Most AI training shows people a demo on somebody else’s data. Teams nod along, go back to their desks, and nothing changes. This workshop runs on your material instead.

Participants bring real documents, campaigns, reports, and proposals, and build working prompts and workflows during the session with Pam in the room. Pam Didner trains teams on Claude and Microsoft 365 Copilot, and she covers what each one is good at, where they fall down, and which of your recurring tasks are ready to hand over today. By the end, every person has built something they will use on Monday, not a folder of notes they will never open. Available as a half day or full day, and customized to the tools your organization has already licensed.

Key Takeaways:

• Working prompts and workflows built on your team’s own documents during the session
• A clear read on which of your recurring tasks AI handles well and which it does not
• A shared vocabulary so the team can keep building after Pam leaves

Your most experienced people carry decades of knowledge that lives nowhere but their heads. Some of them are retiring soon. AI can hold that knowledge, but only if someone feeds it properly, and that is the work this session does.

Participants bring their real material, the pricing logic, the customer history, the process nobody wrote down, and spend the session structuring it so AI can actually use it. Pam Didner walks the group through what to capture, how to format it for accurate answers, who owns keeping it current, and where this goes wrong. Teams leave with something working, built on their own knowledge, rather than a plan to build one later. Half day minimum, full day if the group is building for more than one function.

Key Takeaways:

• A method for pulling undocumented knowledge out of your most experienced people
• Knowledge structured during the session so AI returns accurate, usable answers
• An ownership and maintenance plan so it stays accurate past month one

Sales teams tune out AI training fast, usually because it was written for marketers and handed to them without changes. This session is built for the sales floor.

Pam Didner works through the parts of the sales day where AI earns its place: account and prospect research, call preparation, follow-up that does not sound automated, and the pipeline hygiene nobody wants to do. Reps build and test the workflows during the session using their own accounts and their own CRM data. Pam spent 20 years in sales enablement inside large B2B organizations, so the session respects how sales people actually spend their time and skips the parts that sound good in a deck and fail in the field.

Key Takeaways:

• Research and call-prep workflows reps build and test during the session
• Follow-up and outreach that uses AI without sounding like it did
• The handful of sales tasks where AI creates more work than it saves, and why

Marketing planning usually comes down to one meeting where someone has to explain the number. This full-day workshop gets you ready for that meeting.

Participants work through market and competitive research, tie initiatives to business goals, and build a budget that prioritizes the work most likely to produce pipeline. Pam Didner shows where AI takes weeks out of the process, from pulling competitive intelligence to pressure-testing spending assumptions to drafting the executive-facing version of the plan, and she is equally clear about the judgment calls AI cannot make for you. Participants leave with a plan document in progress, not a blank template.

Key Takeaways:

• A budget framework that ties every line to a business goal and a pipeline target
• Where AI compresses the research and drafting work, and where it should stay out
• How to balance short-term wins against long-term growth when the budget is tight

Most messaging frameworks die the first time a sales rep ignores them. This workshop builds one that holds.

Participants develop positioning, define real differentiation rather than the kind every competitor also claims, and translate product features into language a buyer recognizes. Pam Didner shows how to use AI to test messaging against different buyer personas before it goes live, to see how competitors are actually positioning themselves right now, and to generate enough variations that the team can compare options instead of arguing about one. Teams leave with a framework and, more importantly, with sales having been in the room while it was built.

Key Takeaways:

• A positioning and messaging framework built with sales in the room, not handed to them after
• How to test messaging against buyer personas with AI before it reaches a live campaign
• Differentiation language that holds up when a competitor claims the same thing

Most marketing teams say they support sales. Sales teams mostly say they cannot find anything useful. This session closes that gap.

Pam Didner, who built sales enablement programs inside Intel and other large B2B organizations, works through what sales actually needs, what marketing keeps producing instead, and how to tell the difference. Participants map content to real deal stages, fix the handoff points where leads go quiet, and build the account-level personalization that AI now makes possible without adding headcount. The session ends with both teams looking at the same definition of a qualified lead, which is usually the first time that has happened.

Key Takeaways:

• A content map tied to real deal stages rather than a generic funnel
• How to personalize at account level with AI, without hiring for it
• Shared lead definitions and handoff rules both teams sign off on in the room