Get startedGet started for free

Different types of strategies

1. Different types of strategies

Welcome to the course, where we will learn how to build an effective AI strategy. In the video, we will demystify what an AI Strategy is and how it relates to business and data strategy.

2. AI - a business priority

We are living in the age of unprecedented digital connection, which is disrupting the way businesses operate.

3. AI - a business priority

AI, or artificial intelligence, has become table stakes and a business priority for gaining a competitive edge. However, to harness its full potential, a well-crafted strategy aligned with business goals is essential.

4. AI and its applications

To understand AI strategy, let's first explore AI and its applications. AI helps businesses grow in several ways, such as enhancing customer insights,

5. AI and its applications

as seen with Starbucks' "Deep Brew" project, which personalizes customer experiences and

6. AI and its applications

optimizes operations,

7. AI and its applications

or increasing efficiency, like how GE uses AI for predictive maintenance,

8. AI and its applications

reducing downtime,

9. AI and its applications

or even in opening new revenue streams, like how Alibaba is using AI to foster smart cities.

10. Strategy vs. plan

Let's focus on what is a 'strategy' – is it a plan? A plan is a set of activities aimed at a goal, like boosting customer engagement or launching new products. It bridges the current situation to business goals, answering the 'what', 'when', and 'how'. Strategy, however, is decision-making involving variables like customer preferences, regulations, or technology advancements. So, we understand how strategy is different from a plan. Let's now understand how a strategy is different than goals and tactics in an organization's context.

11. Strategy pyramid

Let's examine the strategy pyramid: At the top are goals, outlining the company's vision and mission. These drive the strategy, informed by decision variables, and finally, execution follows, translating strategy into action. Next, let's understand what a business strategy is.

12. Business strategy - software example

A business strategy refers to all the decisions and actions to achieve the larger vision. For example, business strategy for building software involves an understanding of industry and market dynamics,

13. Business strategy - software example

who the end-user is,

14. Business strategy - software example

their pain points,

15. Business strategy - software example

would the new software solve the problem, and how? What would be the definition of success and its metrics?

16. Business strategy - software example

Is there any other opportunity area to look into, should building this be a priority? If so, why?

17. Business strategy - software example

What would be the return on investment from this product, including financial and technological analysis?

18. Data strategy

Now, let's explore how business strategy is linked with data strategy. AWS describes data strategy as an organization's long-term vision for collecting,

19. Data strategy

storing,

20. Data strategy

sharing,

21. Data strategy

and usage of its data.

22. Data issues

Data issues related to quality,

23. Data issues

privacy,

24. Data issues

security,

25. Data issues

and integration can slow down the strategic initiatives.

26. Data alignment

Hence, an effective data strategy requires continuous adjustments and iterations to align with the business strategy.

27. Time for AI strategy?

The groundwork is done with business goals and data to support it, but where does AI strategy come into the picture? While, in some cases, a robust business strategy and mature data strategy eventually lead to leveraging AI to augment and enhance decision-making, it is not a strict prerequisite.

28. AI sparks innovation!

AI is the cornerstone of innovation, sparking the discovery of new opportunities amid an evolving industry landscape powered by technological advancements. These new initiatives may arise in areas previously unexplored and thus may not have pre-existing data.

29. The trifacta

So, AI and data strategy work concurrently, aligning with overarching business goals.

30. AI strategy

An effective AI strategy starts with the most important question of why AI is needed in the first place - is it out of fear of missing out or from business prerogatives?

31. AI strategy

What is the value proposition?

32. AI strategy

What are its success criteria?

33. AI strategy

How would AI components align with existing infrastructure and technology stack? Note that these are some of the starting points, and we will delve deeper into what goes into making a comprehensive AI strategy, which is the focus of this course.

34. Let's practice!

Let's revise how these strategies work in tandem with each other.

Create Your Free Account

or

By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA.