AI in Practice
From role design and data readiness to enterprise adoption: turning AI from a demo into a real operating system for work.
13 essaysCore questions in this topic
- Where should an enterprise begin adopting AI?
- How should teams define AI roles, prepare data, and preserve human accountability?
- How can individual use become reusable organizational capability?
A 90-Day Roadmap for Distributors to Put AI to Work
Distributors don't need to wait for perfect conditions to adopt AI, nor can they roll out every use case at once. This is a 90-day path from a single task to a role, a process, and scaled replication.
AI Is Not New Software — It Is How the Boss Reallocates Work
Many companies treat AI as just another piece of software without changing how work is allocated. The real transformation is deciding which tasks AI does first, and which judgments must remain with people.
Without These Business Tables, AI Can Only Talk in Platitudes
For AI to understand a real business, it must see verifiable sales, inventory, customer, and account data. Without a data foundation, its answers never rise above common sense.
AI Can Suggest, but Money, Goods, and Commitments Must Be Signed Off by a Human
AI can generate recommendations, but decisions involving funds, goods, credit, and external commitments must be confirmed by an accountable person, with a record kept.
How to Design a Job for AI: Building Your First AI Clerk
A reliable AI role needs fixed inputs, a defined process, a delivery format, boundaries of authority, and human sign-off — not just a job title handed to an AI.
I Can't Code — So How Did I Direct AI to Build ABI?
Not knowing how to code doesn't mean you can't lead an AI project. What matters is defining business objectives, dividing roles, setting acceptance criteria, and recognizing the gap between generating code and having a usable system.
Stop Memorizing Prompts: The Complete Five-Step Method for Delegating Work to AI
A prompt is not a magic spell. Only by spelling out the goal, the materials, the rules, the deliverable, and the acceptance criteria can you actually hand real work to AI.
How Brands Can Truly Help Distributors Adopt AI
Helping distributors adopt AI can't just mean issuing accounts and running training sessions — brands need to start from real operational problems, validate results with small pilots, and then scale.
Why I'm Urging You to Let AI Distill You, Right Now
For the first time, AI gives middle-aged professionals the chance to assetize their experience: turning judgment that exists only inside one person's body into a Skill that an organization can call, replicate, and compound.
Beyond Dashboards: How Regional Managers Can Run Markets with AI
How regional managers can use AI to move from reading dashboards to finding problems, tracking action, and running markets.
How Frontline Sales Managers Can Use AI Agents to Track Teams, Stores, and Results
How frontline sales managers can use AI agents to manage teams, in-store execution, and business results.
How FMCG Professionals Can Use AI Well, Part Two
Advanced ways for FMCG professionals to integrate AI into real workflows.
How FMCG Professionals Can Use AI Well
A practical foundation for how FMCG professionals can understand and use AI.