Generative AI in sales: where it truly helps and where it gets in the way
Generative AI promises to revolutionize sales. We separate the uses where it truly adds value from those that only generate noise and robotic messages.
Generative AI has entered sales with the force of every trend: huge promises and half-baked applications. As with any tool, the key is not using it for its own sake, but knowing where it truly adds value and where, used badly, it does more harm than good.
Where it truly helps
Generative AI shines in drafting and synthesis tasks: preparing a first email draft, summarizing a call, researching an account faster, generating variants to test. It speeds up heavy work and frees rep time for what requires human judgment.
Where it gets in the way
The biggest risk is fake personalization: using AI to mass-send messages that look personal but are generic. Buyers detect the robotic tone, and the effect is worse than an honest, simple email. AI that replaces human judgment in the relationship usually subtracts.
- Good: drafts, summaries, research
- Good: variants to test copy
- Good: freeing time from mechanical tasks
- Bad: fake personalization at scale
- Bad: replacing human judgment in the conversation
The human-at-the-wheel rule
Generative AI performs when it assists a human who decides, not when it replaces them. A rep who uses AI to prepare and then adds their judgment gains time and quality. A process that lets AI converse alone loses what truly closes sales: the human connection.
AI and quality data
Generative AI is only as good as the context you give it. On qualified leads with real context — sector, need, signal — it produces relevant drafts. On poor data, it produces generic text with good grammar. Data quality remains the base, for AI too.