Introducing AI in sales: where do I start?

Not with the tool. Introducing AI in sales starts with the customer: how do they research, compare and decide today — and how is AI changing that behaviour? Only from that answer does it follow what AI should achieve in your own sales organisation, and in what order.

The usual sequence runs the other way round, and that's why it fails. A provider shows a demo, the tool gets bought, then use cases are sought. This creates activity, but no impact. The viable sequence has four steps.

First step: understand the customer. According to Forrester, 94 per cent of B2B buyers use AI in the buying process — they arrive at first meetings with ready-made comparisons and business cases. Before you automate internally, it must be clear what this shift means for winning customers. Otherwise AI optimises a sales organisation for customers who no longer exist in that form.

Second step: examine your own system. AI amplifies what's already there. Clean processes become faster; data chaos becomes chaos faster. The honest stock-take — processes, CRM data quality, roles, governance — decides whether AI becomes a lever or another failed project.

Third step: a few clearly chosen use cases. Not ten pilots, but two or three cases with measurable benefit and an existing data foundation. Show impact there. The rest comes afterwards.

Fourth step: enablement instead of training. A strategy doesn't yet change daily work, and an AI licence even less so. Behavioural change needs leadership: modelling it, demanding it, following up — in workshops and in day-to-day business. The goal isn't knowledge. The goal is the ability to act.

What this sequence achieves: it ensures that technology serves a sales model — rather than the sales model adapting to a demo. And it makes the implementation manageable, because at every step there's a decision, not a hope.