A potential pitfall with agentic AI? Settling for the easy wins.

AI agents are reshaping how work gets done. We recently surveyed 300 senior executives at US companies and found more than a third have broadly adopted the tool, another 27% have adopted it in a limited manner, and 17% have fully adopted it throughout the company. Those organisations are generating real value from AI agents through increased productivity, cost savings, faster decision-making and a better customer experience. 

A potential pitfall? Settling for too little. Broad adoption doesn’t necessarily mean deep impact. Many employees are using agentic features built into enterprise apps to speed up routine tasks such as updating records and answering questions. That brings a meaningful boost in productivity, but it stops well short of transformation. To generate a bigger impact, companies need to create multi-agent models—systems of AI agents working in concert to deliver tangible results. In this kind of setup, agents can take on complex, cross-functional workflows across functions, business units and even vendors. 

Getting there will require that companies address the biggest barrier preventing broader adoption of agentic AI: mindsets. Right now, people—including senior leaders—are holding AI agents back. When we look at the top challenges that survey respondents cited (34% each), they strike us mostly as safe excuses. Cybersecurity concerns? AI agents can be made secure. Cost? A well-designed implementation can pay for itself and then some within months. 

Here's how companies can start going further with agentic AI: 

• Focus on people.  AI agents are most beneficial when they help workers revisit—and even reimagine—their day-to-day work. Give workers the skills they need to build agentic AI into their daily routine and encourage them to use the technology to create more value.
• Orchestrate and integrate.  Using a few AI agents in isolation on existing applications is unlikely to move the needle. Leading companies adopt the tool across a range of business processes, using AI enterprise command centres to help connect different AI agents, coordinate how they work together and speed rollout across the company.
• Prioritise trust.  As AI agents advance, they’ll be doing more work and making more decisions autonomously. To drive stakeholder trust, build your AI agent strategy on a responsible AI foundation.