AI as a Habit. Financial Value as a Goal.
Tobias Lütke, CEO of Shopify, recently shared a company-wide directive: “Reflexive AI usage is now a baseline expectation at Shopify.” It’s a powerful idea —but reflexive AI use alone won’t guarantee value.
At The Good Agents Company, we believe AI use should always deliver tangible financial value. It should make or save money by improving efficiency, reducing costs, increasing revenue, or unlocking new opportunities. And reflexive AI use — without reflection — risks wasting time, money, and trust.
Here’s how organizations can give Lütke’s directive a financial tweak.
A Reflex, but with ROI in Mind
Embedding AI into daily workflows is good practice. But not all AI usage creates value. When every employee is encouraged to “use AI reflexively,” it must come with a second directive:
👉 Be ready to explain the benefit.
- What task was improved?
- How much time was saved?
- Was quality or coverage increased?
- Would the task have been done at all without AI?
Capturing these stories, and connecting them to cost or revenue, helps turn reflexive use into shared learning. It also helps leaders justify further investment in AI.
Guardrails for Financially Fruitful AI Use
Without guidance, even well-intentioned teams can waste hours “playing with AI.” Here are three simple practices to ensure exploration stays on track:
1. Link to a Business Outcome
Before starting an AI experiment, ask:
- Will this help us do something faster, better, or cheaper?
- Will it reduce risk or unlock something we couldn’t do before?
2. Track Time and Outcome
Encourage teams to document:
- Time spent experimenting
- Task improvement (if any)
- Estimated value (e.g., time saved x hourly cost)
Over time, this builds an internal business case library for AI use.
3. Use a Simple Financial Viability Checklist
Here’s a trimmed-down version of our Financial Viability Checklist that teams can use:
✅ Does it save time or money?
✅ Does it reduce friction or improve decision quality?
✅ Can we measure the impact simply?
✅ Is it repeatable or scalable?
✅ Would the benefit justify the investment?
Make AI Reflexive — and Reflective
Reflexive AI use is a smart cultural shift. But to truly scale its value, teams need lightweight financial awareness and permission to reflect.
Empower your employees not just to use AI, but to think like product owners — always looking for ROI, always learning from what works (and what doesn’t).
That’s how you build a culture where AI agents become business agents — driving real outcomes, not just curiosity.