There’s a growing belief that AI will unlock efficiency across the enterprise. In reality, many organisations are discovering the opposite, AI is only as effective as the knowledge it draws from. And that’s where most companies fall short.AI(Artificial Intelligence) (Getty Images/iStockphoto)The issue isn’t a lack of information. Enterprises already possess vast amounts of it. The real challenge is that their most valuable knowledge, the expertise built over years by internal teams, is scattered, inconsistent, and often inaccessible when it matters most. Until that changes, AI will struggle to deliver meaningful value.As companies rush to embed AI into workflows, critical assumption is often overlooked, that the underlying knowledge is accurate and up to date. In practice, this is rarely true.Outdated documentation, conflicting guidelines, and fragmented sources can easily lead to incorrect outputs. A misrepresented certification can stall a deal. Incorrect privacy details can trigger compliance issues. Even routine customer support can go wrong when based on deprecated instructions. In these situations, the cost of being wrong far outweighs the benefit of being fast.This is why knowledge governance is becoming a priority. Organisations need clear ownership, regular validation, and strict version control to ensure that what their teams and AI systems rely on is trustworthy. Without this foundation, scaling AI simply means scaling risk.Another structural issue lies in how knowledge is held. In many organizations, expertise lives with individuals rather than systems. This creates bottlenecks. Teams depend on a handful of experts for answers, slowing down decision making and limiting scalability.The shift underway is toward distributing that expertise across the organization. Instead of knowledge being locked within specific roles or departments, it becomes part of a shared system that multiple teams can access and contribute to.This doesn’t just improve efficiency; it changes how organizations operate. Teams become more aligned, responses more consistent, and decision making more informed. At the same time, this shift requires discipline. Broad access cannot come at the cost of accuracy. Clear structures, defined responsibilities, and review mechanisms are essential to maintain quality as more contributors get involve.Many companies believe they already manage knowledge because they have repositories in place. But storing information is not the same as operationalising it. Static repositories tend to degrade over time. Content becomes outdated, context is lost, and trust erodes.What leading organisations are building instead are dynamic knowledge systems. These systems continuously evolve, with clear indicators of reliability, recency, and validation. They allow both humans and AI to quickly assess whether information can be trusted.More importantly, they enable insight generation. When knowledge flows across teams, patterns begin to emerge, recurring customer concerns, shifting compliance requirements, or new expectations around technology. These signals can directly shape strategy across functions. This is where knowledge starts to create real competitive advantage.The conversation around AI often focuses on tools and models. But the real differentiator lies elsewhere, in how well an organisation manages its own knowledge.Companies that treat knowledge as a structured, evolving system see tangible benefits. Risk decreases because decisions are based on reliable inputs. Teams move faster because they no longer depend on fragmented information. Customers receive clearer, more consistent experiences.Perhaps most importantly, internal experts are freed from repeatedly answering the same questions, allowing them to focus on higher value work. In this environment, AI stops being a source of uncertainty and becomes a force multiplier. The organisations that get this right won’t just adopt AI successfully; they’ll redefine how work gets done.(The views expressed are personal)This article is authored by Ganesh Shankar, chief executive officer and co-founder, Responsive.