CIO are set to spend ambitiously on AI this year, IDC projecting worldwide spending on technology to support AI strategies will reach $337 billion in 2025. But ask most organizations and their business leaders what they’re getting back from it, and the room goes quiet.
In fact, 54% of board members admit they can’t put a dollar amount on their AI investments. That number should be a concern for every CIO – not because AI is failing, but because the way we’re measuring its value is.
Many organizations are approaching AI with the wrong mindset and without clarity around what success looks like, how to measure it, and how to embed AI in a way that serves both the business and the people who power it.
The issue isn’t the tech. It’s the mindset, the metrics and the missing support.
Why AI ROI Is So Hard to Measure
AI is often expected to produce immediate and concrete financial results. Nearly half of AI decision-makers say their organizations expect ROI on AI investments within one to three years, while another 44% expect a longer timeframe – even these timelines reflect a limited perspective.
When CIOs treat AI like a quick-win cost saver, rather than a long-term strategic enabler, the disconnect between investment and measurable value only grows. The real value of AI often reveals itself over time, in improved efficiency, enhanced decision-making, and better customer experiences.
Yet despite this, many organizations continue to race into AI adoption, convinced they’re getting ahead of the curve. But without clearly defining what success looks like without setting KPIs or aligning cross-functional goals. It’s an assumption that AI will pay off without putting the necessary foundations in place.
And when success isn’t defined, frustration becomes inevitable. Executives start questioning the return, employees are left navigating poorly implemented technologies and the AI no matter how advanced, fails to deliver on its promise. Not because it can’t, but because it was never properly integrated from the start.
Rethinking What ‘Value’ Means
To unlock real value from AI, CIOs must redefine what ROI means and step away from just looking at ROI in terms of what costs were saved. Instead, looking at metrics from the employees’ point of view is equally as important, and in many ways even more important.
That starts by involving employees early in the process. Gather feedback from past initiatives and use it to shape future strategy. When CIOs shift the focus from “How much did we save?” to more relevant questions like:
• Has this reduced digital friction?
• Has his made our employees more efficient?
• Are our employees working more productively and delivering better customer outcomes?
These aren’t just questions to briefly ask, they’re metrics in their own right and can be tied to monetary value further down the line.
Importantly, these benefits aren’t confined to IT, they span across the business. Which means the KPIs used to track success can’t live in silos either. Partnering with HR, Operations, and other departments ensures your measurement strategy reflects the full impact of AI across the organization.
By setting clear, cross-functional KPIs before implementation, everyone understands the goals, the benefits, and their role in making AI succeed. And that’s when the technology really starts to deliver.
The Role of Support
Support, training, and change management are often treated as afterthoughts, but they’re central to the adoption to that drives the ROI from the investment. It’s not just employees recognizing the need for support, organizations equally understand what needs to be done with 96% of organizations agree they need to enhance their digital adoption support to help employees adapt to AI.
With 91% expecting an increase in digital friction as AI transformation accelerates, business leaders must prioritize employee enablement from the start. That means involving employees when defining project metrics, and ensuring they have the tools, guidance, and communication needed to adapt.
Successful implementation hinges on human alignment. That means clear communication and ongoing support to aid the longevity of the project.
Human-Centered Outcomes
With 75% of companies not yet seeing ROI from their AI investments, it’s clear that something needs to change.
CIOs need a mindset shift away from chasing ROI in the traditional sense and instead start looking at the impact it’s deriving. Reframe the question from ‘Did this save us money’ to ‘is it helping our people do their jobs better?’.
When AI empowers employees rather than burdening them, the return becomes clear – streamlined workflows, a more productive workforce, and stronger business outcomes.
The future of AI and the value derived from these initiatives is in how we implement it, how we measure it, and most importantly how we support our employees to use it.
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Download The Science of Productivity Reports - part 1, 'Transformation: Driving Adoption, Productivity, and Change in the AI Era', free of charge. And part 2, 'The Experience Silo: HR, IT, and the Digital Workplace'.