This three-day programme is built for sales leaders, account executives and revenue operations teams who have to decide where AI belongs in their sales cycle. It is analytics-led and pipeline-first: participants work on their own accounts and their own pipeline data, finding and scoring prospects, building research-driven outreach, drafting proposals, forecasting with more than one method, and running the deal reviews and post-mortems that keep a forecast honest. Generative AI does that research, drafting and summarising well, and an AI agent goes one step further: given a goal, it reads the inbound lead, applies the scoring rules, drafts the follow-up and hands the result to a salesperson for approval. The decisions that follow sit with the sales leader: which work is handed over, under which rules, and on what evidence the result can be trusted in front of a prospect.
Day one establishes how generative AI works, takes every participant through structured prompting on their own accounts, and maps AI across the sales cycle before going deep on prospecting: the ideal customer profile, trigger events and buying signals, weighted lead scoring, list building with deep research modes, and account and competitor research. Day two covers the middle of the funnel: research-driven outreach and multi-touch cadences, proposal and business review drafting, pipeline forecasting with trend, weighted pipeline and regression methods, signal-based deal reviews and forecast post-mortems, and conversation intelligence for coaching. Day three moves from assistants to agents. Participants design and build an inbound lead triage and follow-up agent on a lead list carrying realistic ambiguity and planted edge cases, instrument it and read its traces, metrics and costs, then settle the CRM automation and governance rules under which an agent may work in front of prospects.
Every lab runs in a pre-configured cloud environment opened from a browser, with no software to install. Participants choose a visual build track or a coding-agent track, and each lab is verified against fixed acceptance criteria. Participants leave with a working lead triage agent, a sales prompt library, a weighted scoring model, an outreach cadence, an evidence pack of traces and metrics, an AI sales playbook for their team and a ninety-day rollout plan. The programme finishes on where the field is heading: agentic AI, where a sales agent is given a goal and researches, scores, drafts and updates the CRM under human supervision, with context engineering, loop and graph engineering, agentic retrieval-augmented generation, the Model Context Protocol and voice agents.