Only 19% of enterprises have AI-ready data, jeopardizing 69% of CEOs' AI goals

For AI practitioners, the CEO survey is a reality check. The industry has spent two years marveling at model breakthroughs, but the real barrier to enterprise AI deployment isn't intelligence—it's data. With fewer than one in five organizations having AI-ready data, the next phase of the AI revolution will be fought not in model architecture but in the unglamorous trenches of data plumbing and network modernization.

A new Cisco survey of chief executives reveals a growing anxiety at the highest levels of business: more than half fear their companies will fall behind due to inadequate technology foundations for AI. The research, published in July 2026, found that 69% of CEOs now view AI adoption as essential to remaining competitive, yet over 50% believe their existing infrastructure could limit AI initiatives. This apprehension is radically reshaping executive priorities, with 40% of CEOs ranking infrastructure modernization as their top business priority for 2026. The significance of this shift cannot be overstated: for the past two years, the dominant narrative around enterprise AI has been about model experimentation—trying out generative AI for chatbots, coding assistants, and content generation. Now the boardroom conversation is pivoting sharply from 'what can AI do' to 'how do we make it work at scale,' and the answer is proving to be a daunting infrastructure challenge.

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The proportion of CEOs citing a lack of AI knowledge as a barrier to boardroom discussions has fallen from 74% a year ago to under half, while those saying it prevented informed decision-making dropped from 74% to 49%.

The findings build on Cisco's 2025 AI Readiness Index, published in October 2025, which surveyed more than 8,000 IT leaders globally and painted a sobering picture of enterprise preparedness. Fewer than one-quarter of organizations reported that their networks were fully optimized for AI workloads, while a mere 19% said their in-house data was fully centralized and accessible for AI applications. These technical bottlenecks—networking, data management, and security—have now converged with CEO sentiment, producing a powerful mandate for modernization. The convergence is striking: the executives who control budgets now understand, with greater clarity than ever, that pouring money into AI models without fixing the underlying plumbing is a recipe for wasted investment. The proportion of CEOs citing a lack of AI knowledge as a barrier to boardroom discussions has fallen from 74% a year ago to under half, while those saying it prevented informed decision-making dropped from 74% to 49%. Boardroom AI literacy is rising fast, and with it, the conversation is becoming more operationally rigorous.

The 2026 CEO priority stack reveals a layered transformation strategy. After infrastructure modernization, the second-ranked priority is upskilling teams to handle AI workloads, followed by deploying AI agents alongside employees, measuring AI’s business impact, and strengthening governance. This sequencing is logical but fraught with risk: if infrastructure upgrades lag, the AI agents and employee upskilling may not have the scalable foundation they require. Conversely, companies that move swiftly on the infrastructure front could achieve a powerful first-mover advantage. The timeline is especially tight given the fast pace of AI capability advances; delaying modernization by even 12 months could leave a company stranded in the legacy era while competitors pull ahead.

The implications for the technology market are profound. A massive reallocation of IT budgets is likely, with spending flowing away from experimental AI software and toward networking equipment, cloud data platforms, and cybersecurity infrastructure. For vendors like Cisco, this is an opportunity to capture a wave of demand, but the survey also signals that no single provider has a lock on the solution; startups in data centralization, edge networking, and AI governance are likely to see a surge of enterprise interest. At the same time, the report highlights a tension between ambition and executive confidence: while CEOs are bullish on AI’s importance, the fact that over half worry their infrastructure could limit them suggests a recognition of vulnerability that could drive accelerated investment cycles in 2026 and 2027.