5 Brutal Truths: Data Scientists Who Operationalize AI Fast Will Win!

Read time: 2.5 minutes

5 Hard Realities: You either operationalize AI quickly or you don't.

1. Quit building models that don't get used. Embed predictions in the workflows of your users.

❌ Dashboards and notebooks
✅ Automated and proactive actions in CRM systems; alerts; retention offers.

2. C-Suite execs don't want probabilistic scores, they want decisions.

❌ "91% accuracy for forecasting."
✅ "Increase inventory by 18% in Region A next week."

3. Most value from AI is lost through human interpretation. Stop having your analysts interpret the predictions produced by the models you built.

❌ Raw predictions
✅ Automated key performance indicator summaries sent to Slack, Teams, and email.

4. Your business knowledge is worth more than your model's architecture. AI is through the roof; however, no one has the context around it.

❌ Focusing on how sophisticated a model can get.
✅ Refining a workflow to align with the company's key performance indicators (KPIs).

5. The fastest return on investment is through the reduction of operational timeframes, not through smarter models.

❌ Expending time optimizing accuracy without reducing delays
✅ Automating workflow before the meeting even begins.

💡Key Takeaway: 

Modeling that doesn't result in action is not valuable. You must operationalize your predictions to be relevant.