How Organizations Can Close AI Adoption Gaps and Maximize ROI

Worldwide AI spending is forecast to reach $2.52 trillion in 2026. But despite huge investment, there’s little evidence of AI ROI. According to PwC, only 30% of CEOs are confident about revenue growth in 2026, highlighting the ongoing uncertainty about AI’s productivity returns.

To start driving meaningful returns, leaders should ask themselves a series of straightforward questions: Do I currently know how AI tools are being used within the organization? Which tasks are the tools having the biggest impact on? And which teams are driving the highest returns using AI? 

For many leaders, this will expose a visibility gap. Some may have partial insight, others may be completely in the dark. Some employees may be using AI heavily, while others barely engage. One thing is for certain: A lack of clarity is not conducive to driving the productivity gains and ROI that AI promises.

Without the full picture, business leaders cannot see where value is being created, where adoption is stalling, or where employees need more support. Closing that visibility gap is the first step towards turning AI investment into measurable business value.

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Widespread use, uneven impact

ChatGPT reached more than 800 million weekly active users by October 2025, doubling from 400 million earlier in the year. Clearly, adoption is not the issue, but usage alone doesn’t create value. Our benchmark data shows that there are significant differences in how AI is being used and its productivity impact across teams. On average, regular Generative AI users save around 3 hours and 47 minutes per week, while the top 10% of Generative AI users are saving nearly 18 hours a week.

Our findings also reveal that the impact of Generative AI varies widely by the tools employees use. CoPilot users save 2 hours and 45 minutes per week, whilst ChatGPT users save more than double, with an average of 5 hours and 46 minutes per week. The same pattern appears across different types of work. Recent analysis shows that AI can reduce task completion time by 80-90% in legal and management work, 75-85% in knowledge and administrative work, and 50-60% in technical and hardware-related tasks.

These differences in how employees use AI and the resulting productivity gains point to a deeper issue. When adoption is uneven, only a small group of power users capture real value while others fall behind. For AI to deliver meaningful impact, organizations need consistent adoption across teams. That requires giving leaders clear visibility into how AI is being used and where gaps exist so firms can remove bottlenecks for employees or provide targeted training to improve usage.

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What’s measured can be improved

To drive AI adoption widely across organizations, employees need practical, in-the-moment guidance on which tools to use, for which tasks, and how to use them effectively. However, organizations can’t deliver this level of support without a clear view of how AI is currently being adopted across the workplace. To get that visibility, businesses need a robust Digital Employee Experience (DEX) strategy that brings AI usage data, experience metrics, and sentiment insights into a single view.

With insight into the end user experience, organizations can build a clear picture of how staff are actually using AI, from simple tasks like summarizing emails to complex research that saves hours of work. That visibility enables organizations to identify gaps in AI usage, which they can address. For example, targeted guidance or training can show less confident AI users how to adopt more complex workflows, helping staff get the most value from the tools available.

This level of insight also helps organizations identify the barriers that slow AI adoption, such as HR teams hesitating to use AI until internal data-sharing policies are clarified, departments unsure on which AI tools are most suitable for their specific tasks, or just a fear of using AI. These challenges often stem from a limited understanding of where AI can deliver the most value rather than a lack of willingness to adopt. By addressing these obstacles directly, organizations can empower all employees to adopt AI, leading to a more consistent and impactful use across the business.

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When AI investment turns into value

AI has the potential to transform productivity, but its benefits are only realized when adoption is consistent and effective across the organization. Uneven use leaves value concentrated in a small group of users, while gaps and barriers prevent the broader workforce from contributing to ROI. By gaining clear visibility into how AI is used, businesses can provide support where it’s needed most and enable employees to use AI more effectively. The result is a workforce where all employees can unlock the full potential of AI, turning inconsistent AI adoption into true ROI.