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The B2B commerce landscape is undergoing a profound transformation driven by advancements in AI, shifting buyer expectations, and increasing economic pressures. Companies effectively leveraging digital technologies while staying consumer-focused will gain a competitive edge while those slow to adapt risk falling behind in an evolving market.

This article explores seven major trends expected to define the future of B2B commerce based on insights from Forrester, IDC, and leading industry examples.

1. Artificial Intelligence Revolutionizes B2B Commerce

AI has shifted from experimental technology to a vital instrument embedded in every aspect of B2B operations. Organizations are utilizing AI to enhance product recommendations, optimize search relevance, and implement AI-powered strategies like dynamic pricing.

Key applications of AI in B2B commerce include predictive analytics and generative AI. With predictive analytics business can detect customer churn risks, enabling proactive retention strategies. From drafting automated responses to helping sales teams make informed decisions in real time, generative AI is reshaping the customer experience.

Despite AI’s potential, some businesses still struggle to achieve meaningful results due to disconnected data and fragmented systems. Establishing a robust AI adoption strategy remains critical as companies aim to fully integrate AI into their operations.

2. The Rise of Smart Procurement Systems

Industrial B2B organizations are beginning to deploy AI-driven procurement agents to automate purchasing decisions. These agents can analyze massive amounts of data to quickly evaluate factors such as costs, ESG compliance, and supplier data, ensuring informed decision-making. Per Forrester, almost 30% of B2B firms will integrate AI buying agents1.

For example, Siemens has applied AI procurement tools to streamline supplier management, achieving cost efficiencies while adhering to sustainability mandates. Businesses prioritizing ESG-compliant procurement tools will find themselves better positioned as these practices become industry standards.

3. Challenges in Chatbot Adoption

While advances in conversational AI technologies are evident, many organizations remain hesitant to adopt them broadly. According to Forrester, only 20% of brands are projected to implement conversational AI for commerce by 20251.

A key concern lies in the limitations of traditional, deterministic chatbots—systems designed to follow predefined paths and respond within a fixed decision tree. These chatbots often fall short in handling the complexity and variability of real-world human interactions. In contrast, agentic AI systems offer a more dynamic alternative. By learning autonomously and adapting in real time, they can navigate evolving conversations and create their own paths forward. For businesses, investing in this next generation of conversational AI agents unlocks more natural, responsive client interactions while helping to overcome persistent integration and user experience challenges.

4. Augmenting Human Relationships with AI

AI’s role in enhancing efficiency does not diminish the need for human expertise in B2B interactions. While AI simplifies tasks like personalization and data processing, strategic partnerships and high-value sales still rely on relationship-building. According to IDC, integrating AI efficiencies with high-touch customer engagement will drive the strongest business results2.

Leading organizations are integrating AI as a supportive tool alongside traditional methods. For instance, PROS Collaborative Quoting empowers sales teams by combining AI tools with human oversight for seamless, bi-directional client interactions. This hybrid approach preserves trust while boosting efficiency.

5. Redefining Sales Strategies with AI “Coworkers”

Sales teams are finding that partnering with AI agents can provide support in managing customer data, analyzing patterns, automating repetitive tasks, and optimizing sales strategies—ultimately enhancing productivity. Forrester predicts that by 2025, 40% of businesses will adopt these virtual assistants3.

An example of this is the 2024 collaboration between PROS and Microsoft to create smart quoting solutions. These tools enable sellers to generate emails with accurate, personalized quotes attached, demonstrating how AI coworkers can simplify daily tasks and enhance responsiveness, solidifying the role of AI coworkers moving forward.

6. Composable Architectures Offer Agility and Growth

To manage the growing complexities of B2B commerce, IDC recommends businesses move toward composable architectures and API-first solutions2. Unlike traditional systems, these modular platforms provide flexibility, scalability, and seamless integration with other tools.

With composable architectures, businesses gain the agility to adapt quickly to market demands, streamline workflows, and create personalized customer experiences. Businesses should leverage pre-defined out of the box experiences and workflows, followed by bespoke and unique experiences leveraging some of their core commerce componentry. Organizations leveraging these advanced platforms can innovate rapidly while maintaining competitive advantages in an evolving commerce ecosystem.

7. Compliance Moves to the Forefront of Strategy

As data privacy regulations and sustainability standards evolve, forward-thinking businesses recognize the importance of embedding compliance mechanisms directly into their strategies. IDC highlights that proactive compliance is no longer optional; it is a necessity for avoiding financial and reputational harm2.

Advanced risk monitoring tools, automated reporting, and responsible AI frameworks are helping companies meet regulatory requirements. Businesses that integrate transparency, ethical AI practices, and sustainability efforts into governance structures will benefit from enhanced trust and reduced risks.

Looking Ahead

The future of B2B commerce lies at the intersection of AI, strategy, and execution. Companies that prioritize innovation, implement customer-centric solutions, and adapt to compliance standards will emerge as industry leaders. Those that hesitate to modernize risk becoming less competitive in today’s fast-moving market.

If your organization is considering integrating AI to transform operations and customer interaction, now is the time to act. Whether it’s optimizing procurement, redefining sales processes, or adopting composable architectures, today’s investments will set the foundation for tomorrow’s success. Competitive advantage is no longer a choice; it’s a business imperative.

Feature Image Credit: Dowell via Getty Images

By John Bruno

BRANDVOICE | Paid Program

John Bruno, VP of Strategy at PROS, leads the analyst relations, competitive intelligence, and strategy teams at PROS. He is responsible for go-to-market strategies across PROS travel and B2B solutions. John has more than 15 years of B2B software experience, and has formerly served as the head of product at an enterprise eCommerce platform and as a Senior Analyst at Forrester Research. Read More

Sourced from Forbes

By John Winsor

In a major shift for the creative industry, Microsoft recently launched an ad for its Surface line that was almost entirely created by artificial intelligence. Using tools like Hailuo and Kling, the design team generated every scene except for a few human close-ups, such as hands typing. The ad ran for three months without anyone noticing it was AI-made, proving Shelley Palmer’s insight“If you cannot tell the difference, there effectively is no difference.”

This milestone highlights a critical transformation in how brands create content. As Palmer smartly frames it, creative work now falls into two categories: “required” content, practical, executional work increasingly handled by AI, and “inspired” content deeply human storytelling still beyond AI’s full reach. Microsoft’s Surface ad achieved a 90% reduction in time and cost while maintaining broadcast-quality standards. For brands and agencies alike, this signals an urgent need to rethink how creativity is produced, valued, and rewarded.

When I led strategy at Crispin Porter + Bogusky, one of the most decorated creative agencies in history, we focused intensely on unpredictable human creativity. Later, at Victors & Spoils, we pioneered open talent models, demonstrating that creativity could survive and thrive in new structures. In my book Open Talent, I argue that embracing open networks and AI-driven collaboration doesn’t diminish creativity; it liberates it, amplifying human potential by automating required content.

The implications are clear: AI can now efficiently handle the “required” creative work, freeing human teams to focus on the “inspired” work that moves hearts and builds brands. However, the economic efficiencies AI brings are already compelling brands to recalibrate their balance between human creativity and machine-driven execution.

Brands now have the opportunity to fundamentally rethink their creative strategies. First, it’s no longer necessary or financially wise to pay for agency overhead. Freelancers, empowered by AI tools and connected through emerging platforms like Hence Creative, can deliver exceptional results with greater agility and at a fraction of the cost. The bloated agency model is giving way to streamlined, open networks that prioritize speed, innovation, and return on creative investment.

Second, companies must recognize the opportunity to automate and streamline their required content. AI can rapidly generate high-quality, functional creative assets, enabling brands to reduce costs and reallocate resources toward more strategic and emotionally resonant initiatives. This shift is not about replacing creativity; it’s about reclaiming the time and space for deeper innovation.

At the same time, AI’s ability to handle routine creative tasks allows human teams to focus on what matters most: inspired storytelling. Freed from production-heavy demands, creative professionals can push boundaries, explore cultural narratives, and forge the emotional connections that truly engage audiences. In this new era, the brands that thrive will be the ones that understand creativity as more than content; they’ll see it as a profound emotional dialogue with consumers.

Finally, brands must adopt an open talent mindset. AI reaches its greatest potential when paired with diverse human insights. By tapping into a global pool of freelance and independent talent, brands can access broader perspectives, richer ideas, and faster innovation. AI isn’t a competitor in this model; it’s a collaborator, amplifying the capabilities of a dynamic, distributed creative workforce.

Ultimately, the adoption of AI-generated content might spell the end of traditional ad agencies that cling to outdated structures. Those unwilling to evolve will find themselves struggling to survive. But those who embrace AI as a tool for enhancing human creativity, blending technology with diverse, open networks of talent, will lead the next wave of storytelling innovation.

The future of creativity won’t be built behind the walls of traditional agencies. It will emerge from open ecosystems, where humans and machines collaborate, liberated from legacy systems, and ready to meet a new era of brand building.

Feature Image Credit: Brands&People

By John Winsor

Follow me on Twitter or LinkedIn. Check out my website or some of my other work.

Sourced from Forbes

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Artificial intelligence is rapidly transforming the creative landscape, particularly in the visual arts.

Since 2022, AI-powered image generation tools have exploded in popularity, flooding social media platforms and sparking intense debate within the art community. These tools, often trained on vast datasets of existing images scraped from the internet, allow users to create intricate, photorealistic, or abstract images simply by typing text prompts. This technological leap has fuelled a burgeoning market, with the global AI image market projected to surpass $0.9 billion by 2030, a significant jump from $0.26 billion in 2022. This rapid expansion begs the question: who stands to gain from this boom, who is being left behind, and what does the future hold for the intersection of art and artificial intelligence?

The Beneficiaries: Tech, New Creators, and Expanding Markets

The most obvious beneficiaries of the AI art boom are the tech companies developing and deploying these powerful generative AI models. Platforms offering AI image generation tools, some operating on subscription models or selling credits, stand to gain significantly as adoption increases. These tools democratize art creation, allowing individuals without traditional artistic training to generate visuals, sometimes leading to commercial success through platforms like Etsy or Redbubble. Some artists are even finding novel ways to profit by selling the sophisticated text prompts used to generate specific styles or images.

Beyond individual creators, businesses are adopting AI-generated art to streamline workflows, particularly in marketing and advertising, saving time and potentially costs associated with hiring human designers for specific tasks. Some artists themselves are embracing AI as a collaborator, using it to brainstorm ideas, explore new styles, expedite parts of the creative process, or enhance their existing work. Nearly half of the artists surveyed found text-to-image technology useful in their process. Furthermore, AI is creating new avenues in the art market, such as AI-generated art sold as NFTs (Non-Fungible Tokens), attracting younger collectors and enthusiasts more readily than traditional buyers. High-profile sales, like the $432,500 auction of an AI-generated portrait at Christie’s in 2018, have brought mainstream attention, although the market remains somewhat inconsistent. AI is also being explored for its potential in art authentication and market analysis, interpreting vast datasets to identify trends and potentially assess value.

The Casualties and Concerns: Artists, Copyright, and Ethics

Despite the opportunities, the AI art boom casts a long shadow, primarily over working artists. Many fear significant negative impacts on their income, with estimates suggesting over half of artists feel AI will harm their ability to make a living. Illustrators report declining commissions as clients turn to cheaper, faster AI alternatives, while concept artists face layoffs or pressure to incorporate AI into their workflows. This displacement raises existential concerns within the creative community. A major point of contention is copyright. AI models are typically trained on enormous datasets, often including copyrighted images scraped from the internet without permission from the original creators. This practice has led to lawsuits and widespread anger among artists who feel their work is being used unfairly to train systems that could ultimately replace them or devalue their unique styles.

Current U.S. copyright law complicates matters further, as it only protects original works created by humans. Works generated solely by AI, even with detailed text prompts, generally cannot be copyrighted, though works incorporating AI elements alongside substantial human creativity might qualify on a case-by-case basis. This legal ambiguity leaves many artists feeling unprotected, with nearly 90% fearing that copyright laws are outdated for the AI era. Ethical concerns also abound. AI systems can perpetuate and amplify biases present in their training data, leading to skewed or stereotypical representations of race, gender, and other groups. The potential for AI to generate convincing deepfakes or misinformation is another significant worry. Moreover, critics argue that AI art, derived from existing data, lacks the genuine emotion, intent, originality, and lived experience that define human creativity. While some argue AI can’t replicate human creativity, the uncanny resemblance and speed of AI generation challenge traditional notions of artistry.

The Road Ahead: Integration, Regulation, and Redefinition

The future of AI in art appears poised for deeper integration rather than outright replacement of human artists. Many envision AI evolving into a powerful collaborative partner or creative assistant, enhancing ideation, speeding up production, and enabling artists to explore novel forms of expression. Future AI tools are expected to offer greater realism, integrate multiple media (like text, animation, and sound), and become more interactive, perhaps even suggesting modifications in real-time during the creative process. Personalized AI models, trained on an artist’s specific style or dataset, could offer more tailored creative possibilities.

However, navigating this future requires addressing the significant ethical and legal challenges. Calls for regulation are growing, demanding transparency about AI use, compensation for artists whose work is used in training data, and clearer copyright guidelines. Establishing ethical frameworks and potentially new legal structures to manage ownership, bias, and intellectual property in the age of AI is crucial. The ongoing dialogue involves artists, tech companies, policymakers, and the public, debating how to balance technological advancement with the protection of human creativity and livelihoods. While some predict AI will become ubiquitous in creative fields, potentially displacing certain roles, others believe human artists will remain central, leveraging AI as just another tool in their arsenal, albeit a uniquely powerful one. Ultimately, the AI art boom is forcing a reevaluation of creativity itself, challenging us to define what art means in an era where machines can generate aesthetically compelling images, and pushing us to consider the future landscape of human expression.

Feature Image Credit: Gerd Altmann from Pixabay

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Sourced from MarylandReporter.com

By Chad S. White

Social media is unravelling. Brands betting on platforms they own will be the ones left standing.

The Gist

  • Social shift ahead. The decline of big social media platforms is accelerating, and this is reshaping how brands should approach customer engagement.
  • Trust on trial. Consumers trust user-generated content far more than influencer promotions, which signals a shift in what drives brand credibility.
  • Own your channels. Brands must invest in direct channels like websites, apps and email to regain control over customer relationships.

A few years from now, we may look back on 2025 as the beginning of the end of two long-standing mega pillars of the internet.

The first is Google’s domination of the search engine marketplace, which is being disrupted by generative AI platforms like ChatGPT and Perplexity, with Google’s market share falling below 90% for the first time since 2015. Antitrust issues aside, there are plenty of reasons to believe it will never be that high ever again.

The second is the end of the era of big social media platforms.

Let’s look at the crumbling that’s already started, where things are likely headed and why the momentum isn’t likely to let up.

Table of Contents

The Canary in the Coal Mine

Before its acquisition by Elon Musk, Twitter was widely viewed as the world’s digital town square. Since its transformation into X, it’s become a shadow of its former self, more of a ghost town than the world’s town square.

Since Musk purchased the platform in 2022 for $44 billion, X’s valuation has plunged. According to Fidelity’s valuation of its investment in X, the platform’s worth has fallen by 79% to just $9.4 billion. Brand Finance is even less generous, valuing it at just $498 million earlier this year.

This change of fortune was driven by an 80% reduction in staff, which notably included all of its content moderation staff and partners. That change directly led to a marked decline in content quality and negative shift in tone. This caused millions of active users to leave the platform, and it raised brand safety concerns among advertisers, many of which reduced or ended their advertising. As a result, X is “barely breaking even” and has sued its former advertisers, claiming conspiracy.

That chain of events is important because of what happened next.

Meta Doubles Down on the Wrong Lessons

On Jan. 7, a couple of weeks before Donald Trump’s inauguration, Facebook founder and Meta CEO Mark Zuckerberg announced that the company would be “restoring free expression on our platforms” by getting rid of fact-checkers, removing restrictions on controversial topics like immigration and gender, dialling back other content filters, increasing recommendations of political content and “going to work with President Trump to push back on governments around the world going after American companies and pushing to censor more.”

Zuckerberg explicitly says they’re going to be doing things “similar to X” and rolling those changes out across Facebook, Instagram and Threads.

Based on what’s happened at X, there’s every reason to believe that these changes will cause many unintended consequences.

  • Many Meta users may spend less time on its platforms or depart for other platforms like Mastodon and Bluesky, which have benefited tremendously from X’s similar policy shifts.
  • Advertisers may pull back or depart out of concern for brand safety.
  • Foreign governments may levy additional fines or further restrict Meta’s activities in their nations, worsening its already poor relations.

One of Meta’s early attempts at rolling back content moderation resulted in Instagram users seeing violent and graphic content recommended in their Reels feeds, which led to a flood of user complaints.

Social Media as a Black Box

The double-whammy of lower user engagement and advertiser pullbacks is likely to be devastating, just as it’s been at X. Making matters worse is the fact that social networks have gradually restricted organic brand reach to near zero over the years.

What little organic traffic that exists is often obscured by these platforms, according to SparkToro. And cookie consent is further complicating attribution, suppressing conversion tracking by up to 20%, according to Orbit Media. All of that has further discouraged brands from investing much in an organic presence on social media platforms.

As a result, when brands pull back from social media advertising, they’re often left with a minimal direct presence. That said, some may have an indirect presence via influencers, but even that is on shaky ground.

Influencer Fatigue

Plenty of consumers feel a kinship with their favourite influencers. That’s particularly true of younger consumers in Gen Z.

However, in general, trust is slipping. A common consumer belief today is that most influencers only endorse and promote products because they’re paid to, not because they use or even like the product.

According to a survey by EnTribe, 81% of consumers said a brand’s use of influencers has either no impact or a negative impact on their perception of that brand. Fifty-one percent said they scroll right past influencer posts, in much the same way that consumers ignore ads. When asked if their purchases were ever impacted by an influencer, 62% said they’ve never purchased an influencer-promoted product, while 42% of those who had purchased an influencer-promoted product said they regretted doing so.

The most shocking evidence that the influencer market has peaked is that 86% said they’re more likely to trust a brand that publishes user-generated content, compared to just 12% who said they’re inclined to purchase a product promoted by an influencer.

Bots Are Taking Over — and Everyone Knows It

Authenticity and trust are being further undermined by AI bots, which in some cases are being directly created and enabled by social media platforms. For instance, Meta created Facebook and Instagram AI bots for living celebrities, dead famous people and others. Meta also allows Instagram users to create AI versions of themselves to interact with their followers (seemingly to save them from having to waste their time doing so).

These programs aren’t fringe. They’re core to social media’s future. Meta has even told The Financial Times that it envisages social media filled with AI-generated users.

To their credit, these AI bots are clearly labelled. But it conjures up a dystopian future where we all create AI versions of ourselves that chat with one another and periodically update us about the fake conversations our fake selves are having with all the other fake people. That’s a far cry from the original promise of social media. In fact, we probably won’t call it “social” media at that point.

Of course, all of that is on top of the enduring problem of run-of-the-mill fake accounts. Facebook alone removes around 1 billion fake accounts each quarter.

Take Back What You Can Control

If you throw in the uncertainty swirling around TikTok, social media has never looked more shaky. Still huge, but shaky.

The natural response from brands should be to counterbalance that uncertainty by investing more in channels they have much more control over, including websites, apps, customer loyalty programs, email, SMS (RCS), mobile and browser push, and podcasts.

In addition to building up first-party audiences, which give you much more direct and unmediated relationships with your customers and prospects, investing in these channels also gives you many opportunities to collect first-party data. This data is vital for driving message targeting, ad targeting and analytics that get us closer to our customers.

The internet is undergoing massive changes. And if Twitter’s transformation into X demonstrates anything, it’s that big changes can happen faster than you think. Every brand should be watching carefully and coming up with contingency plans before they realize they’re a few years too late.

Core Questions About the Decline of Big Social Media

Editor’s note: Key questions surrounding the decline of major social media platforms and how brands should adapt their customer engagement strategies.

How is the collapse of big social media changing customer engagement?

As trust in major social media platforms declines, brands are shifting their focus toward direct engagement strategies such as email marketing, owned communities and first-party data collection. Consumers are looking for more meaningful interactions, prompting businesses to invest in personalized customer experiences outside of traditional social media channels.

What role does user-generated content (UGC) play in brand credibility?

With consumers increasingly sceptical of paid influencer promotions, authentic user-generated content has become a powerful trust-building tool. Brands that encourage customers to share real experiences—through testimonials, reviews, and organic social posts—see stronger engagement and credibility compared to those relying on traditional advertising.

Why should brands invest in owned channels over social media?

Brands that rely heavily on platforms like X and Meta face risks due to algorithm changes, declining organic reach and shifting audience behaviours. Investing in owned channels such as company websites, email newsletters and brand communities provides greater control over customer relationships and reduces dependence on unpredictable third-party platforms.

How can brands mitigate the risks of AI-generated content and fake engagement?

AI-generated interactions and fake engagement on social media are eroding trust. To counter this, brands are prioritizing authenticity by fostering real customer conversations, leveraging human-led content creation, and verifying the credibility of online interactions. Transparency about AI usage in customer engagement is also key to maintaining consumer trust.

What are the long-term implications of social media’s decline for digital marketing?

The decline of traditional social media is pushing marketers toward more diversified digital strategies. SEO-driven content, community-based marketing and personalized experiences are becoming more effective than broad social media outreach. Businesses that focus on building loyal audiences through multiple touchpoints will be better positioned for long-term success.

By Chad S. White

Chad S. White is the author of four editions of Email Marketing Rules and Head of Research for Oracle Digital Experience Agency, a global full-service digital marketing agency inside of Oracle.

Sourced from CMSWIRE

facebook user, generated content, social media, marketing, digital marketing,artificial intelligence

By Gary Drenik

It’s no secret that artificial intelligence (AI) has been leading the charge on the evolution of technology across the customer service space.

But as we continue to explore how AI can enhance customer experience (CX), it’s essential to examine how different generations, particularly Gen-Z, view these changes. The digital natives, who have grown up in an interconnected world, are not only comfortable with technology but they expect it to be an integral part of their daily lives – and especially in their customer service interactions.

In today’s digital landscape, brands must strike the right balance between automation and the human touch, understand Gen-Z’s expectations around AI-driven CX adopt strategies that allow them to keep pace with the rising consumer demand in an age of digital interaction.

Consumer Sentiment Towards AI-Driven CX

The sentiment toward AI in customer service is divided, and there’s a generational divide emerging as a key factor. A recent Prosper Insights & Analytics survey revealed that Gen-Z expresses mixed feelings about AI, particularly in customer-facing applications.

While younger generations are generally open to AI, they still have concerns – and one significant issue is trust. According to the Prosper Insights & Analytics data, 21.2% of Gen-Z respondents said they didn’t trust AI to have their best interests in mind. Additionally, 32.1% were worried that AI might provide incorrect information, proving a need for transparency and reliability in AI-powered systems.

However, it’s not all negative. Gen-Z seeks the convenience AI offers in certain situations; for example, in online shopping or entertainment services, nearly 30% of Gen-Z consumers prefer AI chat programs, according to the Prosper Insights & Analytics survey. This indicates that while Gen-Z is cautious, they also see the value in AI, especially when it can enhance their experience by offering faster and more efficient solutions.

Gen-Z’s Preferences and Expectations of AI in Customer Service

Gen-Z expects personalization, speed, and convenience, but they also want to ensure that AI solutions don’t compromise the human experience. When it comes to customer service, Gen-Z is typically more likely to favour AI in certain scenarios where speed and convenience are prioritized, like booking a flight or resolving a quick problem with an order.

However, in more complex or sensitive matters like healthcare or banking, the majority of Gen-Z, like other generations, still prefer speaking directly with a human. A recent Prosper Insights & Analytics survey shows that 81.4% of Gen-Z respondents prefer a live person for banking assistance, and 82.5% prefer human interaction when it comes to healthcare-related matters.

The desire for a seamless blend of AI and human support is crucial for businesses to understand. What this means: Gen-Z isn’t opposed to AI; they just want it to complement rather than replace the human touch.

Striking the Balance Between AI-Driven Solutions and the Human Touch

As businesses look to integrate AI into their customer service offerings, they must carefully strike a balance between automation and human interaction. According to Niki Hall, Chief Marketing Officer at Intelligent CX Platform Provider Five9, “AI is an incredibly valuable tool for businesses, but it should never replace the nuance that only a human agent can provide. A seamless integration of AI and human service is key to providing an exceptional customer experience. AI can handle the repetitive tasks, but when a customer faces an issue that requires understanding, there’s just no substitute for a live agent.”

While AI is excellent for handling routine inquiries, triaging requests, and delivering speedy solutions, there are moments when customers need a personalized and human touch to feel heard and understood. Recent research from Five9 emphasized that 75% of consumers crave talking to a human, underscoring that the use of AI as a first line of defence, followed by escalation to human agents as necessary, has emerged as a successful strategy for many organizations.

By freeing up human agents from mundane tasks, businesses can ensure that their employees are focused on delivering high-quality, personalized service to customers who truly need it.

Strategies for Managing Increased Demand During Consumer-Driven Moments

A major challenge in customer service is managing the surge in demand during peak moments, from product launches to special promotions or even crises. This is where AI shines. By deploying AI-driven chatbots and virtual assistants, companies can manage large volumes of customer inquiries at scale, offering instant answers to common questions.

“AI allows us to scale our customer service without sacrificing on the quality of those interactions,” says Hall. “During high-demand periods, we can rely on AI to handle basic questions, while ensuring that our live agents are available to resolve more complex or priority issues.”

Furthermore, businesses can leverage AI’s data-driven insights to anticipate peak demand times and prepare for them accordingly. By understanding consumer behaviour patterns, AI can help predict when demand will surge, allowing businesses to optimize their workforce and infrastructure in advance.

Adapting CX Strategies to Meet Evolving Consumer Expectations

To remain competitive, companies must continuously refine their customer experience strategies to meet shifting consumer expectations. As technology and customer behaviour evolve, the brand’s approach to customer service should as well.

We know Gen-Z’s expectations are high; they want fast and efficient service, but they also demand personalization and transparency. According to the Prosper Insights & Analytics data, 31.3% of Gen-Z consumers believe that AI needs human oversight, and 26% believe that AI should provide more transparency on the data it uses. Brands that can integrate ethical AI practices and provide clear information about data usage will earn the trust of this influential demographic.

As Hall emphasizes, “The key to adapting CX strategies is understanding what Gen-Z values, and that’s authenticity and personalization. They expect brands to use AI in ways that are transparent, responsible, and enhance their overall experience.”

Finding the Right Balance

In today’s digital-driven world, AI is reshaping customer service and adapting to meet the needs of Gen-Z and are shedding light on the future of CX. However, businesses must remember that while AI can improve efficiency and handle routine tasks, human agents still remain essential for addressing complex or sensitive issues. By finding the right balance between AI and human interactions, brands can deliver exceptional customer service experiences that meet the evolving needs of Gen-Z and beyond.

Check out my website.

Feature Image Credit: AdobeStock_159764616

By Gary Drenik

Gary Drenik is a writer covering AI, analytics and innovation.

Sourced from Forbes

By Alex Kantrowitz

OpenAI’s chatbot is surging after a period of sluggish growth. After DeepSeek, that’s never been more crucial.

chatgpt and competitors graph

The Gist

  • ChatGPT’s surgeAfter months of stagnation, ChatGPT hit 3.8 billion visits in January 2025, more than doubling its closest competitor.
  • GPT-4o and voice modeOpenAI’s major update, including an advanced voice interface, fueled renewed interest in ChatGPT.
  • Competitive landscapeDespite DeepSeek’s rapid rise, ChatGPT maintains a massive lead over Bing, Gemini, Claude, and Perplexity.

ChatGPT is booming. After months of stagnant usage in early 2024, the chatbot hit an inflection point and is now far outpacing its competition, according to new data from analytics firm Similarweb (see above).

OpenAI’s flagship bot hit 3.8 billion visits on desktop and mobile web in January 2025, more than doubling Bing, its nearest competitor, and leaving Google’s Gemini, Anthropic’s Claude and Perplexity far behind. The traffic surge is a remarkable reversal for ChatGPT following a usage stagnation that lasted longer than a year. After reaching 1.9 billion visits in March 2023, ChatGPT didn’t surpass that number until May 2024.

“The first rush was about novelty, people trying it out. They do seem to have transitioned to where more people have found practical uses for the app,” David Carr, editor for insights news and research at SimilarWeb, told me.

Table of Contents

Why ChatGPT’s Growth Matters

The ChatGPT boom could not have arrived at a better time for OpenAI, which recently saw its AI models effectively equalled by the open source DeepSeek. The incident caused OpenAI CEO Sam Altman to admit the company was on the wrong side of history regarding open source and would maintain a smaller lead than it had previously. OpenAI’s application business is now far more important to its long-term success, and it’s delivering.

The inflection point for ChatGPT seems to have occurred just as OpenAI announced its GPT-4o update, which included an advanced voice mode. The new voice interface would be far more responsive and human sounding than anything on the market, and even a bit flirty.

Following OpenAI’s 4o presentation, Altman infamously tweeted “her,” a reference to a movie starring Scarlett Johansson where a human falls in love with an AI voice that she portrays. Johansson, who’d been approached by OpenAI but refused to collaborate, expressed outrage and threatened legal action following the announcement. It’s possible the publicity helped OpenAI more than it hurt.

Beyond voice mode, OpenAI has improved ChatGPT in several areas. It’s incorporated image generation with Dall-E directly in the bot, it’s released better models — including the o1 reasoning model that DeepSeek challenged — and it’s appeared to hallucinate less. The bot’s also been helped by continued public interest and a willingness among people to try different uses and not abandon it after disappointing results.

Don’t Rest, OpenAI. DeepSeek’s Coming

OpenAI shouldn’t get too comfortable though. DeepSeek’s recent surge surge challenged not only its models, but ChatGPT as well. On Tuesday, Jan. 28, at the height of the DeepSeek publicity wave, ChatGPT registered 139 million visits to DeepSeek’s 49 million, according to Similarweb. Almost overnight, DeepSeek built one third of the audience that ChatGPT took years to establish.

But OpenAI does have the leading AI brand in ChatGPT, something that should be useful as more people seek to engage with artificial intelligence. This past weekend, the company sought to burnish its brand by running its first Super Bowl ad. Google ran a lengthy Super Bowl ad for Gemini as well. If OpenAI can make ChatGPT into the “Coke” of AI, it stands to maintain a lead even if chatbots commoditize.

Can OpenAI Maintain Its Lead?

As for the rest of the pack, it’s not looking pretty. Compared to ChatGPT’s 3.8 billion visit in January, Bing received 1.8 billion, Gemini received only 267 million, Perplexity received 99.5 million and Anthropic’s Claude received 76.8 million. These are web-only numbers, but they’re directionally reliable. And they show OpenAI opening up a massive lead, with competition that isn’t really close.

Core Questions Around ChatGPT’s Growth

Editor’s note: Here are core questions around ChatGPT’s growth:

What drove ChatGPT’s recent surge in usage?

OpenAI’s release of GPT-4o, featuring improved reasoning, enhanced voice mode and better image generation, helped drive renewed interest in ChatGPT. Publicity from the Scarlett Johansson controversy may have also played a role.

How does ChatGPT compare to competitors?

ChatGPT recorded 3.8 billion visits in January 2025, more than double Bing’s traffic and far ahead of Google’s Gemini, Anthropic’s Claude, and Perplexity.

Could OpenAI lose its lead?

While ChatGPT remains dominant, DeepSeek’s rapid growth shows that challengers can quickly capture market share, highlighting the risk of commoditization in the chatbot space.

Feature Image Credit: Jason Dent

By Alex Kantrowitz

Alex Kantrowitz is a writer, author, journalist and on-air contributor for MSNBC. He has written for a number of publications, including The New Yorker, The New York Times, CMSWire and Wired, among others, where he covers the likes of Amazon, Apple, Facebook, Google, and Microsoft. Kantrowitz is the author of “Always Day One: How the Tech Titans Plan to Stay on Top Forever,” and founder of Big Technology. Kantrowitz began his career as a staff writer for BuzzFeed News and later worked as a senior technology reporter for BuzzFeed. Kantrowitz is a graduate of Cornell University, where he earned a Bachelor of Science degree in Industrial and Labor Relations. He currently resides in San Francisco, California. Connect with Alex Kantrowitz:

Sourced from CMSWIRE

By Catherine Brinkman

AI-powered ads target you with eerie precision. Is hyper-personalization smart marketing or a branding risk? Here’s what you need to know.

Hyper-personalized ads are changing the game in digital marketing, taking it from generic to genuinely impactful. These advanced campaigns don’t just scratch the surface — they dig deep, using artificial intelligence (AI) and machine learning (ML) to analyse massive amounts of data and behaviour patterns.

The result? Ads that feel less like marketing and more like a conversation tailored just for you. By delivering content that truly resonates, hyper-personalized ads are setting a new standard for how brands connect with their audiences and build meaningful relationships.

Customers Demand Personalized Experiences

Hyper-personalized ads are dominating digital marketing for one simple reason: consumers demand it.

In 2025, people expect brands to deliver personalized experiences, and many leave negative comments when those expectations aren’t met. This isn’t just a trend — it’s a wake-up call for marketers. We need to stay relevant and actually connect with our audiences. And brands are doubling down on hyper-personalization, turning it into the industry’s go-to strategy for engagement that actually works.

Ads that are hyper-personalized thrive on the smart use of consumer data and behaviour patterns. Unlike old-school advertising that banks on broad demographics, hyper-personalization dives deep into the details. It pulls from everything — behavioural data like clicks and browsing habits, purchase history and even real-time factors like location and time of day.

By blending these data points, marketers craft detailed profiles that power razor-sharp, hyper-relevant ads designed to truly connect.

How Hyper-Personalized Ads Shape Consumer Behaviour

Hyper-personalized ads use psychological principles to shape consumer behaviour, with the mere exposure effect leading the charge. This phenomenon suggests that the more often we see something, the more we tend to like it. By presenting tailored content aligned with a consumer’s interests and online habits, these ads build familiarity that naturally boosts positive feelings toward the brand or product, creating a connection that feels effortless.

Confirmation bias plays a major role in the success of hyper-personalized ads. By delivering content that aligns with a consumer’s existing beliefs and preferences, these ads feel more credible and persuasive. This approach makes decision-making easier and boosts satisfaction, as people are naturally drawn to products that reinforce what they already believe.

Personalization isn’t just a tactic — it’s a psychological powerhouse for driving consumer engagement and sales. When ads create experiences that make people feel valued and understood, they build stronger connections between brands and their audiences.

This isn’t just about loyalty; it’s about results. Personalized marketing can boost revenue by up to 15%, proving that making consumers feel seen and appreciated isn’t just good for relationships — it’s great for business.

Not everyone loves personalized ads. While some appreciate the relevance, others feel uneasy or even invaded. There’s a fine line marketers must walk to make sure hyper-personalization delivers value without crossing boundaries.

Ethical AI Drives the Future of Hyper-Personalization

As hyper-personalized ads keep evolving, they raise some big ethical questions — especially around privacy and the risk of manipulating consumers.

The massive data collection behind these ads puts privacy in the spotlight, forcing brands to strike a balance between personalization and respecting people’s rights. To keep consumer trust (and stay on the right side of tough privacy laws), brands need to be crystal clear about how they collect data and make sure they’re getting real, informed consent.

Hyper-personalized ads bring plenty of advantages, like stronger customer engagement, higher conversion rates and a big boost in satisfaction by delivering content that feels tailor-made. Their impact is undeniable. But there’s a catch — pulling it off takes serious investment in tech and resources, which can put smaller businesses at a real disadvantage.

The ethics of hyper-personalized ads go beyond privacy — they dip into the tricky territory of consumer manipulation.

Using AI and data analytics to nudge behaviour can quickly blur the line between being helpful and outright exploitative. It’s a fine balance: delivering relevant content without taking advantage of people’s vulnerabilities. Marketers need to tread carefully because once trust and autonomy are gone, they’re almost impossible to get back. Brand loyalty and market share could be lost.

With Great Power Comes Great Responsibility

Hyper-personalized ads are reshaping the marketing landscape, offering unmatched opportunities to connect with consumers on a deeper level. But with great power comes great responsibility.

Striking the right balance between relevance and respect is critical for building trust and delivering real value. By leveraging AI ethically and transparently, brands can harness the full potential of hyper-personalization while maintaining the trust and loyalty that drive long-term success.

By Catherine Brinkman

Catherine Brinkman is a dynamic professional with a rich background in corporate training, AI integration and business development across high-tech, finance and manufacturing sectors. A Silicon Valley native, she has over two decades of fundraising experience, 17 years as a corporate trainer with Dale Carnegie Training and 21 years of media training for political candidates.

Sourced from CMSWIRE

By Stan Schroeder

There’s a new AI player in town, and you might want to pay attention to this one.

On Monday, Chinese artificial intelligence company DeepSeek launched a new, open-source large language model called DeepSeek R1.

According to DeepSeek, R1 wins over other popular LLMs (large language models) such as OpenAI in several important benchmarks, and it’s especially good with mathematical, coding, and reasoning tasks.

DeepSeek R1 is actually a refinement of DeepSeek R1 Zero, which is an LLM that was trained without a conventionally used method called supervised fine-tuning. This made it very capable in certain tasks, but as DeepSeek itself puts it, Zero had “poor readability and language mixing.” Enter R1, which fixes these issues by incorporating “multi-stage training and cold-start data” before it was trained with reinforcement learning.

Arcane technical language aside (the details are online if you’re interested), there are several key things you should know about DeepSeek R1. First, it’s open source, meaning it’s up for scrutiny from experts, which should alleviate concerns about privacy and security. Second, it’s free to use as a web app, while API access is very cheap ($0.14 for one million input tokens, compared to OpenAI’s $7.5 for its most powerful reasoning model, o1).

Most importantly, this thing is very, very capable. To test it out, I immediately threw it into deep waters, asking it to code a fairly complex web app which needed to parse publicly available data, and create a dynamic website with travel and weather information for tourists. Amazingly, DeepSeek produced completely acceptable HTML code right away, and was able to further refine the site based on my input while improving and optimizing the code on its own along the way.

DeepSeek AI
I’ll do all of that…tomorrow. Credit: Stan Schroeder / Mashable / DeepSeek

I also asked it to improve my chess skills in five minutes, to which it replied with a number of neatly organized and very useful tips (my chess skills did not improve, but only because I was too lazy to actually go through with DeepSeek’s suggestions).

I then asked DeepSeek to prove how smart it is in exactly three sentences. Bad move by me, as I, the human, am not nearly smart enough to verify or even fully understand any of the three sentences. Notice, in the screenshot below, that you can see DeepSeek’s “thought process” as it figures out the answer, which is perhaps even more fascinating than the answer itself.

DeepSeek AI
We get it, you’re smart. Credit: Stan Schroeder / Mashable / DeepSeek

It’s impressive to use. But as ZDnet noted, in the background of all this are training costs which are orders of magnitude lower than for some competing models, as well as chips which aren’t as powerful as the chips that are on disposal for U.S. AI companies. DeepSeek thus shows that extremely clever AI with reasoning ability doesn’t have to be extremely expensive to train — or to use.

Feature Image Credit: DeepSeek

By Stan Schroeder

Stan is a Senior Editor at Mashable, where he has worked since 2007. He’s got more battery-powered gadgets and band t-shirts than you. He writes about the next groundbreaking thing. Typically, this is a phone, a coin, or a car. His ultimate goal is to know something about everything.

Sourced from Mashable

Sourced from Futurism

Artificial Intelligence, Ai, Facebook, Facebook Ai

“Translation: ‘Our real users are quitting the platform, so we will fill our community with fake users instead.'”

Folks on social media are in an uproar after Meta announced that it’s planning to load Facebook up with AI “users,” better known as bots.

First reported by the Financial Times, this plan to populate the dying social network with these so-called “characters” is geared towards driving engagement — even though other platforms, including Meta’s Instagram, have been roiled by unauthorized bots for years.

“We expect these AIs to actually, over time, exist on our platforms, kind of in the same way that accounts do,” Connor Hayes, Meta’s vice-president of product for generative AI, told the FT. “They’ll have bios and profile pictures and be able to generate and share content powered by AI on the platform… that’s where we see all of this going.”

While it’s unclear when this plan will move forward, Hayes said that there are already “hundreds of thousands” of characters that have been created on the site — though most, for now, remain private.

Unsurprisingly, users on the r/futurology subreddit saw right through the ruse.

“Translation: ‘Our real users are quitting the platform, so we will fill our community with fake users instead,'” one user wrote.

As another aptly put it, “the advertisers buying space on [Facebook] won’t be able to tell the difference either, so it’s all just more clicks and more ad revenue.”

The potential implications for advertising on the platform overall seemed to strike a chord with the Redditors.

“With advertising being their bread and butter and pretty much the reason they still exist, how is this legal and not misrepresenting numbers to clients?” another user mused. “If they tell advertisers that they get X number of impressions, engagement, etc. but those aren’t real people anymore, that seems like straight up lying. Wild that they’re just coming right out with it and doubling down.”

For others, the prospect of fake users is yet another reason they’re ditching Facebook.

“I rarely check my FB feed at all anymore, and when I do it’s almost entirely made up of pages I don’t follow and have never interacted with,” another user wrote. “There’s no way to actually get rid of them, just briefly mute them. So now we can look forward to our actual contacts being even harder to see among a bunch of fictitious users too.”

Unfortunately, those left on the platform — the elderly and assorted right-wingers who are regularly duped by obvious AI slop — may not be able to tell the difference.

“I think the old people that use it the most are the least likely to notice,” one user concluded.

Feature Image Credit: Image by Chris Unger/Zuffa LLC via Getty Images

Sourced from Futurism

By Rocio Fabbro

From scouring subreddits to personalized messages from John Stamos, AI is helping target audiences in new ways

https://qz.com/known-agency-big-lebotski-chicken-subreddit-ai-stamos-1851695089

Artificial intelligence is helping marketers keep up with the rapid pace of change in the advertising industry, allowing them to stay nimble while also expanding their creative capabilities, says Kern Schireson, CEO of the full-service advertising agency Known. That’s making it easier for marketers to know exactly what you want — and how you want to see it.

“It’s a real asset to us as we look to work through a bunch of complex decisions on where and how to introduce messaging, where it’ll be most persuasive to our clients’ audiences. AI gets us there faster,” Schireson said in the latest episode of Quartz AI Factor, a video interview series set at the Nasdaq MarketSite (NDAQ).

But it’s not just an efficiency tool. Known also deploys AI to help tune advertisements to individual viewers, a gargantuan task that used to take far longer and use up considerable resources.

“If you want to do that manually, that’s an insurmountable level of content that you need to create,” Schireson said. “But if you have AI tuning and optimizing the creative iteration for the individual audience at the particular time of day, place context platform in which they’re receiving it, you can do that quickly and efficiently that creates opportunities that never existed before.”

Known ran a Super Bowl ad featuring John Stamos, Schireson said. Using AI, Stamos said the name of whichever city viewers were watching from, giving each individual viewer a different and more targeted experience.

Image for article titled AI is taking ad targeting to a new level. Here's how
Photo: Alexander Spatari (Getty Images)

 

In another example, the company’s AI chatbot, known as “The Big Letbotski,” dug through 80,000 active subreddits to identify the most relevant conversations about chicken sandwiches for its client, Shake Shack (SHAK). After finding 30 of the most content-specific subreddits, it ran targeted ads promoting its Chicken Shack Sundays giveaway in April. That helped Shake Shack beat sales estimates by 31%.

“The Big Lebotski helped look at the dimension of audience and the context of the conversation in that particular subreddit to say, ‘where is this gonna land, where it actually feels like it makes sense for people who are likely to be persuaded by it,’” Schireson said. “And so the intersection of those two questions was really where it helped us zoom in, and the performance speaks for itself.”

 

By Rocio Fabbro

Sourced from QUARTZ