You Deployed AI. What Result Changed?
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A lot of companies have some version of the same objective:
We need to deploy AI.
That sounds a little like me saying, “I bought an automatic leash. Therefore, Dusty and Tanner are walked.”
No. I bought a piece of technology.
The dogs still need a destination. Someone still needs to choose the route. And when Tanner sees a bicycle and bolts, I still want judgment attached to the leash.
The same distinction matters in business.
Instead of asking, “Where can we use AI?” ask:
Which growth outcome could AI materially improve?
Maybe sellers spend hours deciding which target accounts deserve attention. The goal should not be to deploy AI account scoring. A better goal would be to reduce the time between a meaningful account signal and seller action from five days to five minutes.
Maybe your website serves dozens of personas. The goal should not be to add an AI chatbot. Define the result: increase qualified visitor-to-meeting conversion from 2 percent to 3 percent.
Maybe customers underuse features associated with stronger retention. The goal should not be to deploy a customer-success agent. Define the result: increase adoption among at-risk accounts by 15 percent and reduce churn.
Once the outcome is clear, the operating questions become clearer too:
🐕 What can AI decide?
🐕 What can it recommend?
🐕 What can it execute?
🐕 Where does a human approve or intervene?
🐕 Who owns the business result?
Customers do not ultimately want software. They want fewer outages, faster hiring, more revenue, lower risk, higher productivity, and better retention.
That is why the more important shift is not from manual work to AI features. It is from software as a tool to results as a service.
In R8 of Walking the Dogs, I close the Reframe stage of my G-R-O-W-T-H Framework with one final question:
What would we design differently if the result mattered more than the technology?
Dog walked.
Next, we move into Orchestrate, where all these choices finally have to work together in the real world.
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