Today, most companies are experimenting with AI. Many of them can point to demos that impressed, pilots that worked, and tools that saved time in narrow tasks. Far fewer can say AI has changed their business across functions, processes, and teams.
The difference is not the model. It is context: the ability for AI to understand how a business actually runs.
Much of today’s AI discussion centers on agents, along with models and benchmarks. Which model performs best? Which system completes the most tasks? Which interface feels most natural? These factors matter, but they do not solve the central enterprise challenge.
Companies run workflows that cut across teams, policies, approvals, authorizations, and data. They plan, source, produce, hire, pay, and serve through systems that carry real business consequences. AI only creates durable value at scale when it operates inside this reality.
Models generate answers. An agent can complete a task. But running a business requires something more. It requires an understanding of how work gets done, who is authorized to act, which rules apply, and how decisions connect across functions. Without that context, AI simply can’t deliver on its promise.
