Embedding the human factor into AI agent adoption

Adopting AI agents into organizations requires more than just training employees and is a continuous process of utilizing technology to change work methods and deliver greater value. Gartner expects AI deployment to rise from 17% to around 60% over the next two years, driven by the potential to automate complex workflows, increase efficiency, and maximize productivity.

However, many companies currently struggle to generate a return on investment from agentic AI despite its perceived value. A WalkMe report found that 40% of digital transformation expenditures underperform expectations due to user adoption challenges. Employees lose a full working day each week to friction, such as re-entering information, finding workarounds, and lacking guidance on using tools. The study also highlights that employees spend time reworking AI prompts and waiting for faulty tools to be fixed.

Ofir Hatsor, WalkMe's Senior Vice President of Sales for Europe, Middle East, and Africa, attributes much of this friction to the complex and highly regulated environment in which enterprises operate. Organizations often find it difficult to change their day-to-day operations, even when doing so could create real value for the business.

A major challenge is the visibility gap, where executives believe their organizations use an average of 35 applications when the actual number is 661, a 1,789% difference. This makes it difficult to optimize workflows, govern AI tools, and measure productivity. Shadow AI is another issue, with 45% of workers using unapproved AI tools in the past month, often sharing confidential company data. This lack of official control creates risks for companies, particularly in terms of data privacy and governance.

Additionally, organizations face challenges in implementing agentic AI versus its real-world benefits, as many proposed financial gains are based on assumptions that may not hold true. AI tokens also pose a problem, as organizations are often unaware of the number of tokens consumed or their associated costs, which can become very expensive. The rapid pace of AI change can be challenging for employees who have less access to new tools than their leaders, and many feel uncertain about the future.