Four ways CEOs can lead smarter with AI

AI adoption is widespread

AI use is now common. Most large companies, especially in Japan, have deployed tools like Copilot and ChatGPT to help employees with everyday tasks. These tools are often used for writing, summarizing, and generating ideas. That’s a start, but it’s not transformation. It’s surface-level productivity improvement. True transformation happens only when AI is embedded into the systems that run the business, operations, decision-making, and customer-facing workflows.

Many companies still focus on optimizing what already exists rather than redesigning how they work. This creates a hidden risk: while they chase marginal gains, competitors who deeply integrate AI will reshape markets. As Marcos Galperin, Founder of Mercado Libre, warns, many organizations are “maximizing the minimum.” They’re refining outdated systems that may soon become irrelevant.

For executives, this point is critical. The bar has moved from adoption to integration. Generative AI is more than a productivity booster, it’s an instrument for defining new value chains and efficiencies. Leaders who only use AI to fine-tune the current model risk becoming obsolete when the next model arrives.

The scale of adoption is clear. By late 2024, over 70% of large Japanese companies had introduced generative AI, according to the Information-technology Promotion Agency of Japan. Yet only 13% had used it within their core business processes. In the U.S. and Germany, around 40% have done so. Closing that gap means not only deploying AI but redesigning systems around it. The message is simple: adoption gets you started, integration takes you forward.

Leadership mindset is the primary barrier

Technology is not the problem, it’s leadership. Many CEOs still view AI as a useful set of tools, not as a core force capable of transforming how their companies think and operate. This narrow view limits potential impact. AI’s true value doesn’t come from deploying software; it comes from reshaping organizational behavior and strategic decision-making around what AI makes possible.

Strong leadership must shift from management to transformation. It’s not about new tools; it’s about new ways of working. Leaders who hold a traditional mindset, focused on efficiency rather than reinvention, will end up stuck in incremental improvement. Those who see AI as a chance to rebuild their companies will lead the next era of growth.

Robert Smith, Founder of Vista Equity Partners, makes the point clear: leaders who treat AI as a checklist item will struggle to find real returns. Those who see it as a catalyst for rethinking how work happens, how decisions are made, and how value is created will move ahead faster and further.

This is where executive behavior sets the tone. Companies that are ahead have made AI a standing discussion in leadership meetings. Their CEOs spend time learning how AI shifts cost models and future growth. They track AI initiatives as rigorously as other strategic goals. But tracking isn’t enough, it must be visible. Sharing early wins with teams creates momentum. Tangible results change culture more effectively than top-down mandates ever will.

For executives, this is not an abstract principle. Leadership must evolve. The challenge isn’t asking, “How do we use AI?” It’s asking, “What do we need to become because of AI?” The companies that understand this distinction are the ones already redefining the game.

CEOs must dedicate substantial attention to AI as a strategic priority

AI cannot stay confined to technical teams or innovation labs. It must sit at the center of executive deliberation. Most CEOs understand the potential of AI, but many still treat it as a set of experiments rather than a driver of strategy. That approach limits growth. Companies that realize AI’s real potential devote consistent and structured leadership attention to it.

CEOs should be investing at least 20% of their time understanding how AI changes their business. This includes how it reshapes cost structures, redefines competitive positioning, and fuels long-term growth. When AI becomes a regular item in leadership discussions, it signals its strategic weight. The focus must shift from tracking pilot projects to exploring how AI transforms the operating model as a whole.

C-suite leaders should study how AI is altering their industry’s economics in real time. This means understanding its impact on margins, learning cycles, and decision velocity. Companies that fail to integrate this knowledge risk being overtaken by competitors that do. Dedication of time and focus is no longer optional, it’s a signal of strategic seriousness.

Executives must see AI as a continuous transformation journey. The more leadership engages, the faster their organizations build the internal muscle to iterate and scale. The companies winning with AI today are the ones where CEOs are visibly leading the charge.

Establishing a culture of safe and proactive AI experimentation is crucial

For AI to achieve meaningful results, organizations need an environment where people can explore, test, and reimagine their work with confidence. Employees must have the freedom to experiment without fear of failure or job insecurity. They also need clear rules and technical safety nets to ensure responsible innovation. CEOs play a critical role in shaping this environment. A strong innovation culture depends on two things: psychological safety and structured governance.

Creating this balance starts at the top. When leaders provide secure access to AI tools, establish clear guidelines for data use, and reward experimentation, they build momentum. Recognizing employees who improve workflows or automate parts of their roles sends a message that progress is valued. This is how organizations activate their collective potential for transformation.

Tobi Lütke, CEO of Shopify, provides an effective example. He declared that effective AI use is a “fundamental expectation of everyone at Shopify.” This directive wasn’t symbolic, it applied to all levels of the organization, including the executive team. Lütke required AI to be part of prototyping, performance reviews, and internal collaboration. Employees had to demonstrate that AI couldn’t fulfill a requirement before requesting additional resources. His approach turned AI curiosity into disciplined adoption.

For executives, the nuance lies in positioning AI adoption as a requirement. Safety and urgency must coexist. Encouraging exploration while embedding accountability ensures that innovation happens both quickly and responsibly. This balance produces results that scale, the kinds of results that move an organization from cautious AI adoption to confident transformation.

Focusing on a few high-impact AI initiatives drives competitive advantage

Spreading resources across too many small AI projects dilutes impact. The companies leading real transformation are the ones concentrating their capital and talent on a few initiatives that can reshape key areas of performance, things like product innovation, pricing strategy, and customer retention. Focus matters more than volume.

Executives should define two or three areas where AI can create measurable value and then commit the organization’s energy to those areas. These “big bets” need continuous validation through clear metrics, rigorous testing, and rapid iteration. Prioritizing fewer, larger initiatives keeps teams aligned and ensures that AI investments convert into outcomes that can be seen at the P&L level.

A U.S.-based media organization offers a good model. It collects potential AI use cases across the company, prioritizes them based on business impact, and develops minimum viable products through a dedicated team. Successful projects are quickly scaled or made reusable across other departments. Governance, covering data permissions, legal compliance, and ethics, is centralized to maintain control while allowing innovation to move fast. This structure keeps experimentation safe while turning AI from an isolated experiment into an enterprise-wide capability.

For executives, the nuance is in maintaining both discipline and ambition. AI initiatives must have a clear business rationale and a defined pathway from prototype to profit. Leadership focus ensures that resources aren’t scattered across small wins but concentrated where the potential for transformation is greatest.

CEOs must develop their own AI fluency to lead credibly

To lead effectively in an AI-driven world, CEOs can’t rely solely on second-hand knowledge. Understanding AI through hands-on experience is essential for sound judgment and credible decision-making. The more an executive works directly with AI tools, the clearer its potential, and its limitations, become. That clarity shapes better strategic direction.

This doesn’t mean CEOs need to become technical experts. The goal is to build realistic intuition, enough to ask smarter questions and to identify what’s possible versus what’s hype. Without direct interaction, leaders risk making decisions detached from the accelerating pace of AI capability. It’s a leadership competency now, not a future skill.

Several leaders are already setting this example. Satya Nadella, CEO of Microsoft, uses AI copilots to synthesize information across meetings and internal documents, turning what would otherwise be scattered data into organized insight. Jensen Huang, CEO of Nvidia, uses AI as a research assistant to accelerate his own learning. These practices demonstrate that curiosity and direct use create tangible leadership advantage.

For executives, the immediate takeaway is clear: active engagement builds credibility. Teams pay attention when leaders use the same tools that are transforming the business. It signals seriousness and helps break down resistance to change. Reports and briefings can provide awareness, but consistent hands-on work delivers understanding, and that understanding is what turns AI from a concept into an organizational force.

Key executive takeaways

• Move from AI adoption to integration: Most companies use AI for productivity gains but not for transformation. Leaders should embed AI into core operations and decision-making to unlock real competitive advantage.
• Shift leadership mindset for impact: Technology isn’t the barrier, mindset is. CEOs must treat AI as a driver of business reinvention, not a tool for efficiency, and make it a regular item on the strategic agenda.
• Make AI a top-tier priority: CEOs should dedicate at least 20% of their time to understanding how AI reshapes cost, growth, and competition. Active executive involvement signals that AI is central to the company’s future.
• Create a safe and ambitious AI culture: Build conditions where employees can experiment with AI securely and confidently. Reward innovation, set clear usage rules, and ensure that progress is both encouraged and accountable.
• Focus energy on high-impact AI bets: Concentrate resources on a few AI initiatives with measurable business value. Prioritize, prototype, and scale what works to accelerate enterprise-wide transformation.
• Lead through personal AI fluency: CEOs must engage directly with AI tools to gain intuition and credibility. Hands-on experience enables better questions, smarter decisions, and stronger leadership alignment across the organization.