The document discusses the prevalent interest in artificial intelligence (AI) due to the vast amount of generated data and advancements in cloud computing that facilitate data analysis. It highlights the importance of good data, clear objectives, and a focused scope for successful AI projects, emphasizing that poor data and unclear goals often lead to project failures. The potential of predictive analytics to provide valuable business insights is underscored.

1. Being Realistic About
Artificial Intelligence
Tarun Gangwani // @tarungangwani

2. Why are people talking about AI so much?

3. Why are people talking about AI so much?

4. Why are people talking about AI so much?
We have generated a shit ton of data.

5. Why are people talking about AI so much?
We have generated a shit ton of data.
tweets
texts friends
likesposts
updates
shares
hearts
pictures
relationships
connections
retweets snaps reposts
blogs
tries
live
viewers
faces
names
contacts
food reviews
metrics health
fitness
fitness
memes
posts
pokes

6. What have we been doing with this data?

7. Cloud computing has enabled our robot overlords.

8. bot overlords.

9. bot overlords.

10. bot overlords.

11. bot overlords.

12. bot overlords.

13. 🔮

14. predictive analytics
🔮

15. predictive analytics
🔮
descriptive analytics
📊

16. using data to forecast the future
🔮
📊 making sense of data we have

17. 20%
🔮
80%
📊

18. 🔮
📊

19. 🔮
📊

20. 🔮 Top three reasons
PA projects fail.

21. Your data is bad.

22. The end goal
is not clear.

23. The scope is
too large.

24. With good data, a clear goal, and a narrow scope,
you can harness predictive analytics to gain
critical business insights.

25. Learn more at the Ideas Hub!