Since the 1960s, Artificial Intelligence has promised us benefits in business and in our personal lives. This presentation takes us from the early days up to machine learning and applications for enterprise businesses that are delivering personalized experiences to customers ... to a "segment of one."

1. Copyright © 2017, Datalog, Inc., all rights reserved. All trademarks property of their respective holders
®
A brief history of artificial
intelligence for business
Jack Crawford, Founder and CEO

2. Arthur L. Samuel, 1959
2

3. Back then, AI was a forest of trees
citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.368.2254&rep=rep1&type=pdf

4. In the 1970s interest in AI renewed
Artificial intelligence
attracted money
like bears to honey
4Image: zooportraits.com
VC Bear

5. and the money
dried up
Then, the bears got burned
5Image: The Huffington Post

6. After a long AI Winter, the winds
of Δ ignited interest again
6Image: The BBC, “AI: 15 key moments in the story of artificial intelligence”
The first money saving
business AI was an
“expert system” built at
DEC in the 1980s

7. In the 1990s, other businesses began to
to employ “expert systems”
7Illustration: learnlearn.co.uk
EXPERT SYSTEM

8. It was the age of …
8
Rules

9. Rules to put people (us) into buckets
9
Market
Segmentation

10. Then Jeff Berry had a bright idea
10
“Each customer should
be seen as a
SEGMENT OF ONE
Image: LoyaltyOne

11. 11Image: Getty Images, Cristian Baitg

12. Which ushered in the age of the …
12
Individual

13. The problem was that at that time …
13
The only way to predict
individual behavior
and act on it in a timely
manner involved using
rules
Image: Pegasystems, “Next Best Action,” youtu.be/HeL-Y1kSoDg

14. RULES
14

15. Maybe, just maybe …
15
We don’t need
rules

16. Two years ago at the 29th AAAI
16
aaai.org/ocs/index.php/AAAI/AAAI15/paper/viewFile/9444/9488

17. Here’s a true story
The problem
1.Our client had 49%
market share YOY
2.It dropped to 46% in
the past year
3.Customer switch was
the culprit
The goal
Find out which customers
were likely to switch
That is, identify the
segment of 1
17

18. Steps that we took
1. Ask the CMO if we could try
2. Listen to her laugh and say “Sure. Good luck with that.”
3. Call a meeting with the data guardians, citing approval from their chief
marketing officer
4. Wait to receive the data we requested (1 month)
5. Load and clean up the data (1 hour)
6. Run the model on 70% of the data (1 day)
7. Verify prediction with the remaining data (1 day)
8. Spend time improving results so they don’t think it was easy (1 month)
9. Give them the test results (92% accuracy over the past 3 years)
18

19. So what did we hope they would
do with this miraculous information?
1. Create strategies to identify interventions for customers with high
propensity to switch to their competitor
2. Establish “A/B” testing (or other measures) to validate the
effectiveness of these strategies in practice
3. Put these interventions into the “field”
4. Realize the benefits through recovery of their market share
19

20. This particular story had a surprising
twist, and led to our AI startup
They ”shelved” the idea
Why?
Other market factors might have caused the switch
1. Slow pace of product improvement
2. Reduced advertising budgets
3. Sales force effectiveness gaps 20

21. And that “made sense” in 2015?
21
At the time, many businesses couldn’t see the
power of machine learning
for predicting the buying behavior of an
individual consumer

22. It seems that many innovations take
forever to be adopted by
business – 2009
22machinelearning.org/archive/icml2009/papers/218.pdf
NVIDIA
GTX 280

23. You can make AI valuable for
business – opportunities
Sales and marketing
Next best action
Salesrep coaching
Customer switch
Supply chain
Supplier commitment prediction
Conversational bots
Customer care
Propensity to call
Conversational AI
Personalization
Research and
development
Knowledge retention
Success factor identification 23

24. Beyond predictive AI, much more
opportunity lies ahead
24

25. The next leap in AI is
25
Conversation

26. MyPolly.ai
™
Join our conversational AI beta at:

27. 27
postscript:
Let’s remember the pioneers who
began the journey that brought
us here today

28. The reunion of some early AI researchers
28Image: The New York Times, December 7, 2009

29. Copyright © 2017, Datalog, Inc., all rights reserved. All trademarks property of their respective holders
®
Thank you
29
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Jack@datalog.ai
™