Every business is racing to work out how to use AI to increase their sales revenue- the pressure to buy some sort of sales AI tool is real. Most revenue leaders are approaching it in the same way: buy the tool, roll it out and wait for revenue to go through the roof.
It’s not working out like that. The problem is that buying AI and adopting AI are two very different things.
What does AI adoption in sales actually mean?
Buying a sales AI tool isn’t the same as adopting it. Adoption happens when salespeople use it consistently as part of their normal workflow and that use improves a clearly defined commercial outcome.
That distinction matters. Under pressure to move quickly on AI, it’s easy to focus on buying and deploying the technology rather than first deciding what commercial outcome you actually need it to improve.
Why does AI adoption in sales fail?
Buying a tool is relatively easy. Getting salespeople to use it isn’t. Realising ROI is harder still. So, what’s going wrong?
Four common mistakes account for most of the issues:
1. Built for leadership not salespeople.
Any new tool must earn its place in a seller’s day. They’ve got to see the benefit for them- not leadership. Most sales AI tools are designed to show leaders where their salespeople are messing up. They feel like surveillance rather than help. No wonder adoption is low.
2. Descriptive rather than prescriptive.
Most tools tell a seller what already happened: talk time, sentiment, call length. None of that helps someone sitting in a live conversation deciding what to say next. What a salesperson needs is the next best move, not another report.
3. Bolted onto the stack, not embedded in the workflow.
A tool that sits outside a seller’s daily workflow gets ignored. Yet another login, yet another dashboard to look at. No thanks.
4. Deployed without a proven methodology.
If AI is to provide a real competitive advantage, it needs to be underpinned by a best-in-class framework.
No framework = AI sales slop
Wrong framework = Getting worse, faster
Right framework = Exponential growth
What should revenue leaders prioritise instead?
Reverse those four failures and you get four buying criteria:
1. Prioritise a tool your salespeople will use
Your sellers will use it if it helps them progress a deal, not because a leader told them to.
2. Prioritise guidance that prescribes the next move rather than a dashboard that reports on the last one.
Salespeople want to be guided on what to do next. They don’t just want to be told what they did.
3. In the workflow
Prioritise a tool that lives inside your salespeople’s normal workflow, rather than one that adds another login salespeople will avoid.
4. Grounded in a proven methodology
Prioritise a tool underpinned by a proven methodology, one that truly gives your salespeople a competitive advantage and helps them win more deals.
Choose a tool based on those criteria and it’s way more likely your salespeople will adopt it and you’ll get clear, attributable ROI.
So, before you buy another sales AI tool, ask five questions:
1. Which commercial outcome are we asking this AI to improve?
2. Why would a salesperson choose to use it without being chased?
3. Does it guide the next move or only report what already happened?
4. Does it live inside the team’s normal workflow and use reliable data?
5. What proven methodology defines the advice it gives?
If you can’t answer those questions clearly before you buy, don’t expect the technology to solve them after you’ve deployed it.
They’re also the questions we asked ourselves when developing THEA, Flume’s AI Deal Coach. We started with the commercial outcome and what would genuinely help salespeople sell better, then built the AI around it.
Download The AI Adoption Gap: Why sales teams are buying AI and still losing the deals they should win.