AI

The Practical AI Adoption Playbook for Businesses

AI TeamJanuary 8, 20259 min read

Every business knows it should be "doing AI" — but most struggle to move past pilots and demos. Here's the framework we use with clients to ship AI that actually pays for itself.

Start with the Workflow, Not the Model

The biggest AI wins rarely come from a flashy chatbot on your homepage. They come from automating high-volume, repetitive decisions:

  • Document processing: Invoices, contracts, support tickets
  • Triage and routing: Sending the right work to the right person
  • Drafting: First versions of replies, reports, and content
  • Forecasting: Demand, churn, inventory, delivery times

Map your team's week. Anywhere a person reads, decides, and acts on structured-ish information is an AI candidate.

Score Opportunities by ROI, Not Novelty

For each candidate workflow, estimate:

  1. Volume: How many times per week does this happen?
  2. Time saved: Minutes saved per occurrence
  3. Error cost: What does a mistake cost today?
  4. Data readiness: Is the input digital and accessible?

A boring workflow with high volume and clean data beats an exciting one with neither.

Ship a Thin Slice First

Your first AI feature should take weeks, not quarters:

  • Pick one workflow, one team, one metric
  • Use a hosted LLM with retrieval over your own data (RAG) before training anything custom
  • Keep a human in the loop for every decision at first
  • Measure acceptance rate — how often the human keeps the AI's output

Build Evaluation Before You Scale

The teams that succeed with AI treat evaluation as a product feature:

  • Collect golden examples of correct outputs
  • Run every model or prompt change against them
  • Track quality in production, not just in testing
  • Define clear escalation paths when the AI is unsure

Mind the Guardrails

Responsible AI isn't optional — it's what makes AI deployable:

  • Keep sensitive data out of prompts unless contractually covered
  • Log every AI decision for auditability
  • Give users a way to report bad outputs
  • Be transparent about where AI is involved

AI adoption is a compounding game. Each shipped workflow generates the data, trust, and skills that make the next one faster.