Real Life Experiences in Engaging Customers and Doing Business My Presentation at the IBM TechU University in Prague 2019 This presentation is about selling Artificial Intelligence Solutions in a market thet is still not completely aware of the new possibilities.

1. AI Real Life Experiences
in engaging Customers and doing business
IBM Technical University 2019
#techuprague
Cognitive
Session: c111976
Andrea Vercellini
Systems Technical Leader Italy
Enrico Busto
Founding Partner & CTO

2. linkedin.com/in/ebusto
Enrico Busto
enrico.busto@add-for.com
Founder & CTO

3. MEGA TRENDS

4. A Mega Trend is a macro-economic force
that impacts business, economy, and society,
defining our future world.

5. Mega Trend is something that happens
regardless of the will of individual companies.
In other words,
it is something to be adapted to,
under penalty of being excluded from the market.

6. There are some TECHNOLOGY
MEGA TRENDS that are shaping
the world today:
• IoT
• CLOUD & EDGE Computing
• SMART City
• SMART Factory
• ROBOTICS
• RENEWABLE ENERGY
SPEAKERS NOTES

7. Artificial Intelligence is the
common engine that powers all
the other TECHNOLOGY MEGA
TRENDS
SPEAKERS NOTES

8. WE IMAGINE NEW SCENARIOS
WITH THE BEST
ARTIFICIAL INTELLIGENCE SOLUTIONS
As a company we recognized this
opportunity from the beginning
I founded this company in 2008
with the specific goal of creating
Artificial Intelligence technologies
for the industrial market
SPEAKERS NOTES

9. HOW TO
DELIVER
The market related to Artificial
Intelligence is still far from being
mature.
Most of the technologies involved
have just been made available.
This is the point: how do we bring
this message to our customers,
overcoming distrust, managing
inappropriate and exaggerated
requests?
SPEAKERS NOTES

10. Technology Adoption Lifecycle
Sociological Model
Before dive into details, let’s have a
look to the theory:
The technology adoption lifecycle is a
sociological model that describes the
adoption of a new product,
according to the psychological
characteristics of defined adopter
groups.
SPEAKERS NOTES

11. In his book “Crossing the Chasm”,
Geoffrey Moore proposes a
technology adoption model
where five main demographic
classes are recognized:
innovators, early adopters, early
majority, late majority and
laggards.
Today I will give a name to those
five characters
and we will see some practical
real-life examples derived by our
experience.
SPEAKERS NOTES

12. Ryan
Innovator
Young, tech smart
usually employed in R&D
no access to budget
great for feedback & info
RYAN IS MOTIVATED
BY PERSONAL GROWTH

13. Emma
Early Adopter
She has insight to match
technology & business opportunity
She has access to budget
You must understand Her Vision
DO NOT SELL TO EMMA
SOMETHING YOU DON’T HAVE
EMMA IS LOOKING FOR A
CHANGE AGENT

14. Jeff
Early Majority
He’s pragmatic and risk-adverse
he doesn’t want to “beta” anything
quality and support are a Must
suppliers Brand is important
EMMA IS NOT A
GOOD-ENOUGH REFERENCE
JEFF IS LOOKING FOR
PRODUCTIVITY IMPROVEMENT

15. David
Late Majority
Conservative
he doesn’t like disruption
non confortable in
handling new technology
DAVID LOOKS FOR
ESTABLISHED STANDARDS

16. Bob
Laggard
Forget Bob

17. Ryan Emma Jeff David Bob
So, there are two different groups of people:
Ryan and Emma are looking for something New. They
are PRODUCT INNOVATORS
You can sell Artificial Intelligence to Emma
Jeff and David are looking for a PROCESS INNOVATION
You can sell products based on Artificial Intelligence to
Jeff
When you will have enough user stories, David will buy
the solution as well
SPEAKERS NOTES

18. Ryan Emma
Is there a
Practical Application for
this Technology ?

19. THE CHASM
it's subtle because Emma and Jeff
can superficially appear similar,
but Emma is looking for
a change agent,
she can accept glitches,
while Jeff is looking for
productivity improvement:
he wants things to work smoothly
Emma Jeff

20. Jeff David
Jeff is interested in
technology and has
a personal drive in
its adoption
David is interested in
something already
adopted by others

21. David
He buys technology just when it
has become an established standard
He buys from
well-established companies
It’s very hard to sell AI to David
Typical Question: who’s already done that?

22. DON’T MESS WITH EMMA
SHE’S LOOKING FOR A CHANGE AGENT
JEFF THRUST THE BRAND, HE’S LOOKING FOR
A WORKING SOLUTION
EVOLUTION, NOT REVOLUTION
DAVID DOESN’T LISTEN TO ANYTHING BUT
USER SUCCESS STORIES

23. 1 PRODUCT innovation

24. 1 PRODUCT
innovation
TARGET
customers
REQUIREMENTS
resident experts
GOAL
open new markets

25. FEEL VISION SPEECH THINK
Our Application Fields
Speaking about AI the main technical
fields are:
FEEL - Sensors and Digital Filters
(mainly automotive and industrial
controls), RCNN
VISION - all the vision applications
(images and video understanding on
RGB, IR, Thermal and special cameras),
Generative Adversarial Networks,
DCNN
SPEECH - Chatbots
THINK - Reinforcement Learning and
Advanced Controls
SPEAKERS NOTES

26. https://youtu.be/860ggRloLnw
CLICK LINK TO SEE VIDEO

27. REAL LIFEFirst time we met Emma she was looking
for something that has been promised by
an established supplier
Emma had her own budget and moved the
project forward without asking Bob
Bob would never have agreed to adopt a new technology
without first seeing it embedded into a working product
Finally Bob decided to adopt the AI solution on
the whole production models.
THE TIME BOB BOUGHT AI

28. REAL LIFE
THE TIMES THEY ARE A CHANGIN
Emma works for a market leader in
automotive testing equipment
The company knows that the era of the
internal combustion engine is coming to an end
Emma was charged with researching new market opportunities
in the fields of Electric Powertrain & Autonomous Driving
Addfor was hired thanks to its previous success projects

29. REAL LIFE
SUPER-HUMAN HANDLING
Emma works for a primary Japanese Automaker
The company is doing research in advanced automotive
controls for LEVEL 4 and LEVEL 5 Autonomous Cars
Emma was charged with prototyping new AI controls
Addfor was hired thanks to its previous success projects

30. REAL LIFE
It’s not you who find Emma,
but it is Emma who finds you
Emma verifies your reputation. Don’t mess with her
Bob could adopt AI when it’s embedded in standard technology
LESSON LEARNED
Emma is rare

31. 2 PROCESS
innovation
TARGET
internal departments
GOAL
efficient production, cost reduction

32. WORKING
SOLUTION
https://youtu.be/TogC2mscepE
CLICK LINK TO SEE VIDEO

33. WORKING
SOLUTION
https://youtu.be/_0Y5QpyJyA4
CLICK LINK TO SEE VIDEO

34. He cares about the company he's buying from,
quality of the product, supporting infrastructure
Jeff is looking for a
WORKING SOLUTION

35. WORKING
SOLUTION
https://youtu.be/xcxCl51lcqE
CLICK LINK TO SEE VIDEO

36. WORKING
SOLUTION
https://youtu.be/lBrchI8j6ds
CLICK LINK TO SEE VIDEO

37. WORKING
SOLUTION
https://youtu.be/ReXzVRAhF0c
CLICK LINK TO SEE VIDEO

38. WORKING
SOLUTION
https://youtu.be/JRl7qbArChQ
CLICK LINK TO SEE VIDEO

39. REAL LIFE
EVERYTHING HAPPENS FOR A REASON
Jeff works in the IT department of an Italian University
his job is to make things run smoothly and improve processes
Addfor was hired to develop a POC for Real-Time student counting.
The manifested request was not enough to justify the effort
After gaining trust with a successful POC Jeff disclosed his
much bigger Latent Need: to assess the effective mean space
available to every student
Always look for the Real Need. Design the solution around it.

40. REAL LIFE
WAREHOUSE MANAGEMENT
Jeff works in the IT department of an Italian food company
and is looking for something to streamline the warehouse
Manifest Need: to read the plate number of the incoming trucks
to alert the warehouse in advance
The market is full of ALPR solutions but Jeff needs something
specific: a volumetric solution for partially-readable plates
From the Details the Right Solutions.
NEVER FIGHT mass-market solutions if they’re right for Jeff

41. REAL LIFE
BIOMETRY WITH A TWIST
Jeff works in the R&D department of a company specialized
in surveillance services for high-profile customers
Original Need: to have a Deep-Learning discriminator to tell
false positive from real alarms in Thermal Camera Systems
Due to the success on the Thermal Images Jeff asked for a
Variant of our FACEfind to replace existing competitors
From Details the COMPETITIVE Solutions.
NEVER FIGHT mass-market products if they’re right for Jeff

42. REAL LIFE
TOO MANY FALSE ALARMS
AI for Video Analysis is a new technology but the market
starts to be Saturated with multiple options
Leading Companies offer fully-automatic Video Analytics
sadly those systems give too many false alarms
IBM and Addfor are installing Video Analytics base on state of the art
DCNN and IBM Power AC922 - planned 600 systems in three years
From Details the COMPETITIVE Solutions.
NEVER GIVE-UP on competitors declaration

43. REAL LIFE
You Must Understand his Real Needs
You will be Competitive on Details
LESSON LEARNED
Jeff IS your man for AI
Don’t be afraid of declarations from the competitors:
Most of them Oversell AI
Never Ever Oversell AI - The market is big enough

44. SHE’S LOOKING FOR A CHANGE AGENT
YOU MUST UNDERSTAND THE NEEDS
JEFF IS LOOKING FOR A WORKING SOLUTION
YOU MUST DEMONSTRATE K.P.I. WITH P.O.C.
EMMA AND JEFF DON’T CALL YOU TO REPLICATE
SOMETHING AVAILABLE ON THE MARKET. THEY’RE
ALWAYS LOOKING FOR SOMETHING SPECIAL

46. Enrico Busto
enrico.busto@add-for.com