I’ve worked alongside sales teams for years, and I've watched this space transform. Not long ago, sales leaders invested significant time and effort manually crafting value propositions for every customer and opportunity. Today, AI is increasingly being adopted across the sales cycle, with the expectation that it will streamline and simplify much of that process. But despite how deeply AI has made its way into sales, in practice, it still falls short of delivering the expected business value.
While 8 out of 10 companies are using generative AI, more than 80% see no bottom-line impact. This gap, in many ways, reflects a deeper structural issue in the sales stack.
Sales has always been a fast-moving, execution-sensitive function, where ideas evolve in real time, inputs come from multiple stakeholders, and even minor details can make or break a deal. But the document layers, like proposals, pitch decks, and statements of work (SOWs), where the core sales work happens, often remain disconnected. When you deploy AI on top of these fragmented document workflows, instead of accelerating execution, it creates yet another step to toggle between.
The real problem here is integration, or the lack of it, which ends up diluting the impact of widespread AI adoption. When workflows remain siloed, even the most advanced tools only add noise. And that’s why, when you look at conversion rates, deal velocity, or win quality, the needle doesn’t move in the way you’d expect.
Value doesn’t come from having AI, but from how seamlessly it is woven into the entire system. At Adobe, we don’t view AI as an add-on, but a native part of the workflow. Because real impact comes from driving consistency and precision across the document ecosystem, which is the operational backbone of sales.
Let’s explore how it all comes together — but first, let’s understand where teams actually hit roadblocks.