The Elusive ‘Context’ in AI: John Cutler Questions Vendor Narratives

In a recent LinkedIn post, John Cutler discusses the prevailing narrative around Artificial Intelligence (AI) adoption and challenges a key assumption often promoted by vendors. Cutler, a prominent voice in the enterprise technology space, questions the idea that simply accessing a “context layer” is the solution to the gap between AI usage and tangible business outcomes.

The core of Cutler’s critique lies in the vendor’s argument that while AI usage is increasing, actual business results are lagging. The proposed solution, according to many AI tool providers, is the availability of “context”—data and understanding that allows AI to be more effective. Cutler directly addresses this by stating:

“Usage is up! But outcomes aren’t! Missing link: CONTEXT (for sale)”

However, Cutler immediately casts doubt on the simplicity of this vendor-driven solution. He posits that “context” is not a static, readily available commodity that can be simply “tapped into” or purchased off the shelf from an AI tool provider. Instead, he argues that context is a dynamic, emergent property of human interaction and experience.

Challenging the “Context as a Product” Myth

John Cutler strongly refutes the notion that context is a pre-packaged element that AI vendors can provide. He highlights the potential for deception or misunderstanding when vendors present context as a distinct, purchasable feature of their tools. As Cutler points out:

“Guess what? Context isn’t just out there. Context is *created* and emerges through human interaction.”

This perspective suggests that true context is deeply embedded in the nuances of human communication, collaboration, and decision-making processes. It is not merely a data set but a living, evolving understanding built over time through engagement. Cutler’s argument implies that AI tools might be oversimplifying the problem by focusing on data access rather than the complex human elements that generate meaningful context.

The Importance of Human Interaction in AI Effectiveness

According to Cutler, the prevailing vendor narrative that positions “context” as a missing link that can be easily supplied by their technology overlooks the fundamental role of human input. He urges skepticism towards claims that suggest a simple “context layer” is the key to unlocking AI’s full potential.

“So when people talk about just tapping into some sort of mythical context layer (that just happens to live in their tool), be extremely suspect.”

This warning underscores Cutler’s view that genuine business impact from AI requires more than just data integration. It necessitates understanding how humans interact with information, make decisions, and collaborate to achieve goals. The “context” that drives successful outcomes, in Cutler’s analysis, is built through these human-centric processes, not simply extracted from a database or API.

Rethinking AI Implementation

John Cutler’s post serves as a critical examination of the current discourse surrounding AI implementation. By questioning the vendor-centric view of “context,” he encourages a deeper consideration of how AI truly integrates with human workflows and decision-making. His insights suggest that organizations looking to leverage AI effectively should focus not just on the technology itself, but on fostering the human interactions and collaborative environments where true context is generated and utilized.