FINDLAY, OH – December 24, 2025 – PRESSADVANTAGE –
Dr. Andrea Adams-Miller, an applied neuroscientist, executive advisor, communication strategist, and CEO of The RED Carpet Connection LLC, warns that the rapid expansion of artificial intelligence inside companies has created a governance gap that many boards have not yet closed.
As organizations increasingly rely on AI to guide hiring, pricing, forecasting, and risk decisions, boards now oversee systems that move faster than people can reasonably evaluate. That speed raises exposure when leaders trust AI output without clearly understanding how the system reached its conclusions.
Her assessment reflects growing concern at the highest levels of government and industry. During testimony before the U.S. Senate Judiciary Subcommittee on Privacy, Technology and the Law on **May 16, 2023**, in Washington, D.C., Sam Altman stated, “We think that regulatory intervention by governments will be critical to mitigate the risks of increasingly powerful AI systems.”
According to Adams-Miller, that warning applies directly to corporate boards. AI entered organizations as a tool to improve efficiency, but it has quickly become a leadership and oversight issue. Boards once focused primarily on people, strategy, and results. Boards now also oversee AI systems that affect decisions, but do not always clearly show how those decisions were made.
Recent, well-documented cases highlight how governance failures emerge when oversight lags behind technology. At Amazon, leadership shut down an internal AI hiring tool after it showed bias against female candidates. At Zillow, automated pricing models contributed to significant financial losses, prompting the company to exit its home-buying business. In both cases, boards faced scrutiny for approving systems without adequate review, testing, or explanation.
“These examples point to leadership and oversight failures, not just technology problems,” Adams-Miller said.
AI systems often deliver answers quickly and with confidence. Under pressure, executives may rely on those answers without slowing down to question assumptions. Speed can create a false sense of certainty, leading leaders to confuse fast responses with sound judgment. As AI spreads across daily business operations, decision timelines continue to shrink, making clear explanation and accountability harder to maintain.
Boards remain responsible when AI-driven decisions trigger compliance issues, reputational damage, or financial loss. Responsibility does not disappear when machines make decisions. Responsibility shifts, often faster than governance structures evolve.
To address these risks, Adams-Miller outlines a practical governance framework boards can adopt immediately. Boards should assign ‘clear human ownership’ to every AI-influenced decision, require ‘plain-language explanations’ for how AI affects outcomes, and establish ‘defined pause points’ where leaders slow decisions, review risk, and override AI when necessary. Boards should also require ‘communication readiness,’ ensuring executives can clearly explain AI-driven choices to employees, investors, regulators, and the public.
Adams-Miller notes that stress and information overload increase reliance on AI. Executives managing rapid change and constant pressure naturally look for shortcuts. AI often feels like a safe shortcut because it appears neutral and data-driven, even though human choices and limits shape every system.
AI now sits at the center of leadership, not just technology. According to Adams-Miller, AI tends to amplify what already exists inside an organization. Strong leadership becomes clearer, while weak decision-making becomes harder to hide.
“AI can help leaders see patterns,” Adams-Miller said. “People still decide what those patterns mean and what actions follow.”
About Dr. Andrea Adams-Miller
Dr. Andrea Adams-Miller is an applied neuroscientist, executive advisor, and communication strategist, and CEO of The RED Carpet Connection LLC. She advises CEOs, boards, and senior leaders on leadership, decision-making, and governance in AI-driven organizations.
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