Ask executives how their organization is doing with automation, and the answer today is confident. Maybe too confident.
In the Unisys AI & Cloud Insights Report 2026, 94% of business leaders say they're effectively using automation to streamline and optimize their IT environment, up from 70% just a year ago. IT leaders report a similar jump, from 73% to 89%.
That's real progress. But the report, based on a global survey of 1,000 senior IT and business decision-makers, raises a harder question beneath the good news: Is that confidence translating into results? The data suggests it isn't, at least not consistently. And that gap, between capability and value, is quickly becoming the defining challenge of enterprise AI in 2026. Closing it starts with connecting the AI and cloud tools you already have. (That’s the approach behind Unisys Intelligence Accelerator, covered in more detail below.)
Confidence keeps rising while outcomes fall behind
Two numbers tell the story: 90% of organizations now say they have the architecture to support data-driven decision-making, while the share exceeding their operational efficiency goals fell from 80% to 65%, a 15-point decline.
In other words, organizations have never felt more equipped, and are, by their own measure, delivering less than they did a year ago. Part of the explanation is that the bar has moved. As digital transformation ROI used to get a multi-year window to prove itself, and with AI accelerating everything around it, leaders now expect results in a fraction of that time.
Agentic AI shows this tension most clearly: 75% of organizations say the technology is needed to manage the growing cloud and application complexity, and 93% plan to increase or hold steady on agentic AI spending. Yet only 23% have started scaling it across their business. Most are still in pilots, proofs of concept, and early experimentation, investing ahead of results rather than alongside them.
Capability doesn't become value on its own
The report points to a few recurring reasons organizations struggle to move from pilot to production.
- Talent and data: A lack of skilled talent (27%) and data management and integration challenges (26%) top executives’ lists of IT-related issues. That’s ahead of budget, security, or leadership support. Without people who can operationalize new tools and data that's trustworthy and connected, even strong infrastructure struggles to produce results on schedule.
- Fragmentation: Nearly a third of organizations name integration with existing systems as their top application strategy challenge, almost double the next most common barrier. That number climbs to 41% among business leaders. Meanwhile, 53% of organizations say they retain aspects of their original, unoptimized services within otherwise modernized hybrid environments, up from last year.
- Objectives: Many organizations are still optimizing for the wrong finish line. Technical modernization and enabling AI and automation top the list of application transformation goals, ahead of reducing costs or improving customer experience. Only 35% of executives believe they focus enough on business outcomes when evaluating IT spend. Modernizing the stack feels like progress. It only becomes valuable when it's tied to something the business can measure.
Security has become AI's enabler
Cybersecurity's role in the AI conversation is one area where 2026 differs from 2025. Breach rates have nearly tripled year over year, and 93% of organizations say cloud security capabilities significantly affect the level of autonomy they're willing to grant AI systems.
The intuitive read is that this slows things down. The report suggests the opposite: 96% of organizations now say their cloud security approach helps them adopt new technology faster than competitors, up from 60% last year. More than half say security measures may create near-term friction for agentic AI but are essential to scaling it safely over time. Rather than choosing between security and speed, organizations are treating governance as what makes speed sustainable.
Connection, rather than more tools, closes the gap
Across every finding, the organizations seeing the strongest results are getting more out of the technology they already have. They’re doing so by connecting cloud operations to application performance, data governance to AI outputs, and system alerts to the team responsible for responding.
Most AI tools aren’t built to solve that problem. Tools that monitor the cloud or flag security risks can each work well on their own. But if neither shares what it learns with the other, the organization remains no closer to achieving enterprise-wide outcomes.
This connective approach is exactly what the Unisys Intelligence Accelerator is built to provide. It’s an AI-enabled platform that connects agentic AI, automation, and governance with an organization's enterprise context, across cloud, applications, data, and cybersecurity, with people still setting the guardrails. Intelligence gained in one place informs decisions everywhere else. Rather than adding another disconnected tool to the pile, the accelerator helps organizations do more with what they've already built, which is exactly the opportunity the report's data points to.
Make the shift toward measurable AI value
Whether or not a connective platform is already part of your stack, closing the gap takes deliberate steps. Here's where to start:
- Redesign for agentic ways of working: Update operating models, workflows, and governance structures so they reflect how agentic AI operates instead of how teams operated before it existed.
- Invest in AI readiness: Build AI skills across leadership, governance, and infrastructure so that pilots can move into enterprise-wide deployment.
- Define the outcome before the investment: Prioritize converting cloud and AI spending into measurable business outcomes rather than simply expanding capability.
- Simplify before you scale: Modernize and streamline application estates and reduce integration complexity before adding more AI initiatives on top.
- Build in governance: Embed security, sovereignty, and governance controls directly into cloud and AI strategy from the start.
Explore the intelligence-at-scale advantage
This is only a portion of what the AI & Cloud Insights Report uncovers, including how leadership support for agentic AI varies by country and industry, where cloud investment is heading next, and what's driving the sharp rise in cybersecurity breaches.
Unisys Intelligence Accelerator connects AI, automation, and governance across your cloud, applications, data, and cybersecurity operations, helping organizations scale these capabilities through a connected, reusable intelligence platform.
Get the full report | Explore Unisys Intelligence Accelerator
