Many tech chiefs expect AI policy to remain at the state level
Technology leaders at UKG, Pearson, Sutherland, Genesys, Intuit, Appian and Toshiba America were pushing ahead with AI plans despite potential regulation under Democratic control of the House and Senate and state offices, according to interviews by Belle Lin for The Wall Street Journal’s CIO Journal. Tech business leaders who spoke to The Wall Street Journal Leadership Institute said the scenarios discussed in those interviews were not much of a concern for their own AI initiatives, which have only been gaining steam as they increase spending on AI.
Several explanations sit behind that assessment. Some leaders said their companies have pursued internal guardrails and standards for AI safety, making outside regulation less likely to affect how they use AI. Many also said existing AI models already have enough capability to satisfy their technology needs, making a potential AI development slowdown unlikely to alter their future AI plans.
AI regulation could give companies such as UKG the comfort to use AI more aggressively, Prakash Kota, chief transformation officer of the HR software firm, said. “Right now it feels like there’s unknown territory that I’m going into,” he said. “It’s a lot more on enterprises to define those things. If policies come into play that give us more comfort, risk-averse people would want to lean in.”
Dave Treat, chief technology officer of Pearson, said the London-listed education company had already focused on using AI responsibly within the firm and that focus would not change as the regulatory environment evolved. “We already operate with strong governance, privacy, security and human oversight standards, and we expect those principles to remain important under any regulatory framework,” he said. “Thoughtful regulation could help build trust and provide clarity.”
Other tech leaders said they were similarly prepared for any AI regulatory environment, with an enterprise’s own controls and governance over the technology taking precedence. Alex Balazs, chief technology officer of financial-software maker Intuit, said Intuit was prepared for a changing regulatory climate because it had already put its own responsible AI initiatives into practice. “Our principles go beyond what the law requires and reflect what we believe should be the industry standard,” he said. Andrea Schulze Dias, vice president and group chief information officer of Toshiba America, said responsible AI governance would remain a priority regardless of the regulatory timeline. “While new regulations may introduce additional requirements around data privacy, security and governance, our focus remains on adopting AI responsibly,” she said.
Sutherland’s Gilbert gave those internal controls a concrete form. “We built for it. Every agent we run has an audit trail, a confidence threshold and a human checkpoint,” he said. “The companies at risk aren’t the ones using AI aggressively, they’re the ones who can’t produce a log of what their AI did and why.”
Treat also said existing AI models offer plenty of untapped capabilities and that Pearson would still find current models capable enough even if the pace of frontier model development slowed. “With the power of the models as they are today, there’s a long way to go,” he said. “We’re just at the beginning of diffusing or achieving all of that value, so it wouldn’t be the end of the world. But obviously I’m a big fan of constant innovation.”
Doug Gilbert, chief information officer and chief digital officer of IT and business services company Sutherland, said the need for the most powerful models from OpenAI and Anthropic was “extremely low” for everyday applications. “If you look at 95% of the tasks that need to be done, you can use models that have been around for a while,” he said.
Tony Bates, chief executive and chairman of customer-experience technology provider Genesys, said it was possible that pausing the development of AI models could hold back innovation at the company, while the capabilities of current frontier models and Genesys’s own models were good enough. “The technology itself is less of the discussion,” he said. “The conversation is moving from simply pushing the frontier to making sure AI can operate safely in the enterprise.”
Some enterprises were shifting emphasis away from AI models themselves and toward the model harness. The harness is software that runs an AI system, provides memory and business-data context, allows businesses to mix and match models and manages AI token costs, ultimately making enterprises less reliant on a single AI model provider. Balazs said regulation that slows the pace of model innovation would hurt on some level. “Regulation in terms of slowing the pace of model innovation, would that hurt us on some level in terms of an enterprise? Sure,” he said. “But we right now are making a huge focus and investment on building the right AI harness.”
As Democrats began honing in on AI regulation, especially for data centers, many corporate technology chiefs said they expect AI policy to remain at the state level rather than moving quickly federally, and they expect any change to take time. Gilbert framed that expectation this way: “The midterms settled the one question that mattered for many enterprise technology leaders: There will be no federal ceiling on AI regulation anytime soon,” he said. “State laws—California, Colorado, New York, Texas—are the operating standard, not a placeholder.” He added: “I don’t expect sweeping federal legislation from a divided government, but I do expect aggressive oversight.”
Appian’s Matt Calkins identified potential costs to a state-level patchwork. State-level regulation could hurt companies because “it could be irregular across the nation, and because some issues, like alignment and intellectual-property rights, are best handled federally.” Bates said the outcome of the midterms increases the likelihood of AI regulation, but said the more important issue is “whether we get practical guardrails that build trust without slowing innovation.”
The regulatory possibilities remain broad. Regulation around AI models could take any number of forms, especially as Democrats are likely to focus on safety, which had already become a bigger priority for lawmakers. Democrats at the national and state level may push for regulations that set guardrails for new AI models, which could include testing models before they are released publicly. The Wall Street Journal reported that prominent companies and individuals have recently called for mechanisms that would allow AI labs and countries to slow development in a coordinated way to buy time for alignment research, and that lawmakers from both parties have proposed many bills to address “rogue AI systems.”
The interviews did not settle how internal controls will compare with statutory requirements, or whether Congress eventually supplies a federal floor. The executives described the scenarios as not much of a concern for their AI initiatives, and many said a potential development slowdown was unlikely to alter their future plans.