Why In 2027 Every CEO Must Operate Like An AI Strategist
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This article originally appeared on Forbes Business Council.
AI has moved beyond the technology team and now shapes everything about the business, from where a company competes and how it organizes work to where it allocates capital and which risks it can afford to take. None of those decisions was ever the technology team’s to make, signaling that AI strategy has become a core CEO responsibility and will become even more prominent in 2027.
Recent research from the Boston Consulting Group (BCG) found that “72% of CEOs are now directly responsible for AI decisions in their companies,” but “only 15% are generating meaningful value from it,” further proving that owning the problem is not the same as solving it. Leaders must address this confidence gap before it becomes a real business challenge. CEOs should begin working with their executive teams to clarify what their involvement really looks like, and determine which decisions will remain with them and which will be delegated to the appropriate team leads.
Turn AI Pressure Into Opportunity
When digital transformation asked all businesses to operate like technology companies, many answered by hiring people who already did. Engineers held the technical knowledge, executives held the strategy, and this division worked because technology was still something the business used. Fast forward to today, and AI has effectively ended that arrangement. What the company sells, who it competes against and what it no longer needs are all questions AI is forcing executives to reevaluate.
CEOs must work toward the answers that are right for their industries while keeping in mind that value doesn’t come from adding AI to work that stays the same, but from redesigning it. Recent McKinsey research found that workflow redesign had the strongest relationship with reported bottom-line impact. Still, companies must have a vetted strategy in place to validate and understand their AI investments. Pressure to adopt new initiatives too quickly in the race to keep up creates little more than expensive experimentation. IBM’s 2025 CEO research found that 64% of CEOs felt pressure to invest in technologies before clearly understanding their value. The same research reported that only 25% of AI initiatives delivered their expected return, and just 16% scaled across the enterprise.
Executives can skip the expensive experimentation phase by beginning with some basic questions:
- What are our biggest opportunities (where does it make sense to invest)?
- Which experiments have less certainty and should remain small?
- What’s no longer working (where can we reallocate resources)?
- Are there capabilities we can or should build internally?
Your AI Strategy Is Dysfunctional Without A Culture Shift
AI strategy should also be rooted in culture. Such large-scale transformations affect jobs, career paths, expertise, training and the division of labor between humans and systems. This makes AI strategy inseparable from your company culture, and it can ultimately make or break your business.
Be prepared for employees to ask if AI is eliminating roles and get ahead of investing in AI training and upskilling. Furthermore, employees are increasingly expressing concerns about governance and accountability, and company leaders must have answers and guidelines in place. As the AI strategist, it’s the CEO’s job to note these concerns and address them head-on with clarity and transparency. A WEF write-up notes that 60% of CEOs said they intentionally slowed implementation because of concerns about AI errors or malfunctions.
Where To Invest In AI Value First
The aforementioned BCG research also points to the time CEOs invest in developing their own AI capabilities. It found that those spending at least eight hours per week learning about AI are more likely to produce meaningful value. BCG also cautions that the quality and purpose of the AI engagement matter more than simply accumulating training hours. Moreover, employees notice; they pay close attention to executive behavior. A CEO who publicly promotes AI but does not use it signals that the technology is peripheral, but one who uses it carelessly signals that controls are optional. In other words, if you can’t walk the walk, don’t talk the talk.
Evaluate Your AI Strategy
While the CEO does not need to learn to build AI models, they should invest time in developing their AI capabilities. Define where experimentation is acceptable, where human review is mandatory and where AI use is inappropriate, and remember that your personal AI habits will become part of the organization’s unwritten AI policy. Remember, the goal is not maximum ownership of AI, it’s strategic oversight of the company’s AI capabilities, data and relationships that differentiate the business.
Here are some things to keep in mind when evaluating your AI strategy:
- Assign executive ownership (this includes you!)
- Establish the investment and governance process (keep your technology leaders involved)
- Communicate the strategy companywide (everyone must be in the loop for it to work)
- Begin redesigning selected workflows (start small, keep employees informed)
- Set frequent review cycles with your leadership team (this is not a set-it-and-forget-it)
- Remove low-value pilots (ditch anything that’s tied to “AI for the sake of it”)
- Establish a dedicated channel for employee feedback
Above all, CEOs must recognize that AI leadership should be shared, but their own accountability cannot be delegated.