Embedding the human factor into AI agent adoption

When implementing any kind of technology, the difference between offering employees training and supporting them in adoption is all too frequently misunderstood.

But the difference is a significant one.

Training is usually a time-limited, structured educational initiative to help people build technical competence and learn how a system works.

Adoption, on the other hand, is a continuous, long-term process by which employees use technology to change how they work in order to deliver more value.

Nowhere is this distinction more vital than in the emerging world of agentic AI.

To date, many organizations have been experimenting with the technology to automate discrete tasks, particularly in areas such as software engineering, customer support, and operations.

Over the next two years though, Gartner expects deployment to jump from the current 17 percent of businesses to more like 60 percent.

Their key aims in going down this route include automating complex multistep workflows, boosting operational efficiency, and maximizing productivity.

But despite the perceived value of agentic AI here, many organizations are currently struggling to create such value in real terms.

This includes generating a return on investment.

Identifying the value gap In fact, according to WalkMe's 'The State of Digital Adoption 2026' report, a huge 40 percent of all expenditure on digital transformation underperforms expectations, mainly due to user adoption challenges.

As the study, which is based on input from 3,750 respondents worldwide, says: "The technology does what it's supposed to do.

The adoption execution around it doesn't." As such, it found the average employee loses a full working day each week (7.9 hours) to "friction".

For example, they spend 1.34 hours per week re-entering the same information across multiple applications.