From AI-curious to a working sales assistant and a leadership roadmap — in two workshops
How a traditional meat manufacturer went from scattered, unmanaged AI use to a working custom-built sales assistant and a leadership team aligned on one committed next step.
The client & the starting point
A food manufacturer — a traditional business making deli products the same way for decades — came to me in a position I see constantly: their people were already using AI, but nobody had decided how.
When we mapped it, four different AI tools were already running inside the business, each with a different risk profile and no shared rules. The sales team was spending hours turning purchased market data into customer presentations by hand. And leadership had the question every owner in a traditional industry has right now: is AI something we manage intentionally, or something that happens to us by accident?
We answered it with two workshops — one for the people doing the work, one for the people making the decisions.
Workshop 1 — the sales & marketing team
This was a full-day, hands-on fundamentals session for the sales and marketing team. Not slides about what AI might do someday — an actual build.
The centerpiece: a working AI sales and marketing assistant, a custom GPT the team can use to draft outreach, social posts, newsletters, and sales copy in a consistent voice, plus image and video generation prompts for their visual content.
And here's the lesson underneath, the one I want every business owner to take away: the AI isn't the secret. The four documents you feed it are.
A brand voice & messaging guide — how you sound, what you never say
Ideal customer profiles — who you're actually talking to, and what they care about
Offers & pricing — what you sell and how you describe it
Your best-performing emails & posts — proof of what already works
I built a complete four-document set for a sample business so the team could see exactly what "good" looks like at every step, then handed over the full build method and templates so they could load their own material. A generic chatbot gives generic output. The same tool, fed those four documents, becomes an assistant that writes like your business — because it's working from your business.
Workshop 2 — the leadership session
Sixty minutes with the leadership team. Seven segments, one decision at the end.
Why AI, why now — the numbers behind the shift, and why waiting compounds against you
A real-world case from their own industry — a peer meat manufacturer that connected existing production data to AI and reported a 10–12% gross profit gain on those lines, with ROI in three months against a twelve-month estimate
Data security & governance — before anyone pastes company information into a public AI tool, a simple traffic-light classification: which data types can go into free tools, paid tools, or only their own protected environment. Printable, distributable, usable the same day
AI in their existing Microsoft ecosystem — building on the platform they already own, where their data stays in their own tenant, instead of adding risk with unvetted tools
An opportunity map for their business — concrete AI opportunities across all four departments (sales, production, quality/regulatory, accounting), based on what their own team told us. One quick win was agreed in the room
A three-phase adoption roadmap — demonstrate value, build the strategy, then build and scale. Each phase earns the next; leadership always controls the decision to continue
The session ended the way every leadership session should: not with vague enthusiasm, but with concrete next steps on the table — a Phase 1 proposal within the week and a process-review session scheduled with a smaller leadership group. One committed decision, not a hundred intentions.
Why this approach works
Most corporate AI training is theory. People nod, go back to their desks, and nothing changes.
I run it the other way around. The working team leaves with a system they built and can use the next morning — plus the method to make it better. The leadership team leaves with a governance framework, a map of where AI fits their specific business, and a decision. Hands on the tools for the doers; clarity and control for the deciders.
That combination is what turns "AI curious" into actual capability. Nobody has to imagine what AI could do for the business — they've already watched it work on their business.
What this means for your business
If a traditional meat manufacturer can put AI to work in two sessions — a working assistant for the team, a roadmap and one committed decision for leadership — your business can. That's the point.
Book a free consultation — and let's map where AI fits your business. BONUS: Provincial funding is now available for AI training for your employees, and I guide you through the process from start to finish. Don't wait, it will not be available forever!
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