Use AI as a high-stakes negotiation simulator. Feed it context about your deal and the other party, then have it embody their persona and negotiate with you. Crucially, after each round, prompt it to break character and provide expert feedback on your performance and what you gave away for free.

Static playbooks quickly become outdated. Create a dynamic 'living playbook' by having an AI agent continuously synthesize information from recent projects. It can analyze Google Docs, Slack conversations, and call notes to distill the most current best practices, ensuring your team always uses the latest version.

About 15% of buyers now feed sales proposals and terms into AI models, asking them to "poke holes in it." Salespeople must anticipate this by preparing for more technical negotiations, shoring up their own proposals, and understanding how AI might critique their offers.

Instead of relying on ad-hoc calls to finance or other reps, LLMs can act as a central nervous system for sales. By analyzing past quotes and data, AI can instantly recommend the optimal deal structure for a new quote—maximizing commission for the rep and aligning with business goals, putting revenue back in motion.

Don't let valuable knowledge sit in static documents. Transform detailed playbooks, like a 50-page onboarding guide, into a collection of AI agents that actively execute specific steps. This ensures process adherence and automates routine tasks.

M&A leaders can feed diligence findings and past deal notes into an enterprise AI tool to quickly generate risk logs and identify key focus areas. This saves significant time that can be reinvested into crucial, high-touch stakeholder alignment and communication.

Instead of manual deal reviews with managers, sales reps can use custom AI agents trained on sales methodologies. This AI analyzes call recordings and CRM data to score a deal against frameworks like MEDPIC, identify qualification gaps, and recommend concrete actions to advance the opportunity, freeing up leadership time.

Instead of one-off prompts, feed your AI a persistent knowledge base with company data, sales playbooks, and territory info. This "intelligence layer" provides crucial context, enabling the AI to perform complex, tailored sales tasks effectively and consistently.

When exporting CRM data for AI analysis, include all deals, not just your current pipeline. This allows the AI to incorporate data from deals that were closed-lost months ago, identifying accounts that may be ready for a renewed conversation and preventing it from mistakenly suggesting active deals.