AI Business Strategist
Evaluate AI investments, govern adoption and connect pilots to business outcomes. A strategy path for leaders and product teams.
Who this path is for
Useful for people making AI investment and adoption decisions. Coding is not the focus.
Study each topic, complete the applied exercise, and keep evidence of what you learned. These are original study milestones, not a claim to reproduce the full exam blueprint. Use the linked AWS exam guide to check all in-scope domains before booking.
Your learning roadmap
01AI literacy for decisions
3 focus areas · applied exercise
AI literacy for decisions
3 focus areas · applied exercise- AI capabilities and limits
- Build or buy
- Business constraints
Compare automation and AI options for a support workflow.
State the assumptions behind the preferred option.
02Business value
3 focus areas · applied exercise
Business value
3 focus areas · applied exercise- Baseline metrics
- ROI assumptions
- Pilot success measures
Build a one-page business case with a measurable pilot.
Include adoption, quality and cost measures.
03Responsible adoption
3 focus areas · applied exercise
Responsible adoption
3 focus areas · applied exercise- Accountability
- Risk ownership
- Data governance
Create an approval process for a proposed AI use case.
Assign owners for data, risk and operating decisions.
04Scale the change
3 focus areas · applied exercise
Scale the change
3 focus areas · applied exercise- Organizational readiness
- Training
- Feedback and rollout
Design a phased rollout with a clear stop condition.
Explain how evidence from the pilot changes the next phase.
Put the learning into practice
Dedicated CloudAdhar guided labs for this certification are not published yet. Continue with the official AWS preparation resources for additional practice.
Related labs cover selected skills. Completing them does not establish exam readiness.