Before you can say AI made your team more efficient, you need to know how efficient the team was before it. Jonathan Green talks with Shannon Ryan, who works in technology strategy at Veritas Automata, about why so many companies roll out AI without a baseline, how clients handed a 20% efficiency target end up asking for token counts instead of outcomes, and why an AI readiness check starts with your data and your manual processes. They also cover what a rushed AI rollout does to the people in the room, and what cutting junior roles does to the pipeline of future leaders.
Key Takeaways:
- Measure before you automate. Jonathan's rule is to spend a month timing each task and what it costs, implement the AI, then measure again. He says almost nobody does it.
- Clients are being told to be 20% more efficient, and the first ask is often "measure tokens." Shannon's teams found there were no dashboards for tokens, let alone hourly efficiency.
- Start with your data and your manual processes. Shannon's readiness assessments begin by asking whether a company still runs manual processes and where its data actually lives.
- Master a process by hand before you accelerate it. Automating a process you do not yet understand is like building the engine while the plane is taking off.
- Keep the people in the plan. A strategy built only around efficiency and fear of job loss creates resistance, while adoption reduces it, and cutting junior roles today removes the people who would become tomorrow's leaders.
Notable Quotes:
"It is where's your baseline of your data, and are you actually ready for AI?" — Shannon Ryan
"But how are we actually gonna get the humans to adopt it? And when there's adoption, then it reduces the fear and resistance of a new tool." — Shannon Ryan
Connect with Shannon Ryan:
LinkedIn: https://www.linkedin.com/in/shannoncryan
Company: https://veritasautomata.com
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