Readiness Reframed

Enterprise AI adoption is entering a new phase. Organizations are moving beyond experimentation, embedding AI into everyday operations and seeing stronger returns on their investments. Yet even as technology advances, confidence in the ability to manage future disruption is falling.

The 2026-27 Kyndryl Readiness Report reveals this growing paradox. While 64% of leaders report positive returns on AI investments, only 24% say their organizations are completely ready to manage external risks — a seven-point decline from 2025.

As AI becomes more deeply integrated into critical business operations, organizations face new demands on their infrastructure, workforces and risk management strategies. The challenge is no longer simply adopting emerging technologies, but building the capabilities to continually adapt as those technologies evolve.

Readiness is no longer something organizations achieve once. It’s something they must continuously maintain.

For years, enterprise AI strategies have been defined by experimentation. Now, the focus is shifting toward integrating AI into business operations and delivering measurable results.

The research shows meaningful progress. More organizations are moving AI beyond proof of concept, while fewer report having more pilots than they can realistically scale. But early success doesn’t necessarily translate into sustained business value.

Organizations are confronting new challenges, from unexpectedly complex integration and unpredictable AI spending to poorly defined use cases. And as expectations for AI returns grow, pressure to demonstrate immediate value can come at the expense of longer-term innovation.

The next challenge for enterprise leaders is not simply determining where AI can be deployed, but where it can create lasting value — and what must change to support it.

Enterprise modernization has long focused on improving efficiency, flexibility and performance. But AI is raising the requirements for what modern infrastructure must deliver.

While 71% of leaders describe their core IT estates as mostly or fully modernized, many acknowledge that their technology foundations aren’t equipped to support AI at scale. Legacy systems, fragmented data and technical debt continue to limit how quickly organizations can innovate.

These challenges are exposing the limitations of treating modernization as a one-time initiative. Infrastructure that meets today’s needs may not be prepared for tomorrow’s AI capabilities, business demands or regulatory requirements.

For enterprises, the priority is shifting from achieving a modernized state to building technology environments that can continuously evolve — supporting innovation without compromising performance, resilience or control.

Organizations are increasingly putting AI to work, even when the data supporting it isn’t ready.

Four in ten leaders acknowledge that their data isn’t prepared to support AI at scale. Yet these organizations are deploying AI into business workflows at rates comparable to those with more prepared data environments.

The consequences are significant. Organizations with data readiness gaps report AI-related failures at roughly twice the rate of their more prepared counterparts.

As AI becomes embedded in mission-critical operations, the quality, accessibility and reliability of enterprise data are becoming essential to successful implementation. Without stronger data foundations, organizations risk scaling the same weaknesses that limit innovation today.

As AI investments grow, enterprise leaders face increasing pressure to demonstrate returns while making decisions that support long-term business priorities.

But many organizations are still struggling to connect their AI ambitions with a deliberate, coordinated strategy.

More than one-third of leaders say their current AI strategy emerged by accident rather than design. Others report misalignment between technology roadmaps and business objectives, or differing perspectives among senior executives on the value of technology investments.

These disconnects can make it harder to prioritize investments, define success and sustain innovation as expectations change.

Turning AI investment into meaningful business value requires more than deploying the right technology. It demands clear objectives, leadership alignment and a shared understanding of how technology supports the broader business strategy.

For the third consecutive year, cyberattacks remain the leading external concern for business leaders. Yet confidence in the ability to manage these threats has fallen sharply.

AI is adding another layer of complexity. As attackers leverage AI to increase the sophistication of cyber threats, organizations are also turning to the technology to strengthen detection, response and defense.

This creates a new challenge for enterprise cybersecurity. As technology environments become more interconnected and AI takes on a greater role in operations, organizations need stronger visibility into their systems, dependencies and potential vulnerabilities.

The research reveals a disconnect between confidence in existing security measures and preparedness for future disruption. Building cyber resilience increasingly depends on an organization’s ability to anticipate, respond and adapt as the threat landscape changes.

As geopolitical uncertainty and regulatory complexity increase, enterprises are reconsidering where their critical systems operate, how their data is managed and how much control they have over the technology supporting their businesses.

Digital sovereignty is increasingly influencing decisions beyond regulatory compliance. Organizations are weighing the benefits of innovation and speed against the need for operational independence, resilience and control.

Many leaders are willing to accept higher costs or slower technology adoption to maintain greater control over their environments. Yet the actions organizations are taking to strengthen sovereignty vary widely, from mapping sensitive data to evaluating third-party dependencies and preparing for provider disruptions.

The findings suggest that sovereignty is becoming an important consideration in enterprise technology strategy—not simply a requirement to address after decisions have already been made.

The 2026-27 Kyndryl Readiness Report has insights from 3,700 senior business and technology leaders across 21 countries.

The research spans 24 industries, with a focus on banking and financial services, energy and utilities, healthcare, insurance, manufacturing and telecommunications.

The survey was conducted by Edelman Intelligence on behalf of Kyndryl between July 10 and September 2, 2026. Respondents included an equal mix of C-suite executives, senior decision-makers and business and technology leaders.