What the research says
Kartik Hosanagaru, co-director of human studies at the Wharton School at the University of Pennsylvania, said the likelihood of success increases dramatically when companies support well-defined goals, such as significantly improving their chances of success.
Wharton's strategy for responsible AI programs reinforces this idea. The program advises companies to launch AI projects by identifying specific outcomes they want to improve, and will work in the opposite direction to explore how AI can help. Starting with business needs leads to more grounded applications and faster learning loops.
McKinsey's research supports this view, linking strong financial results from AI to the active involvement of CEOs. That doesn't mean that the CEO is reviewing the technical specifications. That means they stay engaged, ask clear questions, and AI initiatives are tied to measurable business outcomes.
In mid-sized organizations where leadership visibility is even more weighted, C-Suite engagement often determines whether AI efforts will move forward or halt.
What a great CEO does
High-performance CEOs treat AI as part of their business operating system. They don't delegate it and hope it comes back in business case. They stay close enough to see what is working, where there is friction, what is in focus.
They start by helping the organization sharpen the lens. Rather than approving everything that sounds innovative, challenge your team to identify business problems worth solving and outcomes worth improving.
They ask:
Equally important is that these CEOs bring AI into the right room. AI gains traction when it appears in operating reviews, when linked to KPIs, and when it is part of a performance discussion. If it is mentioned only in a strategy slide or innovation session, it tends to fade.
The best CEOs don't have to advocate for AI. They appear consistently. That's what drives the job forward.
90-day reset to get AI efforts on track
When AI efforts lose steam, it is often due to lack of alignment rather than interest. For CEOs looking to regain momentum through AI initiatives, this is the practical structure of the Recenter.
Days 1-30: Stock. Lists current AI-related initiatives. Clearly identify their purpose, ownership and indicators of success. Identify what is fixed and not in business outcomes.
Days 31-60: Prioritization and recommendations. Choose one or two efforts with a clear connection to your top priorities. They were embedded in the rhythms that were working, assigned advanced accountability, and made expectations visible.
Days 61-90: Formalization and expansion. Scales what's working. Establish optical governance for monthly check-in and dashboards. Define success criteria for expanding into other areas of your business.
Put it all together
Most companies no longer decide whether to invest in AI or not. They are trying to find a way to count it. That responsibility lies straight in the leadership team. This is three takeaways to guide you along the path forward.
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Stay close to the results. You don't need to understand the algorithm, but you need to know what's working, what's not, and why.
Former Cisco CEO John Chambers gave a clear warning when he said, “AI runs faster than the internet, and businesses that can't move quickly enough may not survive.”
But urgency without clarity does not produce results. Your team doesn't need any more hype. They need direction. The opportunity lies here. Tools are available. Turning AI into benefits is leadership who knows how to focus on effort and follow through.
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Bob Goodwin is the president of the Career Club, working with senior executives to improve leadership performance and align business strategies with people's outcomes. It also hosts Career Club Live, a podcast featuring leading brand Chros, and co-hosts the Wire Wire Podcast with SHRM President and CEO Johnny C. Taylor, Jr. and SHRM-SCP.
