The CLEAR Framework: A Practical Guide to AI-Powered Decision Making for HR Leaders
The conversation around AI in HR has shifted. We’re no longer debating whether to adopt these tools—we’re figuring out how to use them well. And that’s where many experienced leaders find themselves stuck.
After years of guiding senior HR executives through AI transformation, I’ve noticed a pattern. The challenge isn’t the technology itself. It’s knowing when to trust AI outputs, when to push back, and how to blend machine-generated insights with the judgment you’ve built over decades.
That’s why I developed the CLEAR framework—a systematic approach to evaluating AI recommendations that puts your experience at the center.
What CLEAR Stands For
C – Context Check: Does the AI have the complete picture? Large language models work with whatever information you provide. They don’t know your company culture, your CEO’s risk tolerance, or the political dynamics of your leadership team. Before accepting any recommendation, ask yourself: What context is missing here?
L – Logic Examination: Walk through the reasoning. AI can sound confident even when it’s completely wrong. Break down the recommendation step by step. Does each logical leap make sense? Are there assumptions baked in that don’t apply to your situation?
E – Experience Filter: This is where your expertise becomes indispensable. You’ve seen what actually works in organizations. You know which policies look great on paper but fail in practice. You understand the difference between what employees say they want and what drives real engagement. Run every AI suggestion through this filter.
A – Application Assessment: How will this play out in your specific environment? A recommendation that works beautifully at a tech startup might create chaos at a traditional manufacturing company. Consider your workforce demographics, your industry constraints, and your geographic spread. AI doesn’t automatically account for these variables.
R – Risk Review: What could go wrong? AI tends toward optimistic recommendations. It doesn’t naturally surface the legal landmines, the union implications, or the executive who will torpedo any initiative that wasn’t their idea. Your job is to stress-test every recommendation against real-world risks.
Putting CLEAR Into Practice
Here’s what this looks like in action. Say you’re using AI to help design a new performance management approach. The tool suggests eliminating annual reviews in favor of continuous feedback.
Running it through CLEAR:
Context Check — Does the AI know that your organization just underwent a complex restructuring and that managers are already overwhelmed? Probably not.
Logic Examination — The reasoning might be sound in general, but is it accounting for regulatory requirements in the countries where you operate?
Experience Filter — You’ve seen continuous feedback initiatives before. You know they require significant manager training to succeed. Has the AI factored in that investment?
Application Assessment — Your workforce includes manufacturing-floor employees who do not have regular computer access. How does continuous feedback work for them?
Risk Review — What happens to your legal documentation if a termination is challenged and you don’t have formal review records?
The AI recommendation isn’t wrong. It’s incomplete. Your expertise fills the gaps.
Why This Matters Now
We’re at a pivotal moment. Organizations are making significant decisions about AI adoption, and HR leaders are positioned to either lead that transformation thoughtfully or get swept along by the hype.
The leaders who thrive won’t be those who reject AI or uncritically accept its outputs. They’ll be the ones who understand that AI amplifies human judgment, not replaces it.
Your experience isn’t a liability in the age of AI. It’s precisely what makes you capable of using these tools well.
Lorraine Neal is the founder of Everstrong Leadership and Director of People & Culture at ATPCO. She helps senior HR executives leverage AI to amplify their expertise rather than compete with it. Her book, “The Experience Amplifier,” provides practical frameworks for experienced professionals navigating technological transformation.
