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It's time to wrap-up!

1. It's time to wrap-up!

Congratulations! You've completed this comprehensive course on AI Strategy.

2. The trifecta

We have covered quite a lot, starting from how AI strategy aligns with the business and data strategy.

3. AI strategist as an orchestrator

We then revisited what makes a good strategy and how an AI strategist can help put that strategy in place through its role as an orchestrator of the entire AI lifecycle.

4. Projects that justify ROI

Delving deeper, we explored how AI differs from traditional software and discussed the characteristics of business problems that warrant AI technology. Understanding the cost and return dynamics is central to AI strategy. As each organization would have a different approach to deriving the returns, we have discussed the factors that help build a lens to assess the ROI.

5. Innovation culture

By now, we understand that AI projects are inherently iterative and exploratory. Hence, it is important to highlight the role of promoting an innovation culture that allows the teams to experiment without fearing any negative consequences.

6. Getting the components together to scale

Having discussed the role of culture, high-performing teams, and data availability, we underscored the risks associated with AI, including privacy issues and ethical concerns. Finally, we checked the idea's feasibility by conducting a PoC that gives a glimpse of what type of challenges could arise during scaling. We also learned how MLOps is key to scaling AI projects efficiently and effectively. While your business is uniquely placed to leverage AI, I hope the framework shared in this course helps you design your winning AI strategy.

7. Congratulations!

Congratulations!

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