Nirmaljeet's Blog

The explosion of AI products in the market has created both unprecedented opportunities and unexpected challenges for product managers and product leaders. From generative AI assistants to predictive analytics tools, new vendors are emerging daily—each promising to revolutionize how businesses operate.

But this abundance creates a risk: instead of driving AI product management strategy, product leaders can find themselves slipping into the role of vendor managers—evaluating RFPs, negotiating contracts, and piecing together third-party solutions.

And that’s not why we became product leaders.

The True Role of a Product Leader in the AI Era

The role of a product leader in AI is not to chase the latest tools but to orchestrate how technology, customer insight, and business strategy come together to deliver value. That means:

• Defining vision and strategy—imagining what should exist, not just adopting what’s available.
• Championing customer needs—focusing on real problems, not vendor feature lists.
• Turning AI technology into differentiation—combining external tools with internal data, workflows, and customer experience.
• Delivering measurable outcomes—ensuring adoption, ROI, and business impact, not just integration.

In short: AI strategy should drive vendor choices, not the other way around.

Why Vendor Management in AI Is a Trap

It’s easy to see why product managers fall into this trap. Vendors move fast, demos look impressive, and the promise of faster development and lower costs is compelling. But when the product role narrows to comparing vendors and signing contracts, companies lose the strategic value of AI product leadership.

Instead of leading innovation, product leaders risk becoming procurement officers.

How Product Leaders Can Avoid Becoming Vendor Managers

Here’s how to strike the balance between leveraging vendors and staying anchored in true AI product management leadership:

1. Anchor on AI Strategy, Not Tools

Every AI decision should start with the “why.” What customer problem are you solving? What business metric will it impact? Once the strategy is clear, evaluating AI vendors becomes a step in execution—not the centerpiece of your role.

2. Build AI Literacy Within Your Organization

Even if external vendors are part of the mix, invest in developing AI literacy across product, engineering, and design. Teams that understand the fundamentals of AI can make smarter build-vs-buy decisions and avoid over-reliance on outside providers.

3. Differentiate Through Unique Integration

Vendors provide capabilities, but true differentiation comes from how you apply them. Your proprietary data, workflows, and customer insights are the raw material for competitive advantage. No vendor can replicate that.

4. Stay Outcome-Driven

AI innovation isn’t about adopting the latest tool—it’s about results. Measure success in adoption, efficiency, and ROI. Hold yourself accountable for outcomes, not features.

The Future of AI Product Management

As AI matures, vendors will continue to play an important role. But the companies that win will be the ones where product leaders use AI to drive innovation, not just to plug in third-party features.

The essence of AI product leadership hasn’t changed: it’s about creating the future, not just managing what’s available.

The best product leaders won’t drown in the flood of AI tools. They’ll rise above it—using vendors strategically while staying true to their role as visionaries, strategists, and orchestrators of innovation.

Because at the end of the day, your company doesn’t need another vendor contract. It needs a product leader with vision.