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Every company is racing to deploy AI agents. But last week, an article in HBR made an uncomfortable argument: most of them will end up making the same decisions. The researchers called it the "agentic convergence trap." When companies deploy AI agents trained on the same public data, they reach the same conclusions. Here's how it looks in go-to-market: Every sales agent on the market ingests the same firmographics, the same intent signals, the same scraped web data. So when your prospecting agent and your competitor's prospecting agent both decide to reach out to the same buyers, with the same message, in the same week, that's not a coincidence. That's the convergence trap happening in your pipeline. Three things can break the trap: 1. Protect your customer data. The deals, conversations, tickets, and patterns that live in your CRM and nowhere else on the internet. 2. Leverage your company's context. Not the generic goals AI systems default to when they have no better signal. 3. Keep humans in the loop. Human judgment over the decisions that matter most, the ones where context, relationships, and nuance still win. Every competitor will have an agent. They'll all be fast. Most will be capable. Many will run on the same public data and arrive at the same answers. In the AI era, the agent itself isn’t the moat. The context it runs on is. And it’s why we’re building Growth Context at the heart of our agentic customer platform. (Check out the full HBR article in the comments.)

I recently spoke to 400+ Growth leaders at a partner event. From the stage, I asked three questions. The answers show exactly where many businesses are stuck right now in AI adoption. How many of you use AI every day? Every hand went up. No hesitation. How many of you are more productive because of it? 90% of hands. Instantly. How many of you are seeing AI move your key business metrics? 10%. Maybe. That gap is the defining challenge for leaders right now. Their teams are fluent in AI. Individuals are doing more. And yet the metrics that matter most: leads, revenue, retention, growth haven't moved significantly. At HubSpot , we've seen tens of thousands of our customers cross the chasm from individual AI impact to institutional AI impact and drive growth. Here's what works: Give your team AI tools with shared context: the same data, the same processes, the same view of the customer. Siloed agents create siloed impact. When it comes to AI, context is queen. Pick workflows with clear outcomes, and reimagine them with AI. Just because a workflow can be improved with AI, doesn’t mean it’ll translate into business value. Choose wisely. Focus on a few areas. Set targets, apply constraints, and encourage rapid experimentation. Fortune favors the focused. I’d love to hear from you: How are you shifting from seeing individual AI impact to driving institutional AI impact?

With agentic workflows grounded in real agreement context and integrations with leading legal AI platforms, Docusign IAM transforms agreements from static documents into strategic assets that drive faster decisions.

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