Insights from Unisys Highlight the Shift from AI Hype to Measurable Business Impact

Unisys has released its Top IT Insights for 2026: Navigating the Future of Technology and Business report, identifying 10 trends expected to define the next era of enterprise technology. Based on extensive conversations with industry experts and business leaders, the report explores how organizations can move beyond experimentation to achieve repeatable, high-ROI AI deployments, adapt their workforce strategies, and strengthen cybersecurity in an increasingly complex threat landscape.

"In 2025 we saw a lot of AI hype, with conflicting reports about what the technology can deliver, leaving business leaders asking, 'what's next?' and 'when will we start seeing results?'," said Mike Thomson, CEO and President, Unisys. "In 2026, we are going to see more functional deployments of AI, a focus on quality rather than cost-cutting, and the emergence of AI applications that will deliver repeatable, ROI-driven results."

Unisys' Top 10 IT Insights for 2026

1. Focused AI Deployments Will Outpace Large-Scale Transformation Projects
   Rather than sweeping enterprise-wide initiatives, most AI investments will center on smaller, task-based deployments integrated into existing processes. These will use smaller, cleaner data sets, require lower upfront investment, simplify change management, and deliver faster, more predictable returns.
2. Three AI Applications Will Emerge as Repeatable, High-ROI Use Cases
   Enterprises are converging on three proven AI applications: employee and customer chatbots, AI coding agents, and AI-powered service assistants. These solutions are becoming packaged, measurable, and fast to deploy—reshaping how organizations evaluate and fund AI initiatives.
3. AI Investments Will Shift from Cost Reduction to Quality Improvement
   While early AI programs emphasized cost savings, organizations will increasingly measure success through quality gains—such as improved decision confidence, reduced variance, and better outcomes. Leaders expect these quality improvements to drive revenue growth and stronger margins.
4. Organizations will Train AI Models on Small, Task-Specific Data Sets Rather than Pursuing Scale
   The emphasis will move away from large language models trained on vast data sets toward smaller, specialist models trained on clean, domain-specific data. These models deliver higher accuracy, better performance, and lower operational costs.
5. Mass AI-Driven Layoffs Are Unlikely, but Entry-Level Coding Roles Will Decline
   Widespread job losses due to AI automation are not expected in 2026. Instead, organizations will redirect productivity gains toward modernization, backlog reduction, and improved customer experience. However, routine coding automation will continue to reduce demand for junior-level coding roles.
6. Post-Quantum Cryptography Will Become a Strategic Priority
   As quantum computing advances, attackers are already stockpiling encrypted data for future decryption. Organizations must begin preparing now by inventorying cryptographic assets, defining mitigation strategies, and planning phased transitions aligned with emerging standards.
7. AI Will Accelerate Both Cyberattacks and Cyber Defense
   Attackers will increasingly use AI for more sophisticated phishing, deepfakes, and voice spoofing. At the same time, defenders will deploy AI for enhanced anomaly detection, threat hunting via natural-language interfaces, and automated response. The focus will be on rapid containment, credible forensics, and resilient recovery.
8. Recovery Speed Will Matter More Than Breach Prevention
   With breaches becoming more likely, organizations will be judged on how quickly they can recover. Investments in offline backups, clean-room rebuilds, and pre-negotiated crisis-response processes will become essential—and a differentiator for customer trust, insurance, and regulatory confidence.
9. Data Sovereignty Will Drive the Rise of Regional and National Clouds
   Data sovereignty requirements are becoming standard, not niche. Governments and regulated industries will demand that data, encryption keys, and sometimes compute resources remain within national borders, accelerating the growth of regional and national cloud ecosystems. Enterprises that map their sovereignty requirements early and choose platforms with genuine local control will navigate this complexity more successfully than those treating it as a compliance checkbox.
10. Enterprises Will Optimize Workload Placement Instead of Pursuing Wholesale Cloud Migration
    The era of “lift-and-shift everything” is over. Most large enterprises now operate in hybrid environments and will focus on fit-for-purpose workload placement—using private clouds for predictable workloads, sovereign zones for regulated data, and selective rebalancing where appropriate.

Source: Unisys

Stay Connected with ISE Magazine 

Subscribe to our newsletters and magazine for the latest telecom insights, explore the current issue for in-depth features and strategies, and register for upcoming webinars to learn directly from industry leaders.