Recent breakthroughs in artificial intelligence are having ripple effects in virtually every industry, and the M&A field is no exception. This new technology has potentially huge implications for dealmakers, both in day-to-day practice and big-picture strategy. Datasite’s roundtable discussion for Q3 of 2023 focused on how buyers, sellers, and M&A advisors should think about AI as they look ahead.

Questions and Concerns About AI Adoption

Artificial intelligence seems poised to reshape virtually every field of human endeavor. Which of those impacts should be top of mind for M&A professionals?

According to Justin Gans, Senior Director at Capstone Partners, it can be hard to pick just one. AI has already had a considerable impact on the market landscape as major tech firms race to scoop up top talent through large acqui-hires. It’s also impossible to ignore the risks this technology poses, such as the spread of misinformation through deepfakes or the possibilities for market disruptions due to algorithm-driven stock trading.

Meanwhile, professionals across the workforce are wondering how this new technology will affect their careers, even as they search for effective ways to work with it. Audience polling numbers suggested that adapting to the novel capabilities of AI may be the most pressing concern for many, with 53% of viewers listing it as their number-one concern.

What’s Next For AI?

Amir Ghavi, Partner at Fried Frank, said he’s anticipating a major expansion in the ways artificial intelligence will be deployed. Initially, he pointed out, many observers viewed AI mainly in terms of individual apps like ChatGPT. Now, there’s a growing awareness of the viability of a multimodal approach incorporating disparate capabilities like image recognition, language models, and video generation.

“All of the applications we’re used to using today in the enterprise are going to have varying degrees of AI baked into them,” he said. “AI won’t look like one particular thing. Sort of like eggs in a cake, it’s going to be an invisible but quite powerful layer.”

Ashish Pagey, Datasite’s Vice President of Artificial Intelligence, agreed with Ghavi’s assessment. He also noted that there’s a great deal of progress being made on agentic tools that can perform complex, multi-stage tasks autonomously. In addition, the open-source world may be catching up to proprietary models like GPT4, which should further accelerate AI adoption.

AI Market Trends to Watch

The panelists suggested that the M&A market’s initial enthusiasm for AI is being tempered by a growing caution about the risks it poses. Sellers today often have to make a case for their ability to remain competitive in the face of AI-driven disruption.

At the same time, there’s an increasing expectation that companies in every space will have sophisticated cybersecurity and data analytics capabilities. Audience poll responses reflect this concern, indicating that concerns about data security are the biggest headwinds for AI in the M&A industry.

On the more positive side, the panel identified two major hotspots for AI-related deals. The first was advanced tech, as machine learning tools enable companies to better identify and engage with their customers.

Gans offered TikTok as a perfect example. “The thing that makes TikTok such a super-popular app is the way its algorithms can very quickly determine what is most of interest to any particular user,” he said.

Another potential growth area is in large-scale data analytics. The ability to derive useful insights from massive, unstructured data sets offers potentially game-changing benefits for buyers of all kinds.

Kicking the Tires on AI Acquisitions

Moderator Abby Roberts (Senior Director for Datasite Insights) asked the audience what’s most likely to cause a deal in the AI space to fall apart. The top contender: difficulty verifying the seller’s claims about their tech.

Gans concurred, adding that most of the deal collapses he’s seen have been due to exaggerated promises by sellers.

“For example, there was a company that claimed they were experts at identifying hazards for driverless cars,” he recalled. “They were great…when it was a nice, clean street in the middle of the day.”

The panelists suggested that one of the critical questions diligence teams should ask is whether a given solution is taking advantage of the latest in AI capabilities. Buyers may need to beware of companies that say they’ve built their own models, when in fact they’re simply reskinning open-source technology or adding UI/UX features to an existing engine.

“In a very short period of time, we’ve gone through two or three generations of technology,” Pagey said. “The thing I would look for is: Is this product using the previous generation’s technologies and competencies? Or are they well-positioned to use the next gen and continue to expand and differentiate?”

AI Tools In the M&A Workplace

Will generative AI tools increase or decrease the workload of M&A professionals? In a recent survey by Datasite, 47% said they expected this technology to make them busier rather than taking work off their plate.

“We think of AI more as automation, which is true,” Pagey said. “But the macro-level value for an organization is to use that automation to scale up.”

While many individual tasks may be faster with help from these novel tools, dealmakers may have much more to do as the capabilities of their firms expand. Ghavi seconded this view.

“It’s a productivity tool,” he said. “A country like France might use it to take more time off. I suspect that’s not going to be the way it plays out in America. We’re going to continue to try to do more in the same amount of time.”

The trillion-dollar question, he said, is whether dealmakers can handle this accelerated pace competently. Even with the added capabilities offered by AI, there’s a risk of vital details falling through the cracks when major workflows are handed over to computers.

Why Dealmakers Should Stop Worrying and Learn to Love AI

Roberts closed out the discussion by asking the panelists what advice they’d offer to M&A professionals who are concerned about this technology’s potential to disrupt the industry.

“Become as smart as possible about what AI can do,” said Gans, “both for you and your company. We’re past the initial adoption curve…if you don’t get smart on it, you’ll get left behind.”

Ghavi cited MIT roboticist Kate Darling’s suggestion that we should think of AI as animals rather than human replacements — semi-autonomous tools that will sit alongside humans.

He also pointed out that companies may be facing an important tradeoff: should they let vendors use their data to train their models? Their competitors will also have access to the advanced tools that result, but AI may not realize its full potential if companies are stingy with their data.

Pagey suggested that M&A companies may want to start their AI adoption with simple, reliable tools that will enhance their workflows without disrupting them. Then they can move on to more transformative capabilities.

“The first step, I think, will position people to understand, learn, de-risk, and remove some of the unknowns,” he said. “Step number two will probably have much higher returns.”