Where AI Fits
How do you figure out where AI will actually pay off before spending money?
Short answer
Start with the problem, not the tool. Before signing any AI contract, ask what specific problem it solves, how success will be measured, the real implementation cost, what happens to your data, and the exit strategy if it fails. The first question is the one that matters: define the problem, then evaluate goals, workflows, team behavior, security, and bottlenecks. Sometimes the answer is AI. Sometimes it is a simpler process fix.
"I'm getting pitched AI tools every day, and I have no idea how to evaluate them."
Our client is not alone. We see it in our inbox too.
Every day there's another AI assistant, automation platform, or "game-changing" tool promising massive productivity gains. Noise. So much NOISE.
And the biggest mistake companies make? Buying tools before clearly defining the problem they are trying to solve.
My friend Chris Baxter recently commented on one of my posts: "The baseline gap is real, then they discover half the finance team is using Claude for analysis with zero documentation and no security awareness."
That is happening everywhere right now.
Before signing another AI contract, ask these 5 questions:
- Does this solve a specific problem we have identified?
- How will success actually be measured?
- What is the real implementation cost?
- What happens to our data?
- What is the exit strategy if it fails?
Number 1 is the key.
Don't start with the tool. Start with the assessment. Evaluate goals, workflows, team behavior, security, and bottlenecks first.
Sometimes the answer is AI. Sometimes it is a simple process fix.
The companies seeing real ROI from AI are diagnosing before prescribing.
How are you evaluating AI vendors right now?
Related questions
What should you do before buying an AI tool? Define the specific problem you need to solve, then run an assessment of goals, workflows, team behavior, security, and bottlenecks. The tool decision comes after the diagnosis, not before.
What questions should you ask an AI vendor? Does this solve a problem we have already identified, how will success be measured, what is the real implementation cost, what happens to our data, and what is the exit strategy if it fails.
Is the answer always AI? No. Sometimes the right fix is a simpler process change. An honest assessment will tell you when AI is the answer and when it is not, before you spend.
More in the Executive AI Answer Center on getting started with AI and what an AI Opportunity Assessment includes.