Earlier this week Corporate Board Member hosted it’s 20th annual Boardroom Summit in New York, two days that were chock-a-block with ideas and insights from a raft of compelling speakers. We’ll have plenty to deliver to you from the event in the days ahead, but for now, we’ll focus on a session that drew a ton of attention—and questions.
The topic? Generative artificial intelligence, of course. Keith Meyer, Global Practice Leader of Board Services at Major, Lindsey & Africa interviewed Florin Rotar, Chief AI Officer at Avanade, about the burgeoning impact of AI on corporate governance. They hit a ton of hot issues, from regulatory complexities to internal company dynamics, offering up some useful insights for corporate boards navigating the dawn of the AI age.
“We are probably, as an industry and as leaders, overestimating the short-term impact, but dramatically underestimating the midterm impact,” said Rotar, who oversees AI and AI training for the 65,000-person consulting firm. His take: The biggest risk is not taking a risk here. Some useful takeaways from the session:
Regulation: “If you do business in Europe, you will be regulated,” Rotar said. The EU’s aggressive approach to AI governance means that companies across industries must prepare for strict oversight. Rotar urged board members to ask management teams about their strategies for “responsible AI.” “If they look like, ‘What are you talking about?’ then you have a risk.”
Control Tower: To address AI governance, Rotar suggests a centralized system for monitoring AI’s integration and impact across the organization. “The risk that we as a board think we’re taking is actually represented in reality on the ground,” Rotar explained. “That, in my experience, is the biggest risk today.” This AI “control tower” functions at multiple levels—project teams, executive management and the board—enabling boards to set risk parameters, monitor use cases and maintain transparency in AI’s application.
AI Driver’s License: Avanade implemented a “School of AI” to train its employees and introduced the concept of an AI “driver’s license.” “Every single one of 65,000 people has had to go through a training of responsible AI and basic prompting,” Rotar said. This initiative ensures that all employees, regardless of role, understand AI’s fundamentals and responsible usage. Depending on their responsibilities, employees receive different levels of training, akin to licenses for operating vehicles. “There are controls,” he said, “and we test people, and if you [make] mistakes you might get your driver’s license revoked.”
AI in the Boardroom: Rotar described how Avanade’s board uses AI to streamline their workflow, allowing directors to interact directly with data rather than being inundated with reports. AI tools help boards by preparing materials, synthesizing data and even simulating complex scenarios to facilitate more productive and informed meetings. Moreover, the concept of an AI board “co-pilot” is becoming feasible, assisting directors in understanding vast amounts of information and aiding in governance tasks.
Activist Simulator: Beyond operational efficiency, AI offers the potential for boards to simulate crisis scenarios—for instance using AI to simulate the actions of activist investors—allowing boards and management to run prepare for potential challenges proactively.
Motivating People to Use AI: With a couple years of AI rollout efforts under his belt, Rotar said he’s found the key to any successful AI integration lies in motivating employees by focusing on empowerment rather than just productivity—as you might expect. “The number one priority is to empower our people to become the best version of themselves,” he said. By framing AI as a tool for personal and professional growth, organizations can reduce fear—and build trust.
“I’ve been in technology 35 years,” said Rotar. “[This is] one technology where I’m constantly surprised by how much continuous change enablement is needed, because it takes so much to help people to truly think about AI as an enabler rather than threat to them. It requires still so much energy to unlearn and relearn new habits. And it shouldn’t be like that. AI should adjust to us people rather than the other way around. But it’s reality. So continuous change enablement at scale is absolutely critical for success.”
