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AI's Inflection Point Will Redefine Enterprise Readiness in 2026

Dennis Perpetua
Kyndryl

Across industries, enterprises are facing an uncomfortable truth: years of rapid AI adoption have created fragmented IT infrastructures, accidental cloud environments, and workforces that struggle to keep pace with constant innovation.

At the same time, Kyndryl's 2025 Readiness Report revealed that 61% of global business and technology leaders report increasing pressure from boards and regulators to prove AI's ROI. As the technology evolves and expectations continue to rise, leaders are compelled to generate and prove impact before scaling further. This will lead to a decisive turning point in 2026. As companies finalize their budgets and plans, we'll see a clear shift from ambition to execution. The priority will move toward building resilient foundations, aligning technology and employee readiness, and scaling AI initiatives with greater confidence.

Enterprises that adapt will be positioned for sustainable growth. Those that don't will fall behind in the next wave of disruption.

External Adoption Takes a Step Back

After several years of AI-first investments, 2026 will mark a return to fundamentals. Organizations are recognizing that lasting innovation depends on the strength of the infrastructure supporting it. With 25% of mission-critical systems near end-of-service, leaders will shift their focus to reinforcing their IT core — sometimes at the expense of experimental AI pilots.

Infrastructure modernization will move to the forefront, claiming a larger share of IT budgets as companies solidify the systems that enable AI. This isn't a retreat from innovation; it's a recalibration. The next wave of competitive advantage will come from combining advanced AI capabilities with secure, high-performing, and compliant foundations.

Workforce Readiness Will be a Leading Indicator of AI ROI

Simultaneously, the AI employee readiness crisis will evolve from a technical challenge to a cultural one. While 87% of business leaders believe AI will completely transform jobs within a year, only 31% say their workforce is ready to leverage it. This growing gap creates a "readiness paradox": one in which organizations are scaling technology faster than their people can absorb it.

As this paradox deepens, leaders will begin to recognize that the real determinant of transformation success isn't tooling, it's trust. In fact, 42% of leaders cite building employee trust as a major obstacle to AI adoption. Companies can no longer rely solely on hiring or deploying new technology to stay ahead.

Investment in change management, upskilling, and re-skilling will surge as leaders prioritize workforce readiness as the key lever for realizing AI ROI. The organizations that close the cultural gap, empowering employees to engage confidently with AI, will be the ones that capture its full potential.

Geo-Aligned Cloud Ecosystems Have Arrived

Cloud strategy will become as much about sovereignty as it is about scale. Enterprise leaders must navigate a complex web of regional data laws and compliance standards that shape where and how they deploy AI infrastructure.

Already, a majority of enterprises have adapted their cloud strategies in response to geopolitical pressures. In 2026, that number is expected to climb. Localized compliance frameworks will no longer be an exception; they'll be a core KPI measured against AI and cloud implementation strategies.

In this new era, enterprises will prioritize trusted geography over pure cost efficiency, and multinational organizations will shift toward multi-cloud-by-design architectures, striking a balance between performance and resilience. This evolution has direct implications for the nearly 70% of business leaders who feel unprepared to manage external risks such as regulatory uncertainty and market volatility. The same proportion reports that their current cloud environments evolved "by accident, not by design," and nearly all (95%) say they would redesign their cloud strategies if given the opportunity.

The difference between enterprises that use AI and those truly prepared for it will become clear in 2026. Readiness won't be measured by how fast organizations adopt new technologies, but by how strategically they align their infrastructure, governance, and people to use them effectively. Building resilience — technological, cultural, and operational — will define the next wave of transformation.

Dennis Perpetua is Global CTO of Digital Workplace Services & Experience Officer, VP, and Distinguished Engineer at Kyndryl

The Latest

For years, infrastructure teams have treated compute as a relatively stable input. Capacity was provisioned, costs were forecasted, and performance expectations were set based on the assumption that identical resources behaved identically. That mental model is starting to break down. AI infrastructure is no longer behaving like static cloud capacity. It is increasingly behaving like a market ...

Resilience can no longer be defined by how quickly an organization recovers from an incident or disruption. The effectiveness of any resilience strategy is dependent on its ability to anticipate change, operate under continuous stress, and adapt confidently amid uncertainty ...

Mobile users are less tolerant of app instability than ever before. According to a new report from Luciq, No Margin for Error: What Mobile Users Expect and What Mobile Leaders Must Deliver in 2026, even minor performance issues now result in immediate abandonment, lost purchases, and long-term brand impact ...

Artificial intelligence (AI) has become the dominant force shaping enterprise data strategies. Boards expect progress. Executives expect returns. And data leaders are under pressure to prove that their organizations are "AI-ready" ...

Agentic AI is a major buzzword for 2026. Many tech companies are making bold promises about this technology, but many aren't grounded in reality, at least not yet. This coming year will likely be shaped by reality checks for IT teams, and progress will only come from a focus on strong foundations and disciplined execution ...

AI systems are still prone to hallucinations and misjudgments ... To build the trust needed for adoption, AI must be paired with human-in-the-loop (HITL) oversight, or checkpoints where humans verify, guide, and decide what actions are taken. The balance between autonomy and accountability is what will allow AI to deliver on its promise without sacrificing human trust ...

More data center leaders are reducing their reliance on utility grids by investing in onsite power for rapidly scaling data centers, according to the Data Center Power Report from Bloom Energy ...

In MEAN TIME TO INSIGHT Episode 21, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses AI-driven NetOps ... 

Enterprise IT has become increasingly complex and fragmented. Organizations are juggling dozens — sometimes hundreds — of different tools for endpoint management, security, app delivery, and employee experience. Each one needs its own license, its own maintenance, and its own integration. The result is a patchwork of overlapping tools, data stuck in silos, security vulnerabilities, and IT teams are spending more time managing software than actually getting work done ...

2025 was the year everybody finally saw the cracks in the foundation. If you were running production workloads, you probably lived through at least one outage you could not explain to your executives without pulling up a diagram and a whiteboard ...

AI's Inflection Point Will Redefine Enterprise Readiness in 2026

Dennis Perpetua
Kyndryl

Across industries, enterprises are facing an uncomfortable truth: years of rapid AI adoption have created fragmented IT infrastructures, accidental cloud environments, and workforces that struggle to keep pace with constant innovation.

At the same time, Kyndryl's 2025 Readiness Report revealed that 61% of global business and technology leaders report increasing pressure from boards and regulators to prove AI's ROI. As the technology evolves and expectations continue to rise, leaders are compelled to generate and prove impact before scaling further. This will lead to a decisive turning point in 2026. As companies finalize their budgets and plans, we'll see a clear shift from ambition to execution. The priority will move toward building resilient foundations, aligning technology and employee readiness, and scaling AI initiatives with greater confidence.

Enterprises that adapt will be positioned for sustainable growth. Those that don't will fall behind in the next wave of disruption.

External Adoption Takes a Step Back

After several years of AI-first investments, 2026 will mark a return to fundamentals. Organizations are recognizing that lasting innovation depends on the strength of the infrastructure supporting it. With 25% of mission-critical systems near end-of-service, leaders will shift their focus to reinforcing their IT core — sometimes at the expense of experimental AI pilots.

Infrastructure modernization will move to the forefront, claiming a larger share of IT budgets as companies solidify the systems that enable AI. This isn't a retreat from innovation; it's a recalibration. The next wave of competitive advantage will come from combining advanced AI capabilities with secure, high-performing, and compliant foundations.

Workforce Readiness Will be a Leading Indicator of AI ROI

Simultaneously, the AI employee readiness crisis will evolve from a technical challenge to a cultural one. While 87% of business leaders believe AI will completely transform jobs within a year, only 31% say their workforce is ready to leverage it. This growing gap creates a "readiness paradox": one in which organizations are scaling technology faster than their people can absorb it.

As this paradox deepens, leaders will begin to recognize that the real determinant of transformation success isn't tooling, it's trust. In fact, 42% of leaders cite building employee trust as a major obstacle to AI adoption. Companies can no longer rely solely on hiring or deploying new technology to stay ahead.

Investment in change management, upskilling, and re-skilling will surge as leaders prioritize workforce readiness as the key lever for realizing AI ROI. The organizations that close the cultural gap, empowering employees to engage confidently with AI, will be the ones that capture its full potential.

Geo-Aligned Cloud Ecosystems Have Arrived

Cloud strategy will become as much about sovereignty as it is about scale. Enterprise leaders must navigate a complex web of regional data laws and compliance standards that shape where and how they deploy AI infrastructure.

Already, a majority of enterprises have adapted their cloud strategies in response to geopolitical pressures. In 2026, that number is expected to climb. Localized compliance frameworks will no longer be an exception; they'll be a core KPI measured against AI and cloud implementation strategies.

In this new era, enterprises will prioritize trusted geography over pure cost efficiency, and multinational organizations will shift toward multi-cloud-by-design architectures, striking a balance between performance and resilience. This evolution has direct implications for the nearly 70% of business leaders who feel unprepared to manage external risks such as regulatory uncertainty and market volatility. The same proportion reports that their current cloud environments evolved "by accident, not by design," and nearly all (95%) say they would redesign their cloud strategies if given the opportunity.

The difference between enterprises that use AI and those truly prepared for it will become clear in 2026. Readiness won't be measured by how fast organizations adopt new technologies, but by how strategically they align their infrastructure, governance, and people to use them effectively. Building resilience — technological, cultural, and operational — will define the next wave of transformation.

Dennis Perpetua is Global CTO of Digital Workplace Services & Experience Officer, VP, and Distinguished Engineer at Kyndryl

The Latest

For years, infrastructure teams have treated compute as a relatively stable input. Capacity was provisioned, costs were forecasted, and performance expectations were set based on the assumption that identical resources behaved identically. That mental model is starting to break down. AI infrastructure is no longer behaving like static cloud capacity. It is increasingly behaving like a market ...

Resilience can no longer be defined by how quickly an organization recovers from an incident or disruption. The effectiveness of any resilience strategy is dependent on its ability to anticipate change, operate under continuous stress, and adapt confidently amid uncertainty ...

Mobile users are less tolerant of app instability than ever before. According to a new report from Luciq, No Margin for Error: What Mobile Users Expect and What Mobile Leaders Must Deliver in 2026, even minor performance issues now result in immediate abandonment, lost purchases, and long-term brand impact ...

Artificial intelligence (AI) has become the dominant force shaping enterprise data strategies. Boards expect progress. Executives expect returns. And data leaders are under pressure to prove that their organizations are "AI-ready" ...

Agentic AI is a major buzzword for 2026. Many tech companies are making bold promises about this technology, but many aren't grounded in reality, at least not yet. This coming year will likely be shaped by reality checks for IT teams, and progress will only come from a focus on strong foundations and disciplined execution ...

AI systems are still prone to hallucinations and misjudgments ... To build the trust needed for adoption, AI must be paired with human-in-the-loop (HITL) oversight, or checkpoints where humans verify, guide, and decide what actions are taken. The balance between autonomy and accountability is what will allow AI to deliver on its promise without sacrificing human trust ...

More data center leaders are reducing their reliance on utility grids by investing in onsite power for rapidly scaling data centers, according to the Data Center Power Report from Bloom Energy ...

In MEAN TIME TO INSIGHT Episode 21, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses AI-driven NetOps ... 

Enterprise IT has become increasingly complex and fragmented. Organizations are juggling dozens — sometimes hundreds — of different tools for endpoint management, security, app delivery, and employee experience. Each one needs its own license, its own maintenance, and its own integration. The result is a patchwork of overlapping tools, data stuck in silos, security vulnerabilities, and IT teams are spending more time managing software than actually getting work done ...

2025 was the year everybody finally saw the cracks in the foundation. If you were running production workloads, you probably lived through at least one outage you could not explain to your executives without pulling up a diagram and a whiteboard ...