Why AI Governance Matters More Than the AI Model
Every B2B Commerce platform has AI agents now. They demo well, they are getting easier to build, and a single agent pointed at one job can do genuinely useful work.
Explore insights that help enterprise teams solve complex challenges,
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Every B2B Commerce platform has AI agents now. They demo well, they are getting easier to build, and a single agent pointed at one job can do genuinely useful work.

Agentic commerce stopped being a demo in late 2025. OpenAI launched Buy it in ChatGPT on the Agentic Commerce Protocol (ACP) it built with Stripe; Google announced the Universal Commerce Protocol (UCP) at NRF in January 2026; and McKinsey began estimating that agents could mediate three to five trillion dollars of consumer commerce by 2030. The checkout moment, the part where an agent turns a chosen product into a completed purchase, went from concept to shipping standard in about two quarters.

The most useful thing I heard at Applied AI for Distributors wasn't about a model. It was six words.

Many transformation projects run into the same ghost story. Requirement workshops produce a clean, confident picture of how the system should work on the new platform.

For most enterprises, search starts as a feature and ends up as foundational infrastructure. That shift happens gradually—until the scale of a product catalog, the complexity of a data model, or the expectations of an AI-powered experience make it impossible to ignore. When an organization reaches that inflection point, the decisions made about architecture, schema design, and cloud infrastructure either unlock future capability or create compounding technical debt.

Before a stunt double sprints across the rooftop and leaps the gap to the building across, the jump has already happened several times. Every variable measured: the run-up, the gap, the wind, the weight of the performer, the give of the landing.

Project managers who also serve as business analysts face an increasingly complex challenge: balancing strategic oversight with detailed requirements analysis while meeting accelerated delivery expectations. This dual responsibility creates operational strain that traditional approaches struggle to address effectively.

Every few weeks there’s a new headline declaring that AI is going to replace developers, kill agile, and make project managers obsolete. I’ve been in delivery long enough to recognize a panic cycle when I see one.

Technology can scale communication. Only people can build trust.

Four words still printed on millions of B2B product pages are quietly destroying revenue:

Having spent decades in private equity and technology, we believe most firms are still thinking about AI too narrowly. The current conversation often assumes the highest strategic leverage comes from implementing AI at the general partner level—building dashboards, centralized monitoring systems, portfolio-wide intelligence layers, and synthetic operating capabilities sitting above the portfolio.

In the world of distribution, and especially in the HVAC distribution space, isn't it your goal to "become the fastest and most reliable HVAC distributor in our region while improving margins"? That is easy to say but difficult to execute for a variety of reasons. I will break down the top five areas in your distribution business and how to greatly improve your ability to execute.