There’s an old phrase from the early days of computing that we probably need to bring back. Garbage in, garbage out. Put bad information into a computer and you’ll get bad information back out. Somehow, in all the excitement around AI, we’ve forgotten that rule.
Everybody wants to know how AI will change sales. I think there’s a more important question: What are you going to feed it? AI needs data. It needs history. It needs information to analyze. And when I look at a lot of sales organizations, that foundation simply isn’t there.
For more than a decade, salespeople have been told to use a CRM. Record customer interactions. Track opportunities. Document what happened. And for more than a decade, a lot of them haven’t done it. Yet now we want AI to transform sales.
With what? If we haven’t collected the information, there isn’t anything meaningful for AI to amplify.
Part of the problem is that we love saying sales is an art. Heck yes, it is. Connecting with people, listening, asking the right questions and knowing when to push and when to shut up are human skills. But sales isn’t only an art. It’s also a science.
You’d never run finance or R&D without clear processes. I regularly ask salespeople to explain their sales process. Most can’t. Sometimes their companies can’t either. And that matters because AI is incredibly good at working with whatever we give it.
Give it good information and it can identify patterns, improve processes and make people more productive. Give it garbage and it can organize your garbage, analyze your garbage and confidently hand the garbage back to you.
We keep hearing that AI will make businesses faster. Faster at what? A good process? Fantastic. A bad process? Congratulations. You can now execute it faster.
That’s why the biggest AI opportunity for many sales organizations isn’t actually AI, at least not yet. It’s building the foundation AI needs. Define your sales process, get serious about your CRM, and then decide what information matters and consistently collect it. Then bring in AI.
Because AI is spectacular at amplification. It can amplify good data, good processes and human expertise. The technology may be new, but the rule isn’t. Garbage in still means garbage out.
