An Innovation Veteran on What’s Next in Enterprise AI

Good morning. Nine years is a long tenure in any executive role. And a role specifically focused on chasing cutting-edge innovations? It can’t be easy.

When I sat down with ServiceNow’s longtime chief innovation officer, Dave Wright, he confirmed that.

“I can’t remember the last time I listened to music while driving,” said Wright. Those precious minutes are spent taking in podcasts. Later, he spends his time reading, researching and talking to sociologists, anthropologists, psychologists and AI experts to try to stay ahead of where the technology is going. Keeping up with everything requires real effort, he said.

When it created Wright’s role in 2017, ServiceNow’s goal was to make sure someone was conversant with cutting-edge technology and could explain the company’s product road map to clients. It has evolved, and now places a bigger focus on tracking future technologies and advising ServiceNow, its clients and potential clients on how those innovations could affect business and society.

The role is more critical than ever as ServiceNow navigates one of the most significant moments of upheaval the software industry has experienced. Earlier this year, fears that AI developers and labs would suck the value out of software, data, legal services and more erupted in the equity markets, battering software stocks, including ServiceNow’s. Since then, ServiceNow shares have regained some ground—they are up about 25% in the last six months—but they remain down about 33% from their 52-week high.

ServiceNow Chief Executive Bill McDermott has argued that ServiceNow was mistakenly caught in the rerating of software companies. He maintains that ServiceNow is fundamentally different because it is a platform company, acting as a control tower astride legacy systems, enabling AI models to interact securely across enterprise workflows.

Wright said that the so-called SaaSpocalypse narratives never actually materialized in business.

“AI really needs enterprise software to deliver any real ROI. You have models that can reason and come up with suggestions, but you need something else to then allow you to orchestrate the workflows, enforce governance or resolve what happens when something goes wrong,” he told me.

He believes one of the largest areas of potential is in creating a digital twin of entire companies that will allow leaders to simulate different business scenarios such as price cuts, new regulations or business expansions. The idea is to model different future scenarios that inform their big decisions.

If a new regulation is passed, you could have AI read the policy, map it across the digital twin of the organization, assess where it might be noncompliant, and start to build a remediation plan, he said.

Wright hasn’t seen any businesses capable of tackling this yet, given technological and organizational barriers. For one, companies need to first have all their workflows digitized—no easy ask for large, slow-moving legacy organizations. Secondly, the simulations themselves could become so complex that they might require more advanced computing resources, like yet-to-be-developed quantum machines.

“Quantum as a free-standing technology is interesting. But what’s more interesting is this technology convergence…with agentic AI, with physical AI, with robotics, with quantum, with digital twins. It’s trying to imagine what it’s like when all that comes together,” he said.

He’s also done research on CEOs who want to create digital twins of themselves (Mark Zuckerberg style).

He presented the idea to a group of CEOs in 2021. “At the time, everyone liked the concept, but said it couldn’t happen.” Two years later, in 2023, he presented it again to a very different reception.

“And at the end of that presentation, I had people asking when they could buy it. That’s the interesting thing about AI,” he said. “In two to three years, we went from ‘that’s impossible’ to ‘can I buy it?’”

Wright added, “Now when you start to look at quantum modeling, the reality of that becomes much more possible than it ever was before.”

Have you considered building a digital twin of your business? What do you see as the potential opportunities or pitfalls of trying to do so? And where else do you see enterprise AI innovation headed? Send your feedback to me at isabelle.bousquette@wsj.com (if you’re reading this in your inbox, you can just hit reply).

The rapid rise of Chinese AI models has sparked a host of questions in both Silicon Valley and Washington, but the careers of Tang Jie, a at Tsinghua University professor who co-founded Z.AI, and Yang Zhilin, who leads Moonshot AI, show that China’s AI push is nothing sudden, The Wall Street Journal reports. Each company is valued at tens of billions of dollars.

Tang, 49, has been working on machine learning for about a quarter-century. More than a decade ago, he was among the Chinese AI experts already at the forefront of using computers for humanlike tasks such as understanding language and recognizing faces.

Yang, whom Tang once nominated for his university’s top academic award, began intensive training in programming at age 17, competing in China’s National Olympiad in Informatics.

Tang, Yang and their fellow researchers—many of whom got started at Tsinghua and a few other institutions—make up a virtual Silicon Valley in China’s tech centers. Knowledge flows easily between them thanks to a culture of publishing research and the Chinese developers’ preference for open-source technologies that are largely free for download and modification.

To catch up in the era of generative AI, Chinese companies have relied on the familiar mix of ingenuity and imitation that also lies behind the nation’s successes in electronics, cars and green energy. Chinese AI developers brought back home U.S.-trained computer scientists and closely followed advances in the U.S.

Anthropic has accused Chinese companies, including both Z.AI and Moonshot, of violating its policies by engaging in large-scale distillation. Neither company has commented on the issue. People working at Chinese model developers acknowledge that distillation is widespread globally and that some Chinese companies might use it more aggressively than American counterparts.

Industry leaders in both countries said the capability of China’s best AI model is just months behind that of the best in the U.S.

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Follow Isabelle Bousquette on LinkedIn, Instagram, X, and TikTok for more behind the scenes on her tech and AI coverage, and lately, her contributions to the WSJ Leadership Institute’s new Executive Resilience series, where she’s profiling America’s top execs about their fitness and wellness habits.

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Steven Rosenbush is chief of the enterprise technology bureau at the WSJ Leadership Institute. He also has a column. You can follow him on LinkedIn.

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