Prefer the highlights? Key takeaways and summary below.
TL;DR – Key Takeaways
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Many SMBs feel overwhelmed by AI’s endless tools and use cases; adoption fails without a holistic strategy that includes process analysis, data, skills, and change management.
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Shift from “prompt engineering” to context engineering—clear goals + the right data/context beats clever prompts.
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Start with role-based literacy training, then move to targeted, ROI-tied pilots (with humans-in-the-loop) before custom builds.
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Common mistake: buying big AI tools before diagnosing real problems (tool-first thinking vs. needs-first).
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Notable mindset shift: “AI isn’t hype—it’s happening now. Get on board fast.”
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Practical wins: draft quotes from CRM/product data, repurpose product copy across channels, automate expense categorization from receipts, and use RAG chatbots for support/product info.
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Executive takeaway: there’s no IBM-style “safe bet” anymore; leaders must own an AI roadmap that fits their business.
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Training content and processes must update continuously; use AI to help build and update training itself.
Meet the Guest
Jeremy Mayer is a computer scientist turned global training leader who built and led education programs at enterprise scale (including SAP). He co-founded WinWave AI, a consulting and training firm helping small and mid-sized businesses adopt generative AI responsibly. Jeremy is known for translating fast-moving AI capabilities into practical, team-ready systems that save time, reduce risk, and deliver measurable ROI.
Episode Summary
1) The Overwhelm Problem: “Too Many Choices, Not Enough Roadmap”
Industrial suppliers see an exponential rise in AI tools and use cases. That abundance creates risk: budgets, ROI, and security become murky when there’s no plan.
“There’s no perfect playbook for AI adoption—those training wheels are gone.”
Jeremy’s fix: start with a holistic assessment—processes, data sources, employee skills and comfort, and management buy-in—before picking any tools.
2) Start with Literacy—By Role
WinWave begins with role-based literacy so people know what AI actually is (and isn’t), what’s safe, and where it helps. Technical, ops, sales, and leadership each get tailored guidance.
Framework:
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Define business outcomes per role (hours saved, cycle time, accuracy).
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Map current workflows and data access.
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Identify low-risk, high-confidence pilot opportunities.
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Add human-in-the-loop checkpoints for quality and accountability.
3) Context > Clever Prompts
The industry term is shifting from prompt engineering to context engineering.
“It’s only as good as the context you provide—and the data it can see.”
Jeremy recommends RAG (Retrieval-Augmented Generation): connect models to your product sheets, SOPs, and pricing to get accurate, on-policy answers.
4) Practical Wins for Suppliers (Right Now)
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Sales ops: Auto-draft quote replies by pulling product, price, and inventory data; reps review and send.
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Marketing: Turn a single product description into site copy, an email paragraph, and a short blog in minutes.
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Finance: Extract and categorize line items from receipt images automatically.
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BI without BI: Ask natural-language questions over spreadsheets to find top products or regions.
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Support: Stand up a RAG chatbot for product info and common troubleshooting.
5) Avoid the Tool Trap
“Don’t buy the big shiny platform before you confirm the problem is real.”
Jeremy’s caution: large platforms (e.g., supply-chain suites) can be great—but only when they solve your bottlenecks. Diagnose first; pilot narrowly; prove ROI; then scale.
6) Build Momentum Internally
To win hearts and minds across technical and non-technical teams:
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Run short, role-specific workshops with real data and real tasks.
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Pick one or two pilots with measurable, near-term wins (2–6 weeks).
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Publish before/after metrics (hours saved, error rate, lead response time).
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Keep a running backlog of AI opportunities—revisit quarterly.
7) What Changes for Leaders
Leaders must own an AI operating rhythm: continuous learning, small experiments, and a data hygiene push.
“AI isn’t a side project. It’s part of your business strategy now.”
Keep humans in the loop, measure outcomes, and refresh training frequently—weekly if needed in fast-moving domains.
Notable Quotes
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“AI isn’t hype—it’s happening now. Get on board as fast as you can.”
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“There’s no ‘safe IBM choice’ anymore. You need a real adoption strategy.”
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“Stop chasing prompts—engineer the context and connect the right data.”
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“Start with literacy, then pilots with humans in the loop, then scale.”
Learn More / Get in Touch
Visit → https://10-twenty.com
Email → mark@10-twenty.com