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One of the biggest challenges with AI right now isn't learning how to use the tools. It's figuring out where they can actually create meaningful value.
Most Tech Ladies don't need another list of AI prompts or a rundown of the latest tools. They need a practical way to evaluate their work, identify opportunities for improvement, and determine which tasks are worth redesigning in the first place.
When you need to decide which workflow you can improve with AI, here is a five-point test to help you make your choice:
Value: Is there enough friction, delay, inconsistency, or rework to make redesign worthwhile?
Nature of the work: Does it involve interpretation, language, documents, comparison, classification, synthesis, or variable paths?
Context: Can you actually provide the information and rules the AI needs?
Evaluation: Can someone tell whether the output is good or bad?
Risk & authority: What happens when it gets something wrong, and can a human review it before anything consequential happens?
If the workflow fails several of these checks, the answer may not be “better prompting.” A better approach might be to narrow the use case—or don’t use AI to solve this problem.
The reality is that successful AI adoption often has less to do with the technology itself and more to do with choosing the right problems to solve. Organizations and individuals who see the strongest results tend to be thoughtful about where AI fits into existing workflows, where it doesn't, and what role humans should continue to play.
If you're interested in exploring this process more deeply, join us for our upcoming workshop, Find the Right AI Use Cases and Redesign Your Work Around Them. Together, we'll examine real workflows, evaluate whether they're a good fit for AI, and learn a practical framework for redesigning work around the strengths and limitations of today's tools.
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