AI is in every sales stack now. What does it actually change about discovery, demos and the deals we run?
Two things changed and they pull in opposite directions. On the buyer's side, most of the evaluation now happens before you are in the conversation: they have asked an AI to compare you, read your docs, and arrived with a shortlist and an opinion. That kills generic discovery, because asking what keeps you up at night to someone who has already read your pricing page is insulting. Bring a point of view instead and spend the call testing it. On your side, AI genuinely absorbs the grunt work: research, note taking, follow ups, first pass qualification, and some teams have collapsed whole SDR functions into a handful of agents. What it does not do is carry a room, read a political map, or hold a price. Those are still the job, and they are the parts worth getting better at.
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4 resources, 1 India-specific, 4 link-checked.
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Jason Lemkin ran the experiment rather than predicting it: ten SDRs and AEs replaced by 20 agents and 1.2 humans. Worth it for the specifics of what the agents actually do well, and the honest account of the training investment it took.
The written version if you would rather skim than listen, and it draws the line most clearly: cadence based SDR work is going away fast, while the AE job holds for now because judgment and the room are still human. Also useful on what an AI-run motion actually requires to work.
Pulls the survey data into six concrete workflows (account research, outreach, content, conversation intelligence, CRM execution, forecasting) so you can pick where to start. The uncomfortable stat is the one to sit with: most AI deployments miss their expected commercial impact.
Built from a masterclass with Mohit Garg, former CRO at MindTickle, and written for cross-border companies selling from India, including how to structure SDR and AE teams for cost efficiency. Covers qualification, MEDDIC scoring, pipeline reviews and loss reviews in one place.