It seems like every week there’s a new headline about how AI is revolutionizing the way we work… and the hype is absolutely real. In such a short period of time almost everyone can see that AI is no longer a futuristic dream. In both the personal and professional spheres, AI is recognized as a powerful tool that delivers real, measurable ROI today.

For IT leaders, AI is becoming an integral force. It’s now part of how they operate, influencing strategy and supporting every department. IT leaders have expressed AI as a means to:

They were much more likely to identify time-related metrics. 70% of IT leaders listed time saved on IT tasks as their ideal metric. This was followed by cost savings (52%) and percent reduction in help desk tickets (38%). Without much experience, these organizations look at efficiency gains rather than improved outputs and automation for how AI will help them best.

The results show a clear link between how much an organization embraces AI and the opportunities they see with it. More mature organizations see greater potential in AI’s capabilities beyond surface level productivity gains. The more they use it, the more likely they are to figure out new and interesting ways for AI to make an impact. They seek out ways for AI to lead with human guidance, versus the other way around.

It highlights how getting better at using AI isn’t just an exercise in saving time. It’s an investment that directly leads to better output, less stress for staff, and more efficient IT services.

This confidence is also changing the workforce.

Unlike the many headlines across 2025 that said AI will cut jobs, many IT leaders see AI as a positive force that will help the team grow in the long run. 50% of IT leaders expect AI to lead to the addition of new roles that need specialized skills. It’s not just bringing simple automation; the ways AI is expected to improve human work will require smart investment in new talent.

As we have seen, AI maturity influences this perspective greatly. AI mature organizations are 20% more likely to say AI will add new roles and skills compared to the whole. On the other end, organizations just starting their journey with AI are three times more likely to say it’ll have no impact. It’s much harder for them to see how AI will change their teams. Interestingly, those who are using AI, but only just developing their internal processes around it, are 44% more likely to say that AI will change our jobs rather than add to it.

The most persistent vulnerability associated to AI is the blinding speed of its adoption. 60% of IT professionals agree that AI is outpacing their organization’s ability to protect against threats. For the third year in a row that we’ve asked this question, that number remains nearly the same. This is a sombering trend that shows us we’re no closer to a solution than we were when ChatGPT made its public debut.

This feeling is the highest among AI mature organizations (66%). This indicates that those who are ahead in their adoption recognize the existential security gap most clearly.

Top Risks That Rapid AI Adoption Poses

Out of the top three most pressing AI-related threats, two of them are not novel attacks. They are failures in access control and inconsistent identity and access management (IAM).

Traditional software operates more predictably, responding directly to commands in a binary fashion. But AI (especially in the form of autonomous AI agents) introduces a new software behavior. It makes choices. On its own volition. It accomplishes multi-step tasks with multiple decision points along the way. Decisions we expect it to make.

This is why it’s so hard to integrate AI into more critical work. It’s no wonder that integrating AI into existing IT workflows is the number one gap challenging IT teams related to AI adoption (50%). Close on its heels is how to manage risk, compliance, and legal exposure (46%). The more ready an organization is for AI adoption, the more likely these challenges arise.

IT leaders are grappling with this right now. How do you incorporate these powerful, autonomous tools without losing control? Or visibility? How do you keep confidence in the integrity of the process?

For starters, we do. IT leaders recognize they play an outsized role leading their organization through rapid AI adoption. Over 60% of respondents feel they hold the final responsibility for setting AI usage policies.

In practice, however, the responsibility is shared… for better or worse. When asked which teams are primarily responsible for AI governance, 86% said IT. But 48% also said executive leadership and 28% said legal and compliance.

This disagreement over who makes the final call creates disruption and unclear expectations. Just over half of IT leaders shared that internal disagreements at least occasionally slow down AI adoption efforts. 14% state this happens very frequently.

The ripple effect of this internal slowdown is profound. When IT is forced to pause projects or navigate protracted debates, the delays do more than just push back a deadline. They dampen the overall effort to mature. Every stalled initiative limits the ability to refine processes. They make it hard to capture new efficiencies and build institutional knowledge around safe usage.

Ultimately, the greatest risk of internal friction is that it creates a negative feedback loop. The perceived difficulty of managing AI discourages further strategic investment, keeping IT perpetually on its back foot. They become unable to match the speed of the very technology they are attempting to control.

IT leaders know they need to close the major gaps caused by widespread AI use—external threats, internal struggles, and hidden shadow AI. Organizations are actively looking for solutions by focusing on specific ways to defend themselves. But these efforts often focus on the effects of the problem, not the root cause.

The first step is having a clear strategy for control. This means knowing the difference between Secure Use and Safe Use.

Secure Use

Secure use of AI is a reflection of its role as critical infrastructure. This means protecting the network from AI-enhanced threats (like adaptive malware) and making sure AI tools aren’t used as entry points for attacks. Secure use also considers the best practices inspired by Zero Trust principles that ensure access to this technology is as secure as possible.

Safe Use

Safe use focuses on the internal rules and governance best practices that help determine how people use the technology. It considers who is using it, for what purposes, and how. Safe use also concerns what data goes into an AI model. This ensures human users and AI agents use AI correctly to prevent data leaks and follow compliance rules.

This evolution becomes more apparent the more AI mature and ready you are. AI mature organizations are 26% more likely to believe this transition is essential compared to the whole. Those who rank in the Leading tier of AI Readiness were almost 40% more likely to share the same sentiment.

This revealing trend highlights how, in the case of fundamental IT strategy, perception meets reality. Unification is not just believed to be important; it’s part of AI readiness success.

The core challenge identified in this report is the fragmentation of the IT environment. Despite considerable progress, 86% of organizations rely on at least 4-10 different tools for core functions. This leads to complexity and critical security blind spots.

The more ready an organization is for AI (in the Leading tier), the more likely they are to report these challenges. This shows that companies that have made progress in managing AI are more aware of the pain that comes from scattered, fragmented IT management.

IT sprawl remains a persistent challenge:

While 62% of IT leaders believe they should be responsible for AI usage policies, that policy is useless without the ability to enforce it. Unification gives IT this power by providing the necessary visibility to monitor and log AI usage across all endpoints.

A critical area of control is limiting (or stopping) access to AI tools:

• 58% of respondents limit access through role-based measures.
• 19% rely on informal policies to limit who can use AI.

However, a concerning trend appears in the 21% of respondents who have no restrictions on which employees can access or deploy AI. Organizations that think they are AI mature are 33% more likely to admit they have no restrictions than less mature ones.

This should be a warning sign. By adopting AI without access controls, many of these mature organizations are now playing catch-up to reduce their risk of exposure.

This strong conviction is supported by executive leadership. Over 9 in 10 companies expect an increase in their IT budget for 2026.

This commitment is especially strong in security, as organizations most concerned about AI security are more likely to significantly increase their overall IT budget. For AI-specific projects, half of all organizations plan to spend between 11–25% of their 2026 IT budget.

Organizations that are AI mature and those that demonstrate AI readiness are the biggest benefactors here. They are almost 40% more likely to expect budgets to increase significantly, due to the trust they have built with their executive sponsors.

AI is not a destination; it’s the new engine of enterprise growth. By building an IT infrastructure that is unified, consolidated, and focused on strong access controls —while actively investing in staff training and alignment— IT leaders can move beyond simply adopting AI to truly operationalizing it—making it secure, scalable, and sustainable.