I recently read a post by the founder of ClickUp, warning that data wars are coming—and that enterprise AI is at risk of being boxed in by vendor politics. One line stuck with me:
“The better answer is convergence: unifying workflows, data, and systems so AI can operate with full context.”
It’s easy to skim past that word—convergence—as just another tech buzzword. But it’s not. It’s a quiet revolution in how we think about intelligence, ownership, and control.
The Slack Example: When Doors Close
Salesforce recently limited how much of Slack’s real-time communication AI tools can access. It’s not just a technical change—it’s a signal.
When vendors restrict access to the very conversations that shape decisions, they’re not just protecting IP. They’re controlling context.
And without context, AI becomes:
- a chatbot with no memory
- a strategist with no map
- a brilliant mind trapped in a soundproof room
This decision likely reflects a different strategic lens:
- One that prioritizes brand clarity, ethical boundaries, and enterprise trust
- One that curates context intentionally, rather than opening every door by default
But even principled restrictions shape the terrain. They define what AI can see—and what it can’t. And in a world where context is intelligence, those boundaries matter.
What Convergence Really Means
Convergence isn’t just about integration. It’s about giving AI the full picture:
- Unified workflows, so it sees how decisions unfold
- Shared data, so it understands nuance
- Open systems, so it can move across tools
It’s not a feature—it’s a philosophy. And it’s the difference between AI that reacts and AI that leads.
Convergence isn’t just about what AI can do—it’s about what we’re willing to let it understand.