In which we attempt to determine where AI is headed in 2024

For those chasing the generative AI hype train, it’s been a year of frantic experiments.

Scared of being left behind by what could be a transformative tech wave, companies have been jumping on the large language model (LLM) bandwagon, prodding the tech industry out of a post-pandemic slump.

In recent months, however, some experts have pointed to signs that generative AI could be headed for what research firm Gartner famously calls the “trough of disillusionment”—the period in every hype cycle when a tech fails to live up to outsized initial expectations quickly enough (or at all).

So what comes next for generative AI? We checked in with a handful of tech leaders in an attempt to assess the AI vibes and where it feels like the tech is headed.

Peter van der Putten, AI lab director at enterprise software company Pegasystems:

We’ve seen and experienced generative AI’s mind-boggling abilities, including splashy (or scary) applications like mimicking celebrity voices, writing funny songs or stories, or creating deepfake videos that have dominated headlines, fueling a true frenzy around the technology. Now, we’re witnessing some of the backlash, especially as we think about major factors like ethics, regulation, content ownership, and more. I don’t see this as a sign of AI slowing down—it is a sign of AI growing up. As AI is leaving childhood and entering puberty, we just need to give it some ground rules—like we would do with teenagers.

This market frenzy—good or bad—is overshadowing the true potential of generative AI. While yes, fake celebrity videos are both funny and alarming, business leaders need to keep their eyes on the true prize and figure out how to implement AI within their organizations for real-world results that positively impact employees and customers…While the vibe can feel a bit overwhelming at the moment, in the coming year, we’re going to see businesses figure out their AI strategies—with some bumps along the way—to help properly implement the technology for the benefit of both businesses and customers.

Dan Diasio, global AI and automation consulting leader at EY Consulting:

If I was to generalize, 2023 is the year of inspiration and experimentation. A lot of companies have been more than dipping their toe in the water, but working on portfolios, figuring out what works, deploying that technology, and learning how to manage the risks—there’s a whole new set of risks with this particular technology. But I would largely chalk this up as most companies had a real good learning year around AI.

I think that really sets the table for companies next year to focus a lot more on value. And in order to do that, systemically, we’ve seen that as companies have gone through that learning journey, they’ve largely collected experiments along the continuum. And that’s often a large portfolio of experiments. When you talk to a company, they have 30, 50, or 60 different projects that they’re working on. Most of those technologies are addressing the way business processes are designed today. So everything is an assistant or a bolt-on to the way something was designed. My guess is that in 2024, it’s going to shift more toward a lot smaller, a lot fewer initiatives, but those initiatives that will help the companies build strategic differentiation, for competitive advantage and some space, so instead of, like, messing around with like a whole bunch of experiments, it will be a couple of initiatives for each [of the] companies that allow them to differentiate.

David Glick, SVP of enterprise business services at Walmart:

Generative AI emerged into the zeitgeist with incredible speed, creating an impressive hype cycle. This public interest around generative AI is what makes it so different from other disruptive technologies, like the move to the cloud. While the initial hype was certainly warranted, it has since slowed, and businesses are laser-focused on figuring out how to leverage generative AI to produce measurable results.

At Walmart, we have been able to implement generative AI quickly by putting the technology in the hands of our associates. In a crowdsourcing approach, we can find new use cases for generative AI that can be leveraged for new business applications and future product features. The most significant use cases and opportunities in generative AI are still unknown, so, the way you learn what works and doesn’t is to dive in and try it.

Cristina Pieretti, general manager of digital insights for Moody’s Analytics:

There’s the customer aspect of, “How should we be thinking about product development?” I do think it’s a very exciting, but at the same time, challenging way, because my team is dedicated to building products…and you do have to think about how does the experience change with generative AI? And given that the first interaction with a product is going to be that conversational interaction, what does it mean for the rest of the things you design?...And it’s hard because you have to imagine a future…And that’s something that I’ve asked everyone on my team; ‘you have to be thinking about: “What are the generative AI implications? How could this help you deliver a better experience? And what are the things that you should not be doing because you might be doing things differently?”...So I think we’re gonna see a lot of change, I see it already. It’s a change in how you interact with the product and how you do your tasks.

Jack Tam, chief technology officer at Intuit Mailchimp:

The accessibility and technology democratization that generative AI brings to small and midsize businesses illustrate how the hype around generative AI is matched by its tremendous value. Its ability to analyze vast amounts of individual customer data points and create individualized content with a simple interface doesn’t just benefit larger brands and enterprise organizations—it’s applicable and powerful for small and midsize businesses as well. It has the power to enable many opportunities to engage customers and accelerate growth beyond what is imaginable today. In fact, we’re seeing data to back that up: Over 70% of businesses will be prioritizing AI, financial technologies, and expanding e-commerce over the next 12 months, according to a recent survey of small businesses.

We expect that, as generative AI tools are increasingly integrated directly within software platforms, it will become even more pervasive—definitely passing the vibe check. Generative AI tools will be incorporated into consumer and small business product experiences and customers will be able to ask those tools for the end product rather than spend time building.

They can ask it to generate emails, content, schedules, do complex workflows—almost anything—directly within the interface, saving time and growing their business. Added to the fact that all of this can be accomplished without the learning curve that often comes with the introduction of new technology, generative AI will free up businesses to do more interesting and strategic work, pushing our technological limits further as generative AI continues to reinvent how we work.