There’s a pattern showing up across companies of all sizes right now, and it’s worth pointing out: more AI tools, more cost, more complexity, yet with little real improvement in outcomes.

Here’s an example about what I’m talking about. A company has a core system of record already. This is typically an enterprise CRM handling marketing automation, sales, and customer experience management all in one, or a core sales CRM with separate marketing automation and CX tools bolted on from other vendors. In either configuration, on top of that existing stack, companies are now buying a wave of new AI tools and layering them on top, underneath, and around the systems they already have. But nothing gets removed. The old spend stays. The new AI spend gets added on top of it.

The logic behind buying these tools usually starts reasonably: AI is supposed to make things easier, faster, more productive. But that’s not what’s actually happening in practice. Costs go up. Complexity goes up, since now there are even more solutions to manage and coordinate. And the productivity gains and better outcomes that were supposed to justify the spend largely don’t materialize.

And the reason for that is, most of these tools don’t change what anyone is doing. They just give each person their own personal AI agent to automate the task they were already doing. That’s not the same as doing the task better. It’s the same work, done faster, whether or not that work was the right work to begin with or the right way to do it.

It’s like getting to the end of a cul-de-sac faster. Speed isn’t the problem being solved. If the destination was wrong, arriving there more quickly doesn’t help. Most AI bolt-ons speed up the existing process without ever asking whether the process itself should change. They don’t tell you to do something different, something more efficient, something that would actually help you sell more or serve customers better. They just make the current path faster, whatever that path happens to be.

We built our platform with the end goal in mind. We didn’t build our platform to simply manage tasks, we built it to help sales reps, marketing managers, and customer success personnel achieve better outcomes in their jobs. These critical roles don’t need yet another tool or yet another AI agent, they need a solution that helps them do their job better. Real productivity gains, not just faster execution of the same workflows. And instead of increasing costs to get there, the goal was to reduce it.

What we’re seeing from customers who move to our platform is not just fewer systems to manage. It’s less reliance on the pile of extra AI tools that would otherwise be layered on top to compensate for a fragmented stack, and lower overall cost as a result. Fewer systems, less AI sprawl, lower cost: all moving in the same direction at once.

None of this means we’re against AI. We use AI very deliberately inside the platform, in ways designed to protect what matters most for our customers, not just to make something faster or feel more automated to justify its existence. The bar we hold AI to is simple: if it doesn’t make someone meaningfully better at their job, then what’s the point of it? It doesn’t serve a purpose just because it’s new.

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