The first enterprise AI mandate was simple: adopt. In the ensuing rush, enterprises have inadvertently built a digital Tower of Babel. Twelve months later, leaders are staring at a familiar mess: overlapping copilots, shadow keys, brittle automations, and invoices nobody can explain. This "AI sprawl" is now a direct threat to enterprise security and efficiency. Security teams can’t decipher what touched what. Finance can’t tie spend to outcomes. Operators are drowning in tabs. This isn’t a feature problem or a “pick a better LLM” problem. It’s a control-plane problem.

We believe the next mandate will be stricter: govern. The solution to this AI procurement mess is not another point solution, but a different architecture entirely. One emerging solution is the AI Agent Builder Platform, the potential end state for enterprise adoption: a centralized "studio" for an enterprise's entire AI workforce.

These platforms are not just tools; they are marketplaces. We don't expect a winner-takes-all market. Instead, enterprises will rely on a few core platforms to consolidate the number of vendors they engage with. Their power lies in offering a comprehensive set of solutions that caters to the entire organization:

• For the time-constrained professional who doesn't want to build: a marketplace to buy a vetted, pre-built agent for their specific workflow.

• For the non-technical power-user who wants to build: low-code and no-code frameworks to safely build and deploy agents that work precisely as desired.

• For the technical/IT team who must maintain a competitive edge: the full stack of tools to build unique, proprietary workflows, ensuring AI creates differentiation rather than parity.

This architecture functions as a unified control plane, transforming AI from a siloed feature into a governed, enterprise-wide system. Visually, this platform sits at the center of the enterprise:

This architecture represents the end state: a rational, secure, and observable AI ecosystem. To understand why this shift is urgent, we must first analyze the chaotic reality most enterprises face today.

The promise of enterprise software was to break down silos, yet the first wave of AI adoption achieved the exact opposite. Driven by departmental needs and a lack of central strategy, enterprises stumbled into a fragmented procurement process that created more complexity, not less. This chaotic approach results in what we call the "AI Frankenstack," a fragmented, department-led procurement process that creates more complexity than value.

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