The promise of artificial intelligence (AI) to revolutionise the enterprise is no longer a futuristic concept; it is a present-day mandate. However, for many businesses, the initial “hype” phase has given way to a sobering reality: Despite significant investment, many organisations are struggling to realise measurable return on investment (ROI).
Although investment is surging, only 5% of companies are currently achieving AI value at scale, according to Boston Consulting Group’s 2025 “Widening AI Value Gap” report. The rest find themselves in “pilot purgatory.” This reflects McKinsey’s “Productivity J-Curve” theory, which suggests that in major technological shifts, productivity often stalls initially as organisations struggle to align new tech with legacy processes.
To bridge this gap, IT and business leaders must look beyond the software and address the fundamental operational and human barriers preventing AI from taking root.
Roadblocks to AI-enabled growth
Success in the AI era requires addressing a widening disconnect within the modern workplace:
- The technology gap: Currently 74% of employees report that their workplace technology does not meet their needs, according to HP’s 2025 “Work Relationship Index.” This “tech debt” acts as a drag on innovation, with McKinsey identifying that companies often pay a 10% to 20% “tax” on new projects just to address legacy infrastructure issues.
- The adoption and strategy divide: Whereas 45% of organisations report that AI is driving growth, there is a stark “fluency gap” and deep uncertainty regarding when and how to apply these tools in daily tasks. Only 21% of knowledge workers feel proficient in AI, compared to over 50% of IT decision-makers, according to HP’s 2025 “Work Relationship Index.” Demand for AI fluency, or the ability to use and manage AI tools, has grown sevenfold in just two years, faster than the demand for any other skill in U.S. job postings. Without frontline fluency, AI remains a boardroom priority rather than a workplace reality.
- The fulfillment crisis: The HP 2025 “Work Relationship Index” reveals that only 20% of knowledge workers have a healthy relationship with work. When employees feel overburdened, they view new technology as an additional demand rather than as an empowering tool.
- Redesigning tasks vs. workflows: A critical reason for stalled ROI is that many firms try to automate individual tasks rather than reimagining entire workflows. McKinsey estimates that about $2.9 trillion in economic value could be unlocked by 2030, but only if organisations redesign how people, agents, and robots work together.
Bridging the gap: A strategic approach to outcomes
To move from “AI noise” to actionable growth, the conversation must shift from a tech-centric focus to a human-centric outcome model. CIOs are now tasked with flattening the “J-curve” by adopting three pragmatic shifts:
1. Move from reactive support to strategic growth engine: Businesses need to advance beyond maintaining infrastructure to designing a future-proof IT organisation. By reducing “work about work,” which McKinsey estimates could free up 60% to 70% of knowledge workers’ time, IT becomes a primary driver of enterprise innovation.
2. Cultivate “skill partnerships” and AI fluency: Addressing the human element of the J-curve requires tackling the psychological barriers to adoption. Many knowledge workers fear that AI will replace them, a concern that often stems from seeing AI’s capabilities in broad, impersonal terms. To overcome this, IT and business leaders must communicate a vision where AI increases worker value. AI will not make most human skills obsolete, but it will change how those skills are used.
The focus should be on “skill partnerships” where machines handle routine data processing and humans focus on framing questions, interpreting results, and providing emotional intelligence. When employees see AI as a tool for individual development, they will become the engine of your digital transformation.
In addition, forward-thinking enterprises are investing in cross-generational mentoring. This enables Gen Z’s natural tech fluency to merge with the deep business acumen of seasoned professionals, creating a more resilient, adaptive workforce.
3. Prioritise “on-device” and edge efficiency: To avoid the complexity of massive infrastructure overhauls, leaders are looking for plug-and-play simplicity. By deploying hardware such as AI-powered PCs and workstations that handle AI inferencing locally, organisations can provide employees with instant access to AI tools while maintaining zero-trust security principles. This allows for the integration of AI-powered robots and agents at the edge, enabling them to perceive and act autonomously in real-time environments without waiting for the cloud.
The bottom line: Leading transformation with confidence
The future of work belongs to organisations that treat technology as a force multiplier for fulfillment and growth. As IT leaders evaluate their 2026 road map, they must prioritise solutions that remove friction and empower the individual.
The goal: create a work experience where technology acts as an invisible assistant, securing data, automating the mundane, and ensuring that your team is ready for whatever comes next. By aligning technology with the human experience, you can move past the hype and start realising the true ROI of the AI era.
About the author
Ritu Jyoti is currently the CEO of a stealth AI startup and an independent AI value strategist. She is a visionary seasoned executive, focused on building a future where businesses unlock an explosion of efficiency; disruptive innovation; and meaningful, strategic business outcomes with AI — responsibly. Previously she was the GM/GVP of AI and data at IDC, where she delivered actionable research and thought leadership for vendors, end users, and investors around the globe.