Employee AI agent adoption: Maximizing gains while navigating challenges

While agentic AI definitely marks a turning point in human-computer interaction, moving from tool use to collaboration, the next step is integrating these agents and actually deriving value. At VentureBeat’s Transform 2025, Matthew Kropp, managing director and senior partner at BCG, offered a game plan for workflow evolution, employee adoption, and organizational change.

“The companies that are at the top of this curve — what we call future built, the ones that are most mature — are seeing substantial results: 1.5 times more revenue growth, 1.8 times higher shareholder value,” Kropp said. “There’s value here, but we’re early.”

Deploy, reshape, invent

To take advantage and create value with AI and with agents, a company needs to determine where to focus, using a deploy, reshape, invent framework. AI is already being deployed in every enterprise, and will have agents within the next few years. But if you give an employee a chatbot, you haven’t changed the way the work is done. You have to rethink the work, and reshape functions, departments, and workflows by identifying where human work can be automated.

“We’re advising companies right now to focus on your three or four big rocks. If you have a big customer support organization, you should apply AI in customer support. It has a huge impact. If you have a big engineering organization, you should employ tools like Windsurf to reshape the way that you do engineering, software development.”

Invention is still in the very early stage, but enterprises should be thinking about how to use AI’s ability to be creative, reason, and plan. Look at services and products, and how you interact with customers: can you reinvent that using those capabilities?”

For instance, makeup company L’Oreal launched a virtual beauty advisor to scale that exclusive service beyond their retail locations, reinventing the way they think about interacting with their customers at scale.

Thinking beyond basic use cases

It’s also critical to think about how AI changes your business. There’s been a lot of focus in the last couple of years on cost reduction by replacing workers, but that isn’t big-picture thinking. AI amplifies the employees you currently have, dramatically increasing their productivity.

“This is what we’re seeing in software development,” he said. “I don’t think we’ll see companies laying off their software developers. We’re going to see a massive explosion in the amount of capability and features that software companies are building.”

In a study BCG conducted with Harvard, Wharton, and MIT, they asked 750 knowledge workers to write a business and marketing plan, with and without generative AI. The participants using GPT4 executed 25% faster, completed 15% more tasks, and the quality of their output was 40% better. And when given an LLM, the bottom performers in the baseline did just as well as the top performers.

“It brought everyone’s performance up, which is very powerful, because in most organizations the new joiners are less effective than more experienced people,” he said. “It has the ability to increase time to proficiency.”

AI can also surpass human scale, even open up new applications that were not previously possible. For example, in the medical space, outcomes for patients are significantly improved with preoperative and postoperative follow-up from a nurse, but implementing this has been cost-prohibitive — until the advent of AI nurses that can take on that task for a large patient population.

Overcoming the biggest hurdle: Adoption

While these tools are fantastic, people aren’t using them. BCG tracked the adoption of GitHub Copilot and productivity metrics for an organization with about 10,000 software engineers. The top 5% engineers doubled in productivity in four months, while 60% showed zero improvement, because they just didn’t adopt the tool at all.

Why won’t humans adopt? There are three reasons. First is capability ignorance. The second, habit inertia. The third is identity threat, and that is the hardest to overcome. Developers are asking, “If this AI can write code for me then who am I? What’s my value?”

“This is going to be the real work of the next three to five years,” Kropp said. “It’s getting people to use the agents.”

Strategies overcoming reluctance

There are a few valuable ways to overcome these challenges. Naturally, getting the right tool is the first step, and integrating it with the way people work by training them explicitly. It’s also critical to measure and celebrate adoption for those employees actively using the tools so that everyone else starts to see they need to get on this bandwagon.

Another important step is ramping up scarcity — that means taking away resources so employees need to do more with less. At the same time, it’s essential to redesign work processes hand-in-hand with those employees who are on the front lines. Don’t just identify laborious processes where manual work can be automated — identify the parts where humans bring value.

“We minimize the toil and we maximize the joy,” Kropp said. “We’re left with a much more efficient process, a much more efficient company, a much more productive workforce, and jobs that people like to be in.”