The CEO’s AI Dashboard (a series begins)
Welcome to a new edition of The Board: Distillation Aftershots (*).
This blog is a reprint of a weekly newsletter, written by Constellation's Chief Distiller and Board Advisor Esteban Kolsky, shares curious and interesting insights and data points distilled from enterprise technology to identify what’s notable. If you'd like to receive this in your inbox, subscribe here.
In this issue, I want to introduce the framework I will use over the next two months to discuss how CEOs can plan, manage, and adjust AI strategy. AI strategy is now sitting at the center of operating decisions, capital allocation, risk, talent, and partner choices. That combination is why it has moved closer to the CEO. BCG’s 2026 AI Radar found that 72% of CEOs say they are the main decision maker on AI in their organization, and 50% believe their job depends on getting AI right. McKinsey’s board research adds another useful signal: 66% of directors say their boards have limited to no knowledge or experience with AI.
That context matters because AI strategy is rarely one decision. It is a set of linked decisions that tend to drift apart inside the enterprise. Value gets discussed in one forum, data in another, infrastructure in a budget cycle, governance after deployment begins, talent as a staffing issue, and ecosystem choices through procurement. CEOs end up carrying the whole picture because the organization usually does not. McKinsey’s 2025 global AI survey found that organizations generating bottom-line impact are more likely to redesign workflows and place senior leaders in explicit governance roles. Deloitte’s 2026 enterprise AI research points in the same direction: worker access to AI rose by 50% in 2025, and the share of companies expecting at least 40% of AI projects in production is set to more than double within six months. The volume is going up quickly; the management system has to mature with it.
That is why I prefer to think of AI strategy as a dashboard. The value of a dashboard is that it keeps the CEO looking at the full system at once. It also forces ownership to be visible.
| STRATEGIC AREA | PRIMARY RESPONSIBLE PARTY |
|---|---|
| Business Value of AI | COO / CIO |
| Data Readiness | CDO / CIO |
| Infrastructure Readiness | CIO / CFO / CTO / CAO |
| Governance | CISO / CFO |
| Economics of AI | CFO / CHRO |
| Talent | CHRO / COO |
Each of these areas answers a different management question. Business value shows where AI is improving growth, throughput, margin, or decision quality. Data readiness shows whether the enterprise has usable context rather than raw volume. Infrastructure readiness shows whether the architecture can support scale, cost, security, and resilience. Governance shows whether controls are shaping design early enough to matter. AI economics shows whether the spending model holds once pilots become recurring operating expense. Talent shows whether the workforce can absorb the change in work.
Over the next several weeks, I will use each area to develop a practical management perspective on AI strategy. My goal is not to create a maturity model. I want a working instrument a CEO can use to identify where the enterprise is aligned, where it is improvising, and where the appearance of progress is covering weak operational foundations.
Here are some reading resources:
- BCG says 72% of CEOs are now the main decision-makers on AI, and 50% believe their jobs depend on getting AI right, which supports direct CEO ownership of AI strategy.
- HBR and McKinsey report that 66% of directors say their boards have limited to no knowledge or experience with AI, which helps explain why CEOs are carrying more of the strategic load.
- McKinsey’s 2025 State of AI shows that organizations seeing bottom-line impact are redesigning workflows and assigning senior leaders to governance roles, which fits the dashboard approach.
- Deloitte’s 2026 State of AI in the Enterprise tracks the move from pilot to scale and helps clarify how quickly production expectations are rising.
- IBM’s 2026 CEO Study frames AI-first transformation as an operating-model challenge for CEOs, which aligns well with the series you are building.
- IBM’s AI governance guide is useful for the governance section because it focuses on how oversight, accountability, and operating discipline need to mature together.
- Deloitte’s 2026 CFO guide to AI-driven tech trends is a useful supporting source on infrastructure readiness and AI economics because it connects AI spend, variable costs, and financial discipline.
- Accenture’s Pulse of Change research is useful for the talent dimension because it ties AI value to employee alignment, training, and readiness for role changes.
What’s your take? We are fostering a community of executives who want to discuss these issues in depth. This newsletter is but a part of it. We welcome your feedback and look forward to engaging in these conversations.
If you are interested in exploring the full report, discussing the Board’s offering further, or have any additional questions, please contact me at [email protected], and I will be happy to connect with you.
(*) A normal distillation process produces byproducts: primary, simple ones called foreshots, and secondary, more complex and nuanced ones called aftershots. This newsletter highlights remnants from the distillation process, the “cutting room floor” elements, and shares insights to complement the monthly report.
Esteban Kolsky spent the first part of his professional career working on the customer service front line and in management roles, culminating in early implementations of first-generation CRM tools. In 2000, he became a research analyst at Gartner, focused on CRM, customer service, customer experience management, enterprise feedback management, and voice of the customer, among topics that later became the basis for the current field of CX. During his tenure at Gartner, Kolsky assisted vendors and Global 2000 organizations with their customer strategies. He left Gartner to focus his career on strategic advisory services and influenced all the major software vendors, as well as many smaller vendors, in the CX industry and advised executive leadership teams across industries and countries…...
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