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By Megan Sauer

There is one skill all young people need to thrive in the workplace — today and in the future — and it’s been around for thousands of years.

“If I could give my 13- and 16-year-old one competence that I think would stand the test of time, it’d be storytelling,” millionaire entrepreneur Scott Galloway told CNBC Make It, following a live recording of Vox’s “Pivot” podcast at SXSW last month.

The type of storytelling may not matter, because the platforms people use to communicate can rapidly change. The important part is developing an “ability to write well, an ability to articulate ideas and an ability to present ideas with data, infographics, slideshows,” said Galloway.

Galloway is a marketing professor at the New York University Stern School of Business who, in 2005, started L2 Inc. — a research project that grew into a business intelligence consultancy and helps brands learn how to market to audiences online. IT business consultancy Gartner reportedly bought L2 Inc. for more than $130 million in 2017, according to regulatory filings.

Today, for his brand strategy and digital marketing courses, he describes how a brand’s storytelling can directly contribute to, or hurt, its success. The importance of storytelling is particularly why young people shouldn’t rely solely on generative artificial intelligence tools like ChatGPT — not now, not ever, said Galloway.

“We don’t know if in five years some neural network is going to replace ChatGPT. We don’t know if coding is going to be outdated,” he said.

Management experts agree — understanding AI is important, but it isn’t the sole skill needed to succeed at work. Employers want to hire candidates with a combination of soft and hard skills, like analytical thinking, creative thinking, leadership skills and curiosity, a report from management consulting firm Oliver Wyman noted earlier this year.

Another piece of advice, Galloway says: Finding a way to be an expert in your field is a good way to become successful, no matter what else happens around you.

“The specific crowds out the general,” Galloway says. “Find a niche, no matter how narrow it is, and try and own it. Commit to being one of the most knowledgeable people in the world on a domain … You’re never going to be an expert in anything if you don’t enjoy it.”

Feature Image Credit: Rick Kern | Getty Images Entertainment | Getty Images

By Megan Sauer

Sourced from CNBC

By Forrester

Generative AI (gen AI) was born on November 30, 2022, with the release of ChatGPT, and it’s been moving 100 miles an hour ever since, drawing in 100 million people and counting. As new and surprisingly powerful as gen AI is, we can already see how companies will incorporate gen AI capabilities into their businesses’ strategies and operations. Our experience with two earlier, explosive technologies show you how.

  1. The BYO explosion of the late 2000s taught us how to incorporate employee-led disruption. We learned that when employees brought personal technology to solve customer and business problems. We empowered, guided, and protected employees and the firm while taking advantage of the new value that personal technologies in business brought.
  2. The mobile, social, original internet explosions taught us how to respond to and take advantage of customer-led disruption. We built mobile apps to help customers in their mobile moments of need; we adopted social media communications to improve engagement and collaboration; and we tooled up to take full advantage of the business models shaped by the internet.

Technology executives should prepare for generative AI to follow both paths and sprint into your business through four doors:

  • Bottom-up. Some of the 100 million people already using generative AI work for you. As you learned in the BYOD era, employees will adopt any tool that makes them more successful. The hyperadoption of gen AI leads to rampant BYOAI adoption. You can’t stop them, not fully. Your job is to put up guardrails that protect the firm’s IP and teach the skills of responsible AI. You need guardrails because your company IP is at risk. Just like with the original onslaught of BYO, you need to tune in now and empower, guide, and protect employees and the firm. Sharpen your listening tools and network sniffers. Revisit and promote your responsible AI policies ASAP. Your response to BYOAI will shape your top-down approach to gen AI, because employees will have elevated their robotics quotient and will be ready to go.
  • Top-down. Gen AI will unlock the value of 10-plus years of investments in data, insights, and artificial intelligence, including machine-learning models. This is where your investments in trusted AI will pay off, because you’re ready to use them. Already, the hyperscalers and software-as-a-service platform providers have announced and will trickle release gen AI-infused applications. Already, service providers and you are using TuringBots to generate and test code. Already, you’re incorporating marketing content generated from text prompts to hyperpersonalize engagement. And soon, you’ll overhaul your usability with text-based interfaces to business and analytics applications. Every part of your business will have ideas on how to use generative AI, mostly to optimize, automate, or augment something. Some will be great. Pick the ones that are easiest, safest, and most practical to deploy first.
  • Outside-in. Customers’ expectations for what gen AI can do for them are rising faster than anybody can keep up with. Every day, there is a new application using gen AI to do something useful. The latest I saw was a “free” cover-letter generator using GPT-4. (“Free” means that they’re accumulating your job preferences to resell as insights.) Microsoft triggered the search wars with OpenAI in Bing, and Google is now full-on engaged with Bard. Already, in the US, 35% of Gen Zers and 25% of Millennials have used bots to help buy hard-to-find inventory. That bot habit will be supercharged with gen AI, raising expectations even higher. Your job starts by anticipating where customers’ adoption will directly affect your company. If a customer has a better idea of your product landscape than your salespeople, that’s not good. If they are getting gen AI-powered customer care from a competitor and not you, not good. If your competitors’ stuff is in a next-generation recommendation engine and yours isn’t, that’s not good. Just like with mobile, your response will be to ramp up your customer-facing gen AI capabilities inside-out.
  • Inside-out. As you move through the gen AI opportunity thicket, you will quickly identify ways to help customers and deliver more value with your own gen AI-infused applications. Customer care or empowering frontline employees will be an early payoff, we expect. But you’ll find opportunities to streamline customer onboarding, hyper personalize engagement, provide better customer self-service, and stimulate a new round of value creation like what was triggered by mobile apps. Sort the scenarios based on the readiness of your data, the impact you will have, and your confidence that you can anticipate and manage the costs that go along with gen AI licensing and computing. The technical architectures are still in flux, but we believe that it will incorporate layers of intelligence — some of yours, some from others, and some public — protected by control gates for inputs and outputs and piped together into gen AI-infused applications. This “layers, gates, and pipes” approach will help you scale, take advantage of all the capabilities, and give you intense visibility into how it’s going and where the costs lie.

By Ted Schadler

This post was written by VP, Principal Analyst Ted Schadler and it originally appeared here. Follow me on Twitter or LinkedIn. Check out my website

Sourced from Forbes

By Ben Sherry

Artificial intelligence technology may help solve retention problems in the customer service industry.

Solving the customer service industry’s notorious retention issues has been something of a white whale for entrepreneurs. According to data from AI company Cresta, annual turnover rates at contact centres jumped from 30-45 percent to around 80 percent during the pandemic. High turnover rates can lead to longer customer wait times, as it can take between seven to nine weeks to hire a new agent, and many more months to fully train them. Several potential fixes have been introduced, such as A.I.-powered chatbots and virtual customer service representatives, but a true “silver bullet” solution has yet to be found.

One of the reasons call centre employees burn out so quickly is that they’re frequently forced to deal with abusive callers. This abuse often comes in the form of bigoted tirades from American clients. Maxim Serebryakov, the 24 year-old CEO of Palo Alto-based accent augmentation company Sanas, saw this problem up close when his friend Raul Garcia Letona was forced to leave Stanford and support his family in Nicaragua by getting a job at a call centre. Serebryakov began toying with the idea of using artificial intelligence to change a call centre agent’s accent in real time, and in 2020 co-founded Sanas. By processing a multitude of voices and corresponding transcripts through an algorithm, Sanas allows call centre agents to choose how their accent will sound to clients.

Many call centre agents grow up in the U.S. and speak perfect English but are regularly subjected to verbal abuse from bigoted Americans because of their accents, Serebryakov says. Despite Garcia Letona’s high level of education, he was underperforming due to his thick South American accent.

Feature Image Credit: Getty Images

By Ben Sherry

Sourced from Inc.