Strategic AI investment in digital workplace services significantly improves business performance
If you’re not integrating AI deeply into your digital workplace strategy, you’re leaving efficiency and revenue gains on the table. The latest Unisys Digital Workplace Insights Report 2025 makes that abundantly clear. Companies that leaned into AI, not just dabbling, but embedding it into how work gets done, are twice as likely to beat their revenue targets. That’s not a marginal gain. That’s competitive dominance.
These AI-forward companies, or “Productivity Leaders,” aren’t just automating tasks. They’re overhauling how decisions get made, how disruptions are handled, how people interact with systems. AI enhances workflows, cuts waste, and reacts faster than any legacy model. The result? Stronger business performance across every meaningful metric, revenue, efficiency, resilience, and return on investment.
Smart AI deployment isn’t about status or marketing. It’s foundational. Your systems become smarter, your people get more done, and your business scales without scaling complexity. That’s how you win, by operating dramatically better than the competition.
You don’t need to bet the farm on bleeding-edge AI. But you do need to commit. Strategic AI use is no longer about experimentation, it’s operational infrastructure. For C-suite leaders, that means AI should be baked into your core roadmap, not just added to it. If your IT and executive teams aren’t speaking the same language on this, revenue will suffer. Your competitors already figured that out.
AI-driven innovation and cybersecurity are significantly stronger among AI-forward organizations
Innovation without security is wasted effort. You ship faster but you leak data. You create more, but you expose more risk. Companies leading with AI aren’t making that tradeoff. They’re accelerating both. That’s rare and worth paying attention to.
AI-forward organizations are unlocking new product and service innovation while also closing the gap on cybersecurity risks. It’s not just about using AI to create things; it’s about using it to defend what you build. And the results are clear: 91% of Productivity Leaders reported improved innovation, and 98% said they leveled up their cybersecurity posture.
That matters because innovation only scales when your infrastructure can keep up. AI is allowing these companies to reduce vulnerabilities while increasing velocity. In practical terms, that allows them to take bigger swings on bold ideas, without paying for it in security incidents or downtime.
For business leaders, this is about leverage. AI isn’t just automating line-level tasks, it’s reinventing organizational momentum. But it only works if it’s tightly integrated. If your innovation teams are operating in a silo and your cyber teams are playing defense alone, you’re going to fail. The C-suite must demand alignment between security, innovation, and AI strategy. AI won’t do it for you. You have to steer it.
Generative AI enables faster issue resolution and better business continuity
Generative AI isn’t just interesting tech, it’s fixing problems before most companies even notice them. That’s what makes it essential. In high-performing organizations, AI now manages the flow of IT support with more speed and less friction than any manual process can match.
Leaders identified in the Unisys 2025 report are running AI-powered systems 24/7 that automatically triage IT issues, categorize requests, prioritize urgent tickets, and resolve them faster. These aren’t small-time fixes. These systems prevent downtime from snowballing into full-blown outages, which protects revenue and keeps teams productive.
And because AI doesn’t sleep, or wait for office hours, it responds to incidents in real time across global operations. That’s a major shift in business continuity strategy. You’re no longer managing disruption. You’re staying ahead of it.
For executives managing global operations, AI’s ability to reduce downtime should be on your list of critical infrastructure. Relying on human-only systems to handle outages and incident tracking slows everything down. Integrating generative AI into support functions isn’t a cost center, it reduces IT effort and gives your business more uptime. When looking at AI ROI, this is one of the most defensible use cases. And one of the fastest to show results.
Prioritizing employee experience amplifies the value of AI in the workplace
If your employees don’t like the digital tools you give them, that’s your fault, and it’s costing you. AI works best when it serves a workforce that’s been properly understood. That means designing with people in mind, not just infrastructure. Companies leading the AI race get that.
The most successful organizations are using AI not only to improve performance, but to make work simpler for employees. They’re six times more likely to use experience-level agreements that focus on human outcomes, speed, clarity, satisfaction, rather than just uptime or ticket closure rates. That alone shifts how tools are built and maintained.
What makes this effective is feedback. The best companies are actively collecting and acting on employee responses to IT changes. They know what teams need, and they deliver it. As a result, they’re outperforming their peers across satisfaction, engagement, and retention, and that leads directly to better output.
For the C-suite, this is about reducing friction in day-to-day work. If AI tools don’t align with employee needs, performance won’t improve, and adoption will stall. You’ll waste budget and desert strategic goals. Investing in tools is only half the job, understanding how people use them is the rest. Leadership has to push for that connection early and often.
AI investment requires coordinated business and IT leadership alignment
You can delegate tasks. You can’t delegate alignment. AI is too strategic to be owned by just one team. If business and IT leaders aren’t moving in the same direction, your results won’t scale, no matter how much you invest.
Unisys data makes this clear. IT leaders tend to focus on operational performance, compliance, and return on investment. Business leaders focus more on end-user productivity and consistency across remote and in-office environments. Both priorities matter. But if they’re not aligned, you get fragmentation, AI that performs well technically but doesn’t move the business forward.
The companies seeing the greatest value from AI are syncing their priorities. They’re connecting employee experience with infrastructure performance. They’re integrating IT improvements directly with operational performance. In those environments, AI doesn’t sit in a silo. It supports strategy across departments.
The CEO, CIO, and CHRO must treat AI as a shared priority. IT can’t operate in isolation, and business leadership can’t afford to ignore implementation details. If the strategy is top-down but the execution is disconnected, your AI investment will underperform. Build the stack, but lead with clarity, across functions.
Perceptions of AI’s role differ across organizational roles
When IT and business leaders don’t see AI the same way, decisions slow down and benefits stall. The Unisys data points to a clear disconnect, especially when it comes to how effective AI tools are across remote and in-office settings, or how critical generative AI is to operations.
IT leaders are more confident. They report higher satisfaction with digital workplace tools and see AI as essential to reducing support-related delays. Meanwhile, many business leaders aren’t seeing that performance level reflected in real-world workflows. That difference in perception matters, because it shapes priorities, funding, and how progress is measured.
If leadership teams can’t agree on AI’s value or impact, they won’t act fast enough. That gap keeps organizations stuck in evaluation mode when they should be scaling proven systems.
Execs need to normalize continuous data-sharing between business and IT teams. Alignment means clarity: about tool performance, about strategic goals, and about implementation challenges. Misalignment might not show up in the boardroom immediately, but it will show up in missed targets, slow adoption, and employee complaints.
Key takeaways for leaders
- Strategic AI deployment boosts business performance: Companies that aggressively invest in AI-led workplace systems are twice as likely to exceed revenue targets. Leaders should prioritize AI integration across processes to drive ROI, resilience, and growth.
- AI enhances both innovation and cybersecurity: Organizations leveraging AI show sharply higher innovation output and stronger digital defenses. To stay competitive, C-suites must treat AI as a dual force accelerating product development and minimizing operational risk.
- Generative AI improves speed and continuity: Continuous-use AI tools reduce IT downtime and support complexity while restoring operations faster. Executives should invest in generative AI for incident response to protect productivity and minimize disruption.
- Employee-first AI design increases satisfaction and retention: Firms aligning AI tools with employee needs outpace peers in engagement and talent retention. Leaders should embed employee feedback into digital workplace strategies to maximize adoption and staff performance.
- Business and IT leaders must align AI priorities: Misalignment limits effectiveness of AI strategies across the organization. Decision-makers must ensure joint ownership of AI direction to translate investment into measurable business impact.
- Internal perceptions of AI vary widely: Business and IT leaders disagree on AI tool performance and value, risking fragmented execution. C-suites should close these perception gaps with shared metrics and communication to accelerate trust and momentum.
