Three Things Your AI Agents Need to Work Across the Business

Agentic AI is a transformational technology.

But many people are getting swept up in the promise of agentic AI without fully thinking through how it should be implemented.

That’s creating an underappreciated risk. Organizations rushing to incorporate agents into their existing architecture may not be solving their workflow problems at all. Instead, they may just be spending a lot of money on a new tool that recreates their existing issues.

What’s really at stake

Once upon a time, having a website put a business ahead of the curve. Now, it’s a given. Agentic AI is approaching that same tipping point: Organizations deploying AI agents may have a competitive edge today, but as adoption accelerates, simply using them won’t be enough to stand out.

2026 McKinsey data showed that 40% of respondents from enterprise organizations reported scaling AI agents, up from 27% just last year.

The shift is happening quickly. KPMG’s June 2026 survey found that the share of organizations using multiple agents across workflows doubled from 9% to 18% in a single quarter.

Over the next few budget cycles, the leaders will begin to emerge. What separates them from the rest will be how effectively they embed AI agents across their enterprise. That means moving beyond isolated experiments to enterprise-wide transformation: identifying what works, establishing shared guardrails and coordinating handoffs before scaling across teams.

Agents built with clear guardrails and effective coordination will do more meaningful work across the business. Without that, agents will deliver limited value, and good ideas will fail to scale.

Beware the path of least resistance

Deploying agentic AI across every department creates a system that allows organizations to move seamlessly from a sales conversation to inventory data to a shipping delay to a support ticket.

But that won't happen automatically. If each department adopts AI independently by using its own tools and suppliers, those agents may end up operating in the same silos as the teams that built them.

It's an understandable outcome. When caught up in the pressure to adopt agentic AI, departments are apt to move forward on their own timelines, budgets and vendors. Building something that works for one team is the path of least resistance: it’s easier than figuring out how to make it work across the business.

When this happens, agents risk recreating the very fragmentation they’re meant to eliminate, leaving work stalled between departments.

What full capability looks like 

Consider a customer asking about a delayed order. An agent confined to support can pull up the case history and offer an apology. But an agent with access across the entire business can check the shipment, see the fulfillment delay, apply the right policy and resolve the issue in one interaction. By taking on mundane tasks, agents can let employees focus on building deeper human connections.  

The gap between the agent and the human has nothing to do with how smart the AI is. It's a matter of how much of the business it’s allowed to see. An agent that can only operate inside its own department is a new technology bound by the constraints of an old system. Getting over that hurdle looks like building a bridge between systems. 

The right architecture is your killer app

Building an enterprise-wide agent doesn’t mean spending more money or investing in more advanced agentic tools. It means putting the right foundations in place for an agent to operate across the business safely and coherently, using the systems you already have:

Each of these three things removes a barrier that keeps agentic AI from reaching its full potential: disconnected data, unclear accountability and broken handoffs between teams. Leave any one of them unresolved, and even the most capable agent will be limited. Address all three, and organizations can move beyond isolated pilots to make AI-powered enterprise automation part of everyday work, advancing their wider digital transformation.  

The choice is being made for you

Somewhere in your organization, a team is probably evaluating an AI agent. It may be a small purchase, a pilot or a vendor demo that went well.  

Individually, those decisions may seem minor. Together, they shape the architecture your organization will rely on. Without a plan for how those agents connect and operate across the business, that architecture will take shape by default. 

The organizations that will get the most from agentic AI won't necessarily be the ones that move first. They’ll be the ones that think beyond individual use cases and ask how agents can work together across the business before adoption gets ahead of them. 

It’s inevitable that agentic AI will be everywhere soon. Whether your organization allows agents to work to their full potential is still up to you.