Stop Asking Where You Can Use AI. Ask This Instead.

Leadership teams everywhere are asking: Where should we use AI?

It's understandable. The technology is moving quickly, vendors are introducing new tools constantly, and organizations don't want to fall behind.

But that may be the wrong first question.

A better question is: Where is work unnecessarily expensive, slow, repetitive, or difficult in our organization?

Then ask whether AI can help.

Start with the work, not the technology

Imagine an enrollment team manually responding to hundreds of similar questions.

A continuing education division repeatedly creates customized corporate training proposals.

Staff manually move information between systems.

A research institute spends hours synthesizing information scattered across documents.

These aren't "AI problems." They're workflow problems.

AI simply creates new possibilities for solving them.

Build an AI opportunity map

Before purchasing another tool, identify recurring work across the organization and evaluate it across four dimensions:

• Volume: How often does this task occur?

• Time: How much staff capacity does it consume?

• Complexity: How difficult would it be to automate or augment?

• Risk: What would happen if AI produced an incorrect result?

High-volume, time-intensive, relatively standardized, lower-risk work often provides an excellent place to begin.

Prioritize measurable value

A successful AI initiative should improve something measurable.

• Hours saved.

• Response time.

• Cost per transaction.

• Conversion.

• Staff capacity.

• Revenue.

• Student experience.

  
  

Without an outcome, organizations risk accumulating impressive demonstrations that never meaningfully improve operations.

Pilot before scaling

Once high-potential opportunities are identified, choose one.

• Design a controlled pilot.

• Establish the baseline.

• Measure the result.

• Learn.

• Then decide whether to scale.

  
  

This is considerably less risky than attempting an institution-wide AI transformation before understanding where the technology creates actual value.

AI strategy is ultimately operating strategy

The organizations that benefit most from AI may not be the ones using the most tools.

They will be the ones that understand their work well enough to know where technology can meaningfully improve it.

Helios Education Lab helps education organizations identify high-value AI opportunities, redesign workflows, develop practical pilots, and connect technology investment to measurable organizational outcomes.

Before investing in another AI tool, identify the work worth transforming.