The GenAI Strategies of the AI Future 50

THE BIG IDEA

Introducing the AI Future 50 — The Companies With the Highest Potential for GenAI Transformation

Over the last 50 years, as tech has sped up, we've watched companies drop out of the Fortune 500 faster than you can say Noah Lyles, with new players swooping in left and right. This tends to kick into high gear when new tech waves hit. And with GenAI, we're riding the crest of a monster wave.

While early 2023 treated us to speculation about GenAI's rapid corporate impact, the truth is that most organizations are only now developing coherent AI strategies and moving beyond initial pilot phases.

What’s been holding these companies back?

Over the past 20 months, since ChatGPT launched generative AI over the tipping point and into the cultural and corporate zeitgeist, we’ve held discussions with corporate leaders about their generative AI strategy. One of the biggest barriers to AI transformation has been talent: 60% of tech decision makers say that AI talent is their biggest skills shortage.

For those that can bridge the AI talent gap, that means a big opportunity to reimagine their businesses, and we expect to see a lot of mid-sized companies leapfrog into the Fortune 500 over the next 5-10 years, displacing current incumbents. These companies are more likely to swiftly adapt and integrate AI-driven innovations, optimize their operations, and create new value propositions. This adaptability, coupled with their ability to harness first-party data as a competitive moat, positions them to capitalize on AI's transformative potential—outpacing slower, more entrenched competitors while maintaining a competitive advantage against upstarts.

But who will they be?

To identify potential frontrunners in this transformation, we developed a model to evaluate the 50 companies under $5 billion in revenue with the highest potential for GenAI transformation.

We’re calling it the AI Future 50. Think of it like Forbes 30 under 30, but for GenAI Transformation.

Is your company on the list? Are your competitors? Be amongst the first to download the report and find out.

Read the AI Future 50

CHART OF THE WEEK

The Two Sided Impact of AI on Worker Productivity

A recent study by The Upwork Research Institute reveals this stark disconnect between employee experiences and employer expectations when it comes to AI adoption: Leaders remain starry-eyed about generative AI, with 96% anticipating productivity boosts. But those promised gains? They're still MIA. In fact, 47% of full-time employees using AI are uncertain how to meet expectations, and 77% report decreased productivity and increased workload due to these tools.

This productivity paradox stems from a perfect storm: the steep learning curve of new tech, a lack of investment in training and up-skilling, and inflated executive expectations.

But there's hope, and it comes in the form of non-traditional talent. Freelancers are leading the AI-ready pack: 56% of freelancers don't struggle to keep pace with client organization productivity demands, compared to only 35% of full-time employees. And the benefits speak for themselves: leaders tapping into freelance talent report doubling down on organizational agility (45%), work quality (40%), innovation (39%), scalability (39%), revenue (36%), and efficiency (34%). Some (35%) even claim their full-time workers' well-being and engagement have doubled as a result.

Is this a self-serving report by Upwork? Sure, but their research is consistently rock solid, and research—including our own—has consistently found that freelancers are successful early AI adopters. The C-Suite is taking note: 48% of C-suite execs report hiring freelancers to execute delayed AI projects over the past year — with 80% stating that freelance talent is essential to their business, and 38% of the holdouts planning to jump on the bandwagon next year.

While the report suggests hiring freelancers as a potential solution to employee dissatisfaction with AI, this approach alone doesn't address the root cause: a lack of comprehensive AI training programs and methodologies within organizations. Sure, it's possible to have the best of both worlds—productivity through the roof, efficiency off the charts, and employees grinning from ear to ear—but this outcome first requires a fundamental shift in how we approach, structure, and measure work itself.

WATERCOOLER

AI Surpasses Humans at ... Damn Near Everything

According to Moore’s Law, technology should x2 every two or so years — but when it comes to AI, over the past 10 years we’ve advanced by a factor of about a million.

“If air travel had improved at the same rate as LLMs, average flight speed would have improved from 600mph in 2018 to 900,000mph in 2020—a 1,500x increase in two years (!). Instead of taking eight hours to travel from London to New York, it would take just 19 seconds.”

This chart from Digital Native shows how AI has improved in things like understanding handwriting, recognizing speech, and comprehending language over the last 20 years — it’s getting really good at tasks that used to be human-dominated, and it's happening faster than we ever expected.

The question now is whether the pace holds or AI hits a wall due to computation limits, regulation (hello, copyright lawsuits), and energy constraints.

DISCOVERY ZONE

ShortLife is an alarm-clock-like device by Belgium artist, Dries Depoorter, that reminds us that life is short by showing how much time you have left based on your life expectancy.

MEME