Start With the Work, Not the Tool
How businesses can leverage AI in operations and create effective AI strategies.
Original episode title: How to Use AI in Business Operations, w Rachel Woods, CEO of The AI Exchange
Guest
Rachel Woods
Founder, AI Exchange
Rachel Woods is founder and chief executive officer of The AI Exchange, where she teaches businesses how to use artificial intelligence in operations. Her approach emphasizes strategy, bespoke systems, experimentation, and practical workflows rather than tool-chasing, helping teams connect everyday productivity improvements with broader organizational change.
Shows why useful AI begins with mapping the work, defining success, inspecting failure, and refining the system—not shopping for a generic tool.
Profile →
Watch on YouTube ▶What this conversation is really about
Rachel Woods treats AI adoption as a work-design problem. The useful unit is not a model or subscription but a workflow: understand the steps, decide what success means, delegate a bounded portion, inspect failure, and refine. That frame offers an early version of the archive’s grow-versus-cut distinction. A bespoke system may remove repetitive work and move information across teams, but only if people retain enough context to notice when the system is wrong. The episode supplies a practical commercial framework, not independent evidence that every organization using it improves productivity.
From the conversation
The argument in focus
Rachel Woods
Founder, AI Exchange
Rachel Woods is founder and chief executive officer of The AI Exchange, where she teaches businesses how to use artificial intelligence in operations. Her approach emphasizes strategy, bespoke systems, experimentation, and practical workflows rather than tool-chasing, helping teams connect everyday productivity improvements with broader organizational change.
Shows why useful AI begins with mapping the work, defining success, inspecting failure, and refining the system—not shopping for a generic tool.
Profile →Evidence status
Vendor-reported case
A founder presents a commercial workflow framework and examples from direct practice. The mechanism is concrete; adoption, productivity, and community claims are not independently corroborated.
Boundary map
Where the system stops
- What the system handles
- Selected research, synthesis, drafting, routing, and repeatable steps inside a mapped workflow.
- What remains human
- Problem definition, success criteria, source judgment, exception handling, security boundaries, and responsibility for the finished work.
- What remains open
- Which bespoke workflows create durable organizational capacity rather than isolated individual acceleration?
Ideas worth carrying forward
- Map the workflow before selecting a tool.
- Define success and failure in terms a reviewer can inspect.
- Delegate bounded steps before delegating an outcome.
- Treat exceptions as design information, not inconvenient noise.
What this changes Monday
Choose one recurring workflow and write down its inputs, decisions, handoffs, failure costs, and current baseline. Mark the steps that are repetitive and reversible. Test AI on one of those steps, then review the misses with the people who know the work. Keep the question concrete: did the system improve this workflow without weakening source judgment, security, or accountability?
Original episode notes
Do you work at a job? Then you're probably involved in some kind of business operations, and there's a 99.999% chance that your job will be impacted by AI.
So how do you leverage AI to make your job easier? If you're a business leader, how do you create an AI strategy for your company or department? Where should you even begin?
I spoke with an expert in all of this, Rachel Woods, CEO of The AI Exchange, who's a consultant and educator for how businesses can embrace AI.
We get into it!
At a high level, Rachel shares the AI strategies and principles that businesses should think about, as opposed to just using the tools (4:40), how to think about the question of whether AI will take our jobs (11:00), some of her favorite AI tools for boosting productivity (14:00), the importance of creating what she calls "bespoke systems" (18:00), what AI is surpassingly good at... and surprisingly bad at (28:34), and advice for those in business just starting out with AI (39:40).
Bonus? At the end of the show, Rachel provides a promo-code for AI-Curious listeners to use for the educational courses at The AI Exchange.
Super practical episode, hope you enjoy.
You can find Rachel Woods at:
https://twitter.com/rachel_l_woods
The AI Exchange:
https://theaiexchange.com