Why AI Agents Fell Short in 2025 – A Tale as Old as Time, Says Deloitte

The Rise and Challenges of AI Agents in 2025

The year 2025 was anticipated as the year of AI agents, with experts and industry leaders expecting a revolution in how people work and how productivity is achieved. However, according to Deloitte's latest Tech Trends report, these autonomous AI assistants did not take off as expected. The report highlights the obstacles that prevented widespread adoption and offers insights into overcoming them.

Every year, Deloitte releases its Tech Trends report, which examines the biggest trends of the past year to help inform enterprise leaders and workers about what to look out for in the upcoming year. This year’s report, the 17th edition, focused on AI, just like the previous two years. While investments in AI are at an all-time high, the report provided valuable insights on maximizing ROI through agentic strategies.

"Getting beyond the headlines to really focus on the so what, and now what, is the service that Tech Trends tries to do," said Bill Briggs, CTO at Deloitte. "The world's going to continue to advance and evolve, and you can't wait, or you will be left behind."

Failure of AI Agents to Take Off

The emergence of agentic AI technology had enterprise leaders excited about expanding their workforces and increasing productivity with AI assistants. Gartner predicted that by 2028, 15% of day-to-day work decisions would be made autonomously by agents, up from 0% in 2024. However, this momentum has not translated into widespread adoption.

Deloitte's 2025 Emerging Technology Trends study, which surveyed 500 US Tech Leaders, found that only 30% of organizations are exploring agentic options, with 38% piloting solutions and 14% having solutions ready to deploy. The number of organizations actively using the systems in production is even lower, at 11%.

Some companies are not yet close to deploying the technology, with 42% of organizations reporting they are still developing their agentic strategy roadmap and 35% having no strategy in place at all.

Obstacles Identified by the Report

This slow rate of deployment is noteworthy because there is potential for agentic AI to optimize business operations. However, many companies are not in a position to leverage the technology effectively.

"You have to have the investments in your core systems, enterprise software, legacy systems, SAS, to have services to consume and be able to actually get any kind of work done, because, at the end of the day, they're [AI agents] still calling the same order systems, pricing systems, finance systems, HR systems, behind the scenes, and most organizations haven't spent to have the hygiene to have them ready to participate," said Briggs.

Obstacles identified by the report include legacy enterprise systems that many organizations still rely on, which were not designed for agentic AI operations and cause bottlenecks in accessing systems, hindering the agents' ability to carry out actions and perform tasks.

Similarly, the data architectures of the data repositories, which feed information to the AI agents, are not organized in a way that enables the AI agents to consume it. Deloitte cited a 2025 survey it conducted that found 48% of organizations identified the searchability of data as a challenge to their AI automation strategy, and 47% cited the reusability of data as an obstacle.

Lastly, organizations often fail to create the proper governance and oversight mechanisms for the agentic systems to operate autonomously, as traditional IT governance doesn't account for AI agents' ability to make their own decisions.

"You've got this layer on top, which is the orchestration/agent ops. How do we instrument, measure, put controls, and thresholds, so if we got it right, the meter wouldn't be spinning out of control, kind of like we saw with the early days of cloud adoption," said Briggs.

Thinking About the Human Role

Deloitte identified a pattern among organizations with successful implementations of AI: being thoughtful about how agents are implemented. Business processes were created to fit human needs, not those of AI agents, so the shift to automation means rethinking existing business processes.

Rather than just "layer agents onto existing workflows," Deloitte said successful organizations "redesign processes" to take the best advantage of AI's agentic capabilities, leaning into their ability to tackle a high volume of tasks collaboratively without breaks.

The human element also involves ensuring that employees in the organization are properly trained. According to the report, 93% of AI spend still goes to technology, while only 7% goes to changing the culture and training, and learning.

Briggs said this disproportionality is "out of whack, because that's the piece where almost everything is going to fall down." Yet, he said the lack of focus on training is a "story as old as time" and a repeated pattern seen in many of the tech transformations witnessed during his 30 years in the industry.

Working with AI agents will also raise new questions, such as who will manage these AI agents and teams? What will an HR team for these agents look like?

Similarly, Microsoft's 2025 Work Trend Index Annual Report explored the concept of a Frontier Firm, or organizations with both AI agents and humans working in tandem, and found that humans will eventually lead teams of AI agents, necessitating HR processes for these assistants.

"We've got to rethink most of our HR process in a world where we're going to increasingly have people working with algorithms and agents and robots," said Briggs.