By earning citations from high-authority domains, a small design studio can compete with massive global brands. Consequently, GEO becomes the most important marketing frontier for anyone operating in the professional creative space. This focus on authority ensures that only the most reliable and expert voices are amplified by AI.
What are the leading trends in Design After the Prompt for 2026?
Design After the Prompt is shaping a visual landscape defined by high-impact aesthetics and human imperfections. Adobe’s 2026 Creative Trends report highlights a strong desire for content that engages all our senses. Tactile textures that mimic touch, sound, and motion are becoming a primary driver of digital engagement. People want to be immersed in hyper-realistic objects combined with playful distortions that feel truly physical. Furthermore, “All the Feels” signifies a move toward emotionally resonant imagery that sparks a deep human connection. This shift reflects a reaction against the cold, uniform perfection often associated with early AI-generated media.
Ironically, the heavy influence of technology is driving a massive backlash toward messy and chaotic design. The “Imperfect by Design” trend celebrates human flaws, hand-drawn scribbles, and sketchy underlines. Designers are becoming unbothered by perfection and instead embrace the raw and honest nature of their work. Consequently, Design After the Prompt encourages creators to use technology on their own terms to regain creative control. This trend prioritizes imagination and curiosity over creating for a predictable algorithm. Therefore, 2026 is the year where humanity becomes the most valuable asset in the creative process.
2026 Design Trend
Visual Elements
Emotional Goal
Tactile Maximalism
Squishy, puffy, and high-gloss 3D textures
To create a magnetizing sensory experience
Kinetic Typography
Liquifying, bouncing, and stretching text
To make reading feel high-energy and fun
Organic Imperfection
Earthy textures and hand-rendered fonts
To signal authenticity and human touch
Surreal Silliness
Visual jokes and exaggerated absurdist scales
To intrigue and entertain the audience
Cyber Gradients
Electric neon paired with deep blacks
To provide a futuristic, scifi aesthetic
Typography is also leaning toward excess and the absurd as a reaction against uniform computer fonts. We see oversized sans-serifs, bubbly letterforms, and wavy distorted fonts appearing in global branding. Additionally, “Bento Grids 2.0” bring organized chaos to layouts, providing scannable yet satisfying modular structures. Notable examples include Myntra FWD, which uses these grids to show mood boards instead of boring product lists. Design After the Prompt creates a new creative playground where tech empowerment and the inner child collaborate. This approach ensures that digital products feel helpful, human, and responsible in an overstimulated world.
The evolution of multimodal and sentient interfaces
Design After the Prompt moves beyond the screen to incorporate voice, gesture, and biometry into user interfaces. By 2026, UX design will focus on multimodal experiences that allow users to interact in whatever way feels natural. A user might start a request via voice and then switch to typing without losing the conversation’s context. Furthermore, interfaces are becoming “sentient” by adjusting their tone and empathy based on the user’s emotional state. This accessibility ensures that digital products are useful for everyone, including those with physical or mental limitations. Design After the Prompt requires a “lighter by default” mindset that prioritizes functional minimalism.
Specifically, “Explainable AI” is becoming a non-negotiable standard for professional digital products in 2026. Users won’t trust systems they cannot understand, making transparency a primary design challenge. Designers must create interfaces that show their reasoning before they act and allow for human intervention. Additionally, agentic UX means that master agents will coordinate specialized tasks automatically based on the user’s current context. This transition forces designers to oversee human-agent ecosystems rather than just designing fixed screens. Therefore, Design After the Prompt is a move toward intelligent, flexible, and responsible digital experiences.
Performance marketing at scale: The GenStudio revolution
Design After the Prompt enables marketing teams to deliver personalized content with incredible speed and accuracy. Adobe GenStudio for Performance Marketing allows brands to go from campaign intent to final assets in minutes. This application uses a conversational UI agent to understand campaign objectives, brand guidelines, and target personas. Marketers can then generate thousands of variations for A/B/n testing to see what resonates with their audience. Specifically, the platform tracks creative-level attributes like photography style and emotional tone. Consequently, teams can double down on high-performing content and refresh fatiguing ads instantly.
GenStudio Feature
Marketing Capability
Business Benefit
Content Production Agent
Conversations to content in minutes
Dramatically accelerates speed to market
Video Ad Assembly
Reframing and stitching hero videos
Reduces costs by avoiding manual reedits
Omnichannel Insights
Centralized data from TikTok, Meta, LinkedIn
Rationalizes return on ad spend (ROAS)
Multi-language Support
On-brand localized content in 12+ languages
Ensures consistency across global markets
Content Checks
Automatic brand and accessibility validation
Protects brand integrity at massive scale
Design After the Prompt ensures that content is never created for “content’s sake” but is driven by data. GenStudio integrates with Adobe Real-Time CDP to personalize experiences based on journey stage and persona preferences. This ensures that every asset is optimized for engagement and conversion in real-time. Notably, the system allows marketers to stitch branded intro and outro cards to videos automatically. This helps maintain compliance and brand safety across diverse social platforms like LinkedIn and TikTok. Therefore, Design After the Prompt allows creative and marketing teams to unify their workflows into a single campaign view. This closed-loop system transforms performance insights into actionable creative and maximizes impact across every channel.
Firefly Services: The programmatic future of professional design
Design After the Prompt finds its ultimate scalability through the Firefly Services API ecosystem. Organizations can embed over 30 generative and creative APIs into their existing marketing and production pipelines. These APIs cover a wide range of tasks, including text-to-image generation, video reframing, and lip-syncing. Specifically, the Object Composite API allows for placing product shots into realistic backgrounds with automatic lighting adjustments. Furthermore, the Custom Models API enables businesses to train private AI models on their own proprietary data. This ensures that every generated asset remains 100% on-brand and unique to the organization.
Notably, Firefly Services supports asynchronous processing for high-volume content demands and complex integration requirements. The system uses AES 256-bit encryption for all data at rest and provides pre-signed URLs for secure asset access. Consequently, developers can integrate professional-grade AI without having to manage complex on-premise infrastructure. Design After the Prompt is therefore a move toward a programmatic approach to creativity where every asset is an API call away. Adobe also provides managed services to help teams refine their use cases and optimize their models post-launch. This comprehensive support ensures that AI becomes a sustainable and highly profitable ingredient in the modern enterprise workflow.
Predictions for the post-prompt landscape of 2026
Design After the Prompt will reach full maturity when the distinction between AI and human creation becomes less relevant than the story. Scott Belsky predicts that consumers will crave scarcity, story, and process more than ever as AI content becomes ubiquitous. The story behind a marketing campaign or a film will determine its effectiveness in moving an audience. Specifically, effective creativity is what moves us, and models alone cannot achieve that emotional resonance. Consequently, professional opportunities for creators will grow as they focus on high-level questions rather than manual production.
As we approach the end of 2026, several technical milestones will redefine our expectations of visual quality. Adobe Firefly Image Model 5 will offer native 4MP resolution, capturing photorealistic details like lighting and skin texture. Furthermore, video generation will move from simple clips to timeline-based “creative assembly spaces” for generative storytelling. Users will direct scenes surgically by removing people or changing backgrounds with precise natural language prompts. Therefore, the role of the designer shifts toward a director who orchestrates a team of specialized AI agents.
2026 Milestone
Technological Driver
Practical Impact on Design After the Prompt
Native 4MP Generation
Firefly Image Model 5
High-definition print assets without upscaling
Node-Based Creativity
Project Graph
Reusable and scalable brand design systems
Agentic Assistance
Project Moonlight
Automatic orchestration of cross-app tasks
Universal Provenance
C2PA Compliance
Global verification of content integrity
Tactile Sentient UI
Multimodal UX Trends
Higher audience engagement via sensory depth
Notably, the rise of “vibe coding” will allow creators to design for emotional impact first. Visual elements like spreadsheets or bits of code will become a creative playground for new expressions. Design After the Prompt also predicts a surge in hyper-local vernacular design that roots global brands in regional cultures. We will see custom-designed typography in diverse languages that looks “hype” while staying culturally authentic. Therefore, the future of design is a flexible landscape where technology serves the unique and glorious humanity of the creator. This shift ensures that creativity remains a force that connects us deeply rather than a process that separates us.
Final conclusions on the Adobe AI strategy
Design After the Prompt is the only sustainable path for a creative industry that demands both speed and responsibility. Adobe’s strategy matters more than Midjourney because it builds the necessary systems for commercial safety and professional trust. By prioritizing provenance through the C2PA standard, Adobe ensures that authenticity remains a core value of the digital ecosystem. Specifically, the move toward the Controls Era provides designers with the precision they need to maintain their unique style. Furthermore, the integration of agentic AI through Project Moonlight and Project Graph will unlock a whole new category of creative exploration.
The controversy surrounding training data will likely continue as the industry defines the boundaries of ethical AI. However, Adobe’s transparent approach and legal indemnification provide a clear blueprint for responsible innovation. Design After the Prompt forces us to recognize that how we build is just as important as what we build. As creative scarcity disappears, the value of human taste, judgment, and emotional storytelling will only increase. Therefore, the goal of artificial intelligence is not to replace the creator but to expand the surface area of what is possible. Adobe Firefly and its surrounding ecosystem are the tools that will bring these possibilities to life in a way that respects the past while defining the future.
Frequently Asked Questions
What exactly is Design After the Prompt?
Design After the Prompt is a professional framework that moves beyond basic text-to-image generation toward a “Controls Era.” It emphasizes systematic integration, granular creative levers, and human-led orchestration within professional software suites rather than isolated prompt boxes.
How does Adobe Firefly ensure commercial safety for brands?
Adobe trains Firefly exclusively on licensed Adobe Stock and public domain content. Consequently, the company offers full legal indemnification to enterprise users, protecting them from potential copyright claims associated with AI-generated outputs.
What are Content Credentials and why do they matter?
Content Credentials are cryptographically bound metadata labels that record an asset’s history. They are vital in the Design After the Prompt era because they allow audiences to verify the origin and editing process of digital content, establishing essential trust.
What is the difference between Project Graph and standard AI tools?
Project Graph is a node-based editor that allows designers to connect multiple AI models and Adobe tools visually. This architecture enables the creation of reusable creative “capsules,” turning complex tasks into scalable and shareable brand systems.
What is Generative Engine Optimization (GEO)?
GEO is the practice of optimizing content to be cited and summarized by AI answer engines like ChatGPT or Gemini. It involves using structured schema, authoritative citations, and clear logic to ensure a brand remains visible in a post-search digital landscape.
Will AI replace professional designers in 2026?
No, AI will likely enhance the professional designer’s role. Design After the Prompt predicts that creators will move into high-level direction and orchestration, spending less time on tedious production and more time on strategic storytelling and creative exploration.
What is “synthetic laundering” and is it a real risk?
Synthetic laundering refers to training an AI on a library that already contains AI-generated images. While it creates some ethical optics issues, Adobe mitigates risk through rigorous moderation and a commitment to using only licensed or public domain data.
What visual trends should designers watch for in 2026?
Designers should focus on “Tactile Maximalism,” “Imperfect by Design,” and “Kinetic Typography.” These trends prioritize sensory engagement, human imperfections, and high-energy motion as a reaction against uniform, early-stage AI aesthetics.
Don’t hesitate to browse WE AND THE COLOR’s AI and Design categories for more inspiring content. In addition, feel free to check out our selection of the hottest graphic design trends in 2026.
Dirk Petzold is a graphic designer, content strategist, and the founder of WE AND THE COLOR. With a sharp eye for visual culture and a deep passion for emerging trends, Dirk has spent over a decade building one of the most respected platforms in the creative industry. His mission is to inspire and connect designers, artists, and creative minds across the globe through high-quality content, curated discoveries, and thoughtful commentary. When he’s not creating or curating, you’ll likely find him running mountain trails or exploring new ideas at the intersection of design and technology.
AI is coming for unprepared businesses. The tools that seemed futuristic last year are now mainstream. Your customers can access the same information, generate the same content, build the same websites. What if your business became obsolete because you didn’t see what was right in front of you?
The businesses that thrive in 2026 will be the ones that take action today. They’llbuild trust through human connection and prove their value beyond what any tool can replicate. ChatGPT can help you do the same. Copy, paste and edit the square brackets in ChatGPT, and keep the same chat window open so the context carries through.
Protect your business from AI: ChatGPT prompts to future-proof your company
Build a personal brand that AI cannot replicate
Faceless companies are dying. People want to know who runs the show. They want to buy into a belief system, not just a product. Someone in your company needs to show up online. They need to share strong opinions. They need to tell the story behind your brand. Astrong personal brand reduces your marketing cost to zero because people already trust you before they buy.
“Based on what you know about me, help me build a personal brand strategy for my business. Identify my strongest beliefs and values that could resonate with my target audience of [describe your ideal customer]. Create a 30-day content plan that shares these beliefs boldly across LinkedIn, including the specific topics I should cover and the stance I should take on each. Ask for more detail if required.”
Equip your team to outperform any AI tool
Stop hiring people who produce work worse than ChatGPT. Marketing assistants, copywriters, and social media managers who cannot outperform AI will drain your budget. You will spend money on resources you do not need. This does not mean replacing humans with robots. It means equipping your team to use AI as a multiplier. The result is faster output, better iterations, and content that improves every single week. Content is becoming a commodity. Slop will not cut it. Your team needs to create work that actually stands out.
“Based on what you know about my business, create an AI training framework for my team of [number] people in [their roles]. Include the specific AI tools they should master, the tasks they should automate, and the skills they should develop to stay irreplaceable. Design a 4-week implementation plan with measurable outcomes for each team member. Ask for more detail if required.”
Define your value beyond what AI can deliver
Here is the uncomfortable question every service provider needs to answer: Are you better than ChatGPT? If you sell coaching, consultancy, or any service, your value has to exceed what someone gets from a free tool. Most people are probably not paying you for what you think they are paying you for. Figure out what makes you human and go all in on that. Your lived experience. Your intuition. Your ability to hold someone accountable in real time.Quadruple down on the things no machine can touch.
“Based on what you know about me and my business, identify 5 unique value propositions that differentiate my service from what ChatGPT or any AI tool could provide. For each one, explain why a human client would pay premium rates for this specific value. Then create messaging I can use on my website and sales calls to communicate these differentiators powerfully.”
Collect social proof that AI cannot fake
Anyone can code a proof of concept in a few hours now. That is not the differentiator. The differentiator is brand and social proof. You need testimonials from happy customers. The more personal the better. Videos, quotes, screenshots of WhatsApp messages they send you. Solutions will flood the market. Anyone in their garage can create a business and start getting customers. The only way people know which to trust is through reviews. This is your competitive advantage.
“Based on what you know about me, create a systematic approach for collecting powerful testimonials from my customers. Include the specific questions I should ask to elicit compelling responses, the best format for each testimonial type, and where to display them for maximum impact. Design 5 follow-up message templates I can send after delivering results.”
Test and pivot faster than ever before
Because AI makes it so easy to add new services, redesign websites, and build new features, speed wins. You must rapidly test new features, new market approaches, and interrogate your customers to understand exactly why they buy and what else they want. The sooner you can pivot into the next profitable niche, the quicker you avoid being overtaken by AI.Stop playing small. Run experiments weekly. Let the data guide you. The businesses that move fastest will dominate 2026.
“Based on what you know about my business, create a rapid testing framework I can implement this month. Include 5 experiments I should run to validate new opportunities, the metrics I should track for each, and decision criteria for when to double down or pivot. Design a weekly review process that keeps me moving at speed.”
Future-proof your business before AI changes everything
The threat is real and the timeline is short. Build a personal brand that connects on a human level. Equip your team to use AI as a superpower. Define your unique value that no tool can replicate. Collect social proof that builds trust instantly. Test and pivot faster than anyone else in your space.
Over the past five years, my co-founder Anatolii Kasianov and I have been building HOLYWATER, an AI-first entertainment network reaching 60 million users globally. Each of our products is a breakthrough. My Drama dominates vertical video streaming with 40 million users. My Passion is the world’s #1 independent publishing platform outside China with 1,000+ titles. My Muse pioneered AI-generated vertical series.
Our technology stack, IP portfolio and distribution channels are extensive. But when I was asked in an interview what our startup’s moat was, I said the team. We have 285 talented people committed to building something that no competitor can replicate.
When reviewing candidates, most hiring managers see CVs as a set of rare data, such as years of experience, degrees and previous employers, searching for big names. However, the last one is definitely not worth chasing. Typically, people who have worked in a hot tub at a large corporation cannot get into the startup pace. This is even confirmed by research — former startup employees have more preferences for challenge, independence and responsibility. Therefore, it is certainly not worth hiring someone just because they worked for a large, well-known company. Instead, look beyond that — at their ability to solve challenges. That’s what’s significant in a startup.
At my company, we probe for three things that CVs can’t capture:
Problem-solving speed. I’m looking for someone with a “Let me figure this out” mindset. We give candidates real challenges during interviews, not theoretical algorithm questions, but actual problems we’re facing. I want to understand if they can get from confusion to hypothesis to test within hours, not weeks. The pace and curiosity matter more than perfection.
Value alignment. At HOLYWATER, we believe that imagination is the only limit. So we seek people who don’t see obstacles as stop signs.
Generalist instinct. The best performers don’t say, “That’s not my job.” They say, “I haven’t done this before, but here’s my plan.” This isn’t about hiring people without expertise but about hiring experts who refuse to be limited only by it.
Set a high bar for talent
On the one hand, you need to find the right person fast to build momentum, but on the other, it’s crucial to go slow to build quality. We don’t pick one or the other; instead, we go all in.
We have a lot of recruitment steps, and this rigorous selection process can make some candidates uncomfortable. But it helps us find our people faster, the ones who can navigate uncertainty and stay resilient.
Important: High bar is not about rejecting people who haven’t done the exact job before. It’s about finding people who are willing to move fast and take responsibility for their decisions.
When selecting employees, think about the future, not the past. Focus not on the candidate’s past achievements, but on their potential and how they can unlock it in your startup.
Build an ecosystem that supports creativity and growth
Hiring talented people is only half the battle. The other half is creating an environment where their potential can truly be realized.
Most companies cap people’s growth through invisible ceilings: rigid role definitions, hierarchical approval chains and cultures that punish experimentation. You end up with talented people operating at 60% capacity because the system won’t let them run faster.
We designed HOLYWATER differently. When someone joins our team, they enter an ecosystem where the concentration of exceptional people is extremely high. Each team member is an inspiration and a reference for others. The question shifts from “Am I capable of this?” to “How can I do what they just did?”
Each team member receives the opportunity to express themselves, take responsibility and implement their ideas, regardless of age or skill set. For example, our writers can pitch product ideas, and designers can challenge technical assumptions. This approach does not create chaos; on the contrary, it allows us to see things through a different lens and find new opportunities.
And finally, learning happens through immersion, not training programs. We don’t run formal courses or mandatory workshops. Instead, we make it normal to approach anyone and ask: How did you solve that? What tools accelerated your process? Why did you make that decision? Knowledge transfer happens organically because curiosity is rewarded and gatekeeping is rejected.
The environment you build either multiplies your team’s capabilities or divides them. Choose multiplication.
What you can do today
Stop searching for the perfect specialist to solve your next challenge. Start looking for curious minds who solve problems creatively using any tool available.
Treat building a team culture as seriously as building a product. While some founders are afraid to invest in their employees because they will “outgrow” the company and leave, be the ones who show that it is impossible to “outgrow” — because there is no ceiling. Raise the bar, inspire by example, allow them to prove themselves, give honest feedback and grow.
At that point, your competitors won’t be able to replicate your product. Even with access to the same tools, they’ll never catch up on years of learning, adapting and combining talent.
Bogdan Nesvit is the Co-Founder and Co-CEO of HOLYWATER, a tech company reshaping entertainment by empowering creators with AI and smart technology. HOLYWATER’s platforms — My Drama, My Passion, and My Muse — enable creators to produce high-quality stories and help define a new era of entertainment.
Shortly after Google announced its new Universal Commerce Protocol for AI-powered shopping agents, a consumer economics watchdog sounded the alarm.
In a now viral post on X viewed nearly 400,000 times, Lindsay Owens on Sunday wrote, “Big/bad news for consumers. Google is out today with an announcement of how they plan to integrate shopping into their AI offerings including search and Gemini. The plan includes ‘personalized upselling.’ i.e. Analysing your chat data and using it to overcharge you.”
Owens is executive director of the consumer economics think tank Groundwork Collaborative. Her concern stems from looking at Google’s roadmap, as well as delving into some of its detailed specification docs. The roadmap includes a feature that will support “upselling,” which could help merchants promote more expensive items to AI shopping agents.
She also called out Google’s plans to adjust prices for programs like new-member discounts or loyalty-based pricing, which Google CEO Sundar Pichai described when he announced the new protocol at the National Retail Federation conference.
After TechCrunch inquired about Owens’ allegations, Google both publicly responded on X and spoke with TechCrunch directly to reject the validity of her concerns.
In a post on X, Google responded that, “These claims around pricing are inaccurate. We strictly prohibit merchants from showing prices on Google that are higher than what is reflected on their site, period. 1/ The term “upselling” is not about overcharging. It’s a standard way for retailers to show additional premium product options that people might be interested in. The choice is always with the user on what to buy. 2/ “Direct Offers” is a pilot that enables merchants to offer a *lower* priced deal or add extra services like free shipping — it cannot be used to raise prices.”
In a separate conversation with TechCrunch, a Google spokesperson said that Google’s Business Agent does not have functionality that would allow it to change a retailer’s pricing based on individual data.
Owens also pointed out that Google’s technical documents on handling a shopper’s identity say that: “The scope complexity should be hidden in the consent screen shown to the user.”
The Google spokesperson told TechCrunch that this is not about hiding what the user is agreeing to, but consolidating actions (get, create, update, delete, cancel, complete) instead making a user agree to each one separately.
Even if Owens’ concerns about this particular protocol are a nothingburger as Google asserts, her general premise is still worth some thought.
She is warning that shopping agents built by Big Tech could one day allow merchants to customize pricing based on what they think you are willing to pay after analysing your AI chats and shopping patterns. This is instead of charging the same price to everyone. She calls it “surveillance pricing.”
Although Google says its agents can’t do such a thing now, it’s also true that Google is, at its heart, an advertising company serving brands and merchants. Last year, a federal court ordered Google to change a number of search business practices after ruling the company was engaged in anticompetitive behaviour.
While many of us are excited to welcome a world where we’d have a team of AI agents handling pesky tasks for us (rescheduling doctor’s appointments, researching replacement mini-blinds), it doesn’t take a clairvoyant to see the kinds of abuse that will be possible.
The problem is that the big tech companies that are in the best position to build agentic shopping tools also have the most mixed incentives. Their business rests on serving the sellers and harvesting data on consumers.
That means AI-powered shopping could be a big opportunity for startups building independent tech. We’re seeing the first few sprinkles of AI-powered possibilities. Startups like Dupe, which uses natural language queries to help people find affordable furniture, and Beni, which uses images and text for thrifting fashion, are early entrants in this space.
Until then, the old adage probably holds true: buyer beware.
Two tennis players are given the chance to train for a day with a world-class pro. The expert covers service grips, how to judge an opponent’s topspin, and when to stay at the baseline versus serve and volley. It quickly becomes clear there’s a problem. One student is an experienced tournament player. She absorbs the lessons and puts them into practice. The other is a complete novice. She finds the instruction confusing—and it ends up making her already shaky strokes even worse.
The takeaway: the value of performance-enhancing tools depends largely on the experience of the person using them.
Researchers are finding the same pattern when it comes to AI. For entrepreneurs with solid business expertise, AI improves performance. For those with less experience and judgment, it can actually make outcomes worse. At the end of the day, human judgment is still critical.
In today’s increasingly AI-powered business landscape, whether to use the latest tools isn’t really a choice—if you don’t, your competitors will. The real question is how leaders can ensure employees at every level get the most from AI.
Teach How To Use AI Analytically
Researchers looked at how a generative AI assistant helped small business entrepreneurs in Kenya. One of the findings was that for those who were already doing well, the AI tool boosted profits and revenues by 10-15%, according to the study. On the other hand, it lowered results for those on the low-performing side by about 8%.
The researchers noted a difference in the type of advice that users accepted from the generative AI tool. In short, low performers took worse advice—generic recommendations like lowering prices.
The lesson for business leaders is pretty clear: organizations must provide training and instructions on how to work with AI’s output.
For starters, it’s common knowledge that generative AI tools like Gemini and ChatGPT tend to hallucinate—confidently make up answers rather than admit they’re unsure. Beyond clear-cut hallucinations, you can’t always tell the quality of a response. That’s why it’s important to start with a mindset of evaluation, not assumption.
For example, at Jotform, I encourage employees to ask questions before accepting an AI tool’s answer. Questions like: What assumptions are being made? Is any context missing? Is this advice tailored to our specific [business/product/pain point]?
Generative AI can be a powerful brainstorming, writing, and research partner, but never accept an AI result at face value.
Define AI Points In Workflows
The standard leadership advice—provide employees with training—sounds like an obvious way to level the AI playing field. But speaking from experience at my own company, employees already work hard. They’re deeply committed to the mission. They also have rich personal lives, and that’s a good thing. Rolling out training programs that require after-hours learning or cut into personal time can be a tough sell.
One alternative is to integrate AI directly into existing workflows, so employees build proficiency and confidence on the job. But as teams decide where to incorporate AI, leaders must be explicit on how it fits within each workflow—and where human judgment remains essential. This helps establish ground rules for use, like consult AI for first drafts or working analyses, but leave final revisions and sign-offs to people. AI can offer guidance, but employees ultimately own the decisions.
AI can take over the tedious parts of a process, but humans should stay in the loop at the consequential moments. That’s how employees continue to hone their judgment and build business acumen.
Reward Great Ideas, Not Quantitative Output
The buzzword that’s sending chills down the spines of today’s leaders is “workslop.” Harvard Business Review defines it as “AI-generated work content that masquerades as good work, but lacks the substance to meaningfully advance a given task.” It’s the rapid fire list of ideas that ignores key considerations. It’s the first draft that falls completely flat, requiring a return to the drawing board.
Research confirms the cost of workslop: it can add nearly two hours of extra work and hurt productivity, collaboration, and trust. The onus is on leaders to set clear expectations for effective AI use—and to proactively discourage low-quality output.
Here’s the refrain I repeat often at my company: quantity matters little. Substantive quality is everything.
The sheer number of ideas generated or tasks completed is not a measure of success. What matters is output that moves the needle, such as proposing workable solutions. Even when an idea doesn’t ultimately fly, it still has value if it shows real ingenuity and clear thinking.
Leaders can reinforce this by rewarding great ideas and encouraging transparency around AI use. For example, even if an employee starts with an AI-generated suggestion, I want to understand the original idea, how they evaluated it, and how they revised it.
This causes an important shift, away from rewarding those who use AI the fastest and toward those who use it most thoughtfully. As employees build better judgment about when and how to rely on AI, organizations can cut back on workslop and fully harness the technology’s potential. Hopefully, they can level the impact of generative AI on performance, so that all can get the most from it.
One of the earliest turning points in personal branding, one that made career-minded professionals understand that they’re responsible for their careers and the visibility that shapes them, was the launch of LinkedIn in 2003. Since then, career visibility has followed a simple rule: polish your resume, keep your LinkedIn profile current and compelling, and show up to meetings awake. But that rule no longer holds, thanks to AI.
In The Age Of AI, Career Visibility Works Differently
Although we’ve all become skilled Googlers, search is no longer a simple query-and-results experience. It’s increasingly AI-assisted. People are asking Google, other search engines, and AI platforms questions like “Who’s the leading expert in storytelling?” or “Identify people who understand video production and graphic design.” This shift is often referred to as Generative Engine Optimization, or GEO. Unlike traditional SEO, which focuses on ranking pages, GEO is about making your expertise easy for AI systems to understand, trust, and recommend. But AI tools and the AI summaries that appear atop Google searches just don’t have access to your LinkedIn profile. That means the hard work you did to make it reflect who you are and what makes you exceptional no longer delivers the same visibility it once did.
At the start of the personal branding boom, I recommended that professionals have a brief website/blog to showcase their expertise. LinkedIn, at the time, was rudimentary in what it offered, and with a website you had total control of how you tell the world about yourself. Over the years, though, LinkedIn has added features that made your profile a near equivalent of having your own home on the web. The customizable banner, the Featured section that allows you to use multimedia to highlight your brilliance, and the ability to include long-form content to showcase your thought leadership are just a few of the many enhancements LinkedIn has made over the past two decades. But, because LinkedIn is a mostly closed ecosystem, accessing much of its content requires authentication. That means AI systems have limited crawl access, limited visibility of content that is public, and may not be able to attribute content you created to you. That’s a major personal branding challenge.
What AI Search Changes About Personal Branding
If you don’t own a piece of the internet that AI can actually read, you’re invisible to a growing share of opportunities. When an AI Overview is present, the average click-through rate for top-ranking organic links can drop by 34.5% to nearly 50%, according to Pew Research Center. People are relying on the AI summaries to answer their questions. That’s why a personal website is once again valuable, now, as your AI-readable career home base. AI systems favour:
Open, crawlable content
Clear authorship
Consistent themes across pages
Signs of expertise over time
AI looks for structure, clarity, and patterns. Different audience, different rules. And the impact on your career can be serious. If AI can’t see you, it can’t recommend you.
What A Personal Website Does That LinkedIn Can’t
Having your own website puts you in control of three things that AI cares deeply about.
Context. You can explain not just what you do, but why you do it, who you help, and how you think.
Depth. AI favours original thinking. Articles, insights, frameworks, and your unique point of view matter more than job titles.
Ownership. Your site is stable. Platforms and algorithms come and go. Headlines change. Your site is the one place your story doesn’t get rearranged by someone else’s design team.
How AI Actually Finds People
AI tools don’t search the way you do. They synthesize. They look for:
Repeated themes across content
Clear positioning language
Specific problems you solve
Evidence you’ve been thinking about this for a while
They reward clarity over cleverness. Specificity over buzzwords. Humanity over hype. Those are key branding trends for 2026 and beyond. And that’s good news for those who seek to be real in the virtual world. If your expertise is buried inside a profile behind a login, AI wasn’t designed to connect the dots. Your website, though, gives it dots to connect.
What To Include In A Career-Smart Website
Here’s the good news. Having your own website does not mean you need 20-pages of content and an intricate design with multiple tabs. What you need is brand clarity. At a minimum, include these five elements.
A clear homepage statement
In plain language, say who you help, what you help with, and why it matters. No mystery. No keyword games. AI prefers direct sentences.
A human About page
Tell your story like a person, not a resume. What life experiences shaped your thinking? What do you believe? What’s your purpose? This is gold for AI and even better for building an emotional connection with fellow humans.
Proof of thinking
Articles, essays, talks, newsletters, or case studies. Original content screams expertise far louder than boring, trite jargon like “results-driven, team-oriented professional.”
A focus area or services page
Be specific about your primary focus area, not all the things you can do. Focus on just those you want to be known for. AI rewards focus, and personal branding is about being known for something, not 100 things.
Demonstration of credibility
Include media mentions, speaking, certifications, notable clients (for brand association), and projects. These help you build trust with both humans and machines.
AI Visibility Best Practices Without The Tech Headache
You don’t need to be an SEO wizard. You just need to be consistent.
Use the same language across pages. If you help leaders build thought leadership, say it more than once. AI notices patterns.
Write like you talk. AI models are trained on natural language. Stiff corporate writing actually works against you.
Update occasionally. Fresh content signals relevance, but you don’t need a blog schedule that takes over your life. One thoughtful, on-brand piece every two to three months will suffice.
Make authorship obvious. Your name, bio, and perspective should be clear on every piece of content. Anonymous wisdom doesn’t rank, and it won’t get associated with you.
Connect your site to LinkedIn. Think of LinkedIn as the front porch and your website as the rest of the house.
Your Website Signals A More Modern Career Strategy In The Age Of AI
This isn’t really about websites. It’s about augmenting platform-dependent visibility with owned visibility. You still need to master LinkedIn, but AI is changing how opportunity finds you. Recommendations will increasingly come from synthesis, not SEO or search results. The people who show up will be the ones who make it easy for AI to understand who they are, what they stand for, and why they matter. In other words, get clear on your personal brand!
It’s Time To Build An AI-Friendly Personal Brand Engine
In a world where AI is doing the asking, your website is how you answer before anyone even knows your name. And the rules of working with AI are empowering. It goes beyond trying to game algorithms by having all the right keywords in everything you post. The next era of visibility goes back to the origins of personal branding. It’s about being the real, human you, consistently without apology or hesitation.
William Arruda is a keynote speaker, author, and personal branding pioneer. He speaks on branding, leadership, and AI. Watch his AI-Powered Personal Branding Session to learn more about the intersection of AI and personal branding.
The market for AI-generated influencer scripts is rapidly expanding due to rising demand for personalized content, increased digital marketing adoption, and innovation in AI technologies. Opportunities lie in enhancing brand engagement through scalable, interactive content, advancing AI-driven storytelling, and leveraging real-time analytics.
The artificial intelligence (AI)-generated influencer script market is experiencing robust growth, projected to expand from $1.18 billion in 2024 to $1.48 billion in 2025, with a compound annual growth rate (CAGR) of 25.7%. This surge is driven by the demand for personalized digital content, increased investment in influencer-marketing campaigns, and the widespread adoption of virtual influencers. The market reflects a growing consumption of social media content, rising global marketing budgets, and a shift towards cost-efficient content creation models.
Looking ahead, the AI-generated influencer script market is anticipated to reach $3.66 billion by 2029, at a CAGR of 25.3%. This growth is underpinned by a focus on audience engagement, authenticity, and the trend of brand-creator collaborations. The demand for scalable marketing solutions and real-time analytics is rising, fuelled by consumer preference for interactive experiences and behavioural insights. Key technological trends include advancements in generative language models, emotion-driven storytelling algorithms, and automated synthesis for influencer content.
The ongoing rise of digital marketing is a key driver for the AI-generated influencer script market. With digital marketing involving the promotion of goods via channels like social media and search engines, the industry’s expansion is supported by increased online commerce and branding efforts. AI-enabled influencer scripts enhance digital marketing by offering personalized content, optimizing audience targeting, and ensuring campaign efficiency. For example, Eurostat reported that in 2023, 60.9% of EU enterprises utilized social media, highlighting the trend toward digital engagement.
Prominent industry players, such as Pictory and HeyGen, are advancing technological capabilities within the AI script market. In February 2024, Pictory introduced its Custom Pictory GPT tool for transforming user inputs into full scripts, enhancing content creation through automated video production. In April 2025, HeyGen partnered with HubSpot to create personalized videos directly within HubSpot’s workflows, utilizing customer data from its CRM platform to enhance engagement and streamline content production.
I keep catching myself doing this thing lately: staring at an Instagram ad, listening to a podcast intro, scrolling past a post — and wondering, ‘Wait, is this AI?’ Turns out, I’m not alone. A survey by Getty Images states that 76% of people agree: ‘It’s getting to the point where I can’t tell if an image is real’. And it’s this simple sentiment of wondering whether something is real or not that raises an important question for us marketers and creators: How can we shift the narrative of doubt and start focusing on building trust instead?
I’ve been reflecting on this for a while now, asking myself what really makes me trust something online and I keep coming back to the same answer: connection. I trust something when it makes me feel connected.
So that’s when it clicked for me: we double down on what AI can’t replicate. We build connections. We build community. Real, human community. Because while technology can evolve, only people can scale trust. And in an age where so much feels synthetic, trust is about to become your most powerful asset.
If you’re curious about why I’m so passionate about this topic, it’s because community building has changed me. The first time I built a community was in 2021, and it began with 20 inaugural members that quickly grew to 140 founders. In less than a year, we evolved it into a full-fledged fellowship program, which continues today under the European EdTech Alliance.
Thanks to this experience, I have some exciting news for small businesses and creators. You already have what it takes to build trust. According to an article published by WorldCom, micro- and nano-influencers are on the rise because the trust you build runs deeper. Brands are paying attention, and creators who prioritize connection over clout tend to have more engaged communities. And that kind of impact is the perfect testament of a deep, meaningful connection. Something that’s nurtured over time, not created overnight.
In this article, I’ll share why I believe building community can be your superpower right now — not just for marketing, but for building real trust and deep connections. I’ll dive deep into what makes communities such a long-lasting strategy, how to build and sustain one authentically, and even how AI can support (without replacing) the human touch that makes it all work.
Community as a strategy
Unlike marketing campaigns and content pieces that are often one-off and time-bound, a well-built community can evolve and live on by becoming part of your mission. That’s what makes it so powerful. But why does it truly stand the test of time?
Because community taps into something deeper than metrics: emotion and belonging. People want to be part of something meaningful. When you create a space where members feel engaged, supported, and seen, you’re not just building a following; you’re building trust.
That trust creates a bond, not just between members, but between your community and your brand. Over time, you earn a place in their minds and hearts as more than just a product or creator. You become the go-to resource not because you ran a flashy ad, but because you consistently showed up for them. You gave them value, connection, and a sense of belonging.
And when people feel good about being part of your community, they talk about it. They recommend you. They become your advocates. This kind of organic social proof and authority can’t be bought, it has to be built. That’s the true power of community. It’s a space others want to be part of. From a business perspective, it’s hard for members not to fall in love with your brand, thanks to the positive experience your community offers.
When I built EdTech Female Founders back in 2021, we weren’t thinking about AI at all (it wasn’t really a thing yet for most marketers). But the community still thrived. It connected people, sparked ideas, helped increase brand awareness, pushed a great deal of content across social, but most importantly, it created a space others wanted to be part of. If this worked in a pre-AI world, I believe it can work even better now. In fact, I believe building community is more essential than ever. In a landscape transformed by AI, people crave real human connection, and the brands and creators that win will be those that can deliver spaces that unite.
Why community should matter to you (now more than ever)
When your audience sees the real people behind the product, behind the content, you’re not just selling something or posting something. You’re building and creating with them.
Often, your early followers know you. They’ve DM’d you. They’ve seen your behind-the-scenes stories and lessons. They know what you stand for. That creates a level of emotional equity that big brands struggle to earn.
While AI can generate thousands of words in seconds, it can’t generate trust, loyalty, or belonging. Those things are built through consistent, real interactions, and that’s something you can deliver. So, how can you get started?
A strong community strategy starts with authenticity
When everything feels artificial, authenticity becomes your pillar.
Start with real faces, real values, and a real purpose that your community can jump on board with, not just because it sounds good, but because it resonates.
Ask yourself: What’s something you are already doing that could bring people together? Or what’s something that’s missing that you should focus on?
If you’re innovating in a specific niche, can you create a space for experts to swap ideas and insights?
If your segment lacks diversity, can you build a platform to elevate the voices that often go unheard?
If you’re launching a product that reimagines how people live or work, can your community help others do the same?
Your community doesn’t need to be huge to matter or have an impact, but it does need to make sense. It needs to align naturally with your focus, and you should also want to build it. Doing it just for marketing’s sake comes across as inauthentic, and that defeats the purpose. A strong community is real, offers value, and grows from genuine care and intention.
How to keep the spark alive: Nurturing your community long-term
Community is not a transaction, it’s a relationship, and relationships need care and consistency.
Think about how you can show up for your people. Are you giving them something they genuinely value? What’s the reason they should stay connected? You need to build one!
To keep that spark alive, you need to constantly give people something that ignites it! Here are a few ideas on how you can do just that:
Offer exclusive value: Try and think of what free resources you could put together that your members would find interesting. This can be anything from thought leadership content, tutorials, beta access to product features or programs, webinars, and even behind-the-scenes content.
Foster meaningful conversations: Build spaces where members can share their thoughts, network with each other, and feel seen. This could include a dedicated Q&A channel or a space for members to share their own experiences and insights with each other. If you notice this channel going quiet, take the initiative to start a conversation and keep the momentum alive.
Create regular touchpoints: Diversify where you get your community engaged. You can do this by expanding to meetups (virtual is great too!), sending them newsletters with community updates, or those awesome resources you’ve created just for them. Try to keep things fresh and meet your members where they like to be.
The more consistently you show up with real value, the more trust you build. That’s what can transform passive followers into loyal advocates, the kind who root for you even when you’re not in the room.
It might sound like a lot, because it is. No one said building a community is easy. But hey, we’re in the age of AI, remember?
Integrating AI without losing the human touch
You might be surprised by this section, but I truly believe AI can play a big role in helping us scale, even in community building. What matters is how we use it.
AI should support your community-building efforts, not replace the soul of it. Think of it as aid, not the drive. If you’re building something that matters, you shouldn’t burn out trying to do everything yourself. But you also shouldn’t lose the warmth that made people care in the first place.
Here’s how to strike that balance:
Use AI to research your ICP (Ideal Community Persona). Let AI handle the heavy lifting when it comes to understanding who your potential people are and what they care about (at least in the early stages when you don’t have a ton of users). It can uncover trends, sentiments, and even unmet needs.
Use AI to spark conversations. Coming up with content ideas every day is hard, but AI can help you generate prompts, questions, and topics that resonate with your members.
Use AI to streamline onboarding. From automated welcome messages to helpful chatbots, AI can make sure new members feel supported from day one, just don’t forget to add a human touch at the end of the funnel.
The key is to use AI to support the person running the community – not replace the human touch. On the contrary, this should give the manager more time to really focus on deepening those connections.
Real companies, real communities: What this looks like in action
We’ve talked about how to build community, but what does it look like in real life?
Here are 3 community examples that continue to inspire me, and that might just spark some ideas for your own journey:
A global space where women lead the climate conversation, connect across borders, and drive real business impact. Their Slack channel brings together over 4,500 members from around the world, offering a daily touchpoint for ideas, support, and collaboration. One standout feature is their speaker database, which helps connect climate experts with event organizers, ensuring fresh, diverse voices are heard on stages across the world.
Notion turned its users into its best teachers. Through events, videos, templates, and workshops, community members actively help others master the tool. The magic? It’s all built by people who actually use Notion every day, making learning feel real, not rehearsed. Whether you’re into productivity, design, or teaching, there’s a space for you here.
I couldn’t not include Buffer. Their community isn’t just for social media experts, it’s a co-creation hub. From feature suggestions to product feedback channels, users actively shape the platform’s evolution. Initiatives like Creator Camp support users in staying consistent, while casual check-ins foster genuine connection. It feels like a shared home where everyone can put a brick to build.
Let’s build what AI can’t, while letting it help where it can
In a world rapidly filling up with auto-generated everything, a real community becomes the most valuable thing you can build. Not just because it feels good (though it does), but because it gives you an advantage that’s hard to replicate: loyalty, trust, and belonging.
So while everyone else scrambles to scale with AI, take a moment to scale something different, something timeless.
Build community, because you have the power to make someone feel seen, trusted, and supported and that’s where the magic can still live.
Here are five things in small business technology that happened this week and how they affect your business. Did you miss them?
This Week in Small Business Technology News
Small Business Technology News #1 – As AI search hits 700M users, new WordPress tool democratizes ‘AI SEO’ for small businesses.
A new WordPress plugin called LovedByAIhas launched to help small businesses get found in the growing world of AI-powered search. As AI “answer engines” like ChatGPT and Gemini surpass 700 million weekly users, traditional SEO alone isn’t enough for visibility in AI responses. LovedBy.AI is designed to help small businesses with gap analysis to find where site content isn’t structured for AI. Features also include automated schema/data formatting so AI bots understand core business details; and visibility tracking & performance metrics – similar to enterprise tools but scaled for smaller sites. The goal is to help non-technical site owners prepare their websites for AI discovery without hiring developers or paying hundreds of dollars per month.(Source: EIN Presswire)
Why this is important for your small business:
Ask any marketer, or any company that relies on Google to drive their online sales or get their website found and they’ll tell you that AI is starting to worry them. Clearly, big changes are happening and 2026 is going to see a measurable shift. For now, Google still dominates in search. But many publishers and other e-commerce sites I know are experiencing significant drop-offs in traffic because people are using AI assistants to do their searching and provide answers which means that click-throughs are much less. You can argue that if someone does click-through they are a more qualified lead. But regardless, traffic is trending down on sites and there’s a significant opportunity for both the platforms and savvy marketing tech people to figure out how to maximize SEO as these AI chatbots take over.
Small Business Technology News #2 – How ChatGPT could change the face of advertising, without you even knowing about it.
Rapidly advancing AI – especially ChatGPT – may transform digital advertising into something far more personalized, automated, and harder for consumers to recognize. With 800 million weekly users, OpenAI is exploring ways to integrate advertising directly into conversational experiences. For example, ChatGPT Atlas – introduced in 2025 – can automate purchases based on a user’s browsing history. The Agent Mode setting in Atlas will also offer suggestions based on past searches and lets users ask ChatGPT to find past items and add them to carts. OpenAI’s CFO has openly said the company is “weighing up an ads model” but early experiments have shown that users dislike feeling “sold to” and indicated that some degree of autonomy is essential to making a final decision. Based on that feedback, OpenAI is rethinking how ads should appear – likely in more subtle, blended ways. As the technology continues to advance, advertising will become more personalized and harder to distinguish from neutral advice. (Source: Tech Xplore)
Why this is important for your small business:
This is OpenAI’s potential strategy. It will change. And I expect its many competitors will also have their own ideas. It’s going to be the wild west for a lot of advertisers over the next few years as our AI geniuses try to figure out how to monetize ad spend. The good news is that this will take away from Google monopoly on online ads and, which will give more affordable choices to small businesses.
Small Business Technology News #3 – How marketers rank this year’s generative AI, video tools.
Generative AI tools advanced rapidly this year, and Digiday’s report card highlights which tools delivered and which fell short. Google’s Nano Banana image generator is considered the “golden standard” for its precision, hyper‑realistic output, and reduced “AI sheen” – a too perfect quality that’s noticeable in images. Google’s VEO – text-to-video generative AI model – also received high marks as the most robust video model that produces strong character consistency, cinematic interpretation, and prompt execution. AI tools that received a “B” grade include OpenAI’s text-to-video tool Sora for its cinematic quality, lighting, and consistent environments. Though Sora was a major breakthrough marketers found Google’s VEO easier to integrate across creative workflows. Marketers also said they use these tools in tandem with one another and their proliferation and as one exec put it, “Consistency is probably the number one thing you’ll need to give people.” (Source: Digiday)
Why this is important for your small business:
As I’ve previously written, the AI image creators offered by the major platforms are still not business ready. They’re amazing. They’re light years ahead of where they were just a short time ago. They’re fun. But for the typical business owner they’re not worth using professionally. I do believe – in a very short time – they will become even better, more responsive, more accurate, more reliable. I also think that they will become even easier to use and not require teams of tech people to manipulate.
Small Business Technology News #4 – Inbox zero for 2026: Free up 15GB of Gmail storage without deleting a thing.
Jason Chun of CNET explained a clever way to free up your Gmail storage back to the full 15 GB limit without deleting your old emails – essentially getting to “inbox zero” without losing anything. (Source: CNET)
Why this is important for your small business:
“All I had to do was create a second Gmail account,” Chun said, avoiding the fees for extra storage. If account holders choose this method, Chun recommends backing up email messages via “Google Takeout” and then download them to a computer or external hard drive (then delete them once the transfer is completed). Transferring old emails to the newly created account usually involves enabling POP (Post Office Protocol) – the transfer setting where old messages get pulled into the new account while keeping them safe. Chun gives his readers a step-by-step guide to transfer old emails and says depending on how many messages are moved, it doesn’t take long.
Small Business Technology News #5 – 10 ecommerce trends that will shape online retail in 2026.
Brian Warmoth of Digital Commerce 360 listed 10 ecommerce trends to expect in 2026 based on the factors that were at play in 2025 (tariffs, consumer behaviour). (Source: Digital Commerce 360)
Why this is important for your small business:
Among the trends that caught my eye was the advancement of agentic commerce. Warmoth says that AI assistants aren’t just replying to prompts anymore; they’re automating tasks like checkout, research, and curated shopping lists, and 2026 could see them interoperate with external tools and platforms. For those catering to the younger crowd, Warmoth says that Gen Z will be more accepting of virtual shopping assistants, with younger shoppers leading in adopting AI helpers for discovery and buying, while retailers learn where different age groups diverge in behaviour.
Each week I round up five small business technology news stories and explain why they’re important for your business. If you have any interesting stories, please post to my X account @genemarks
Feature image credit: Photo Illustration by Pavlo Gonchar/SOPA Images/LightRocket via Getty Images) SOPA Images/LightRocket via Getty Images
