An overview of the must-know insights for enterprise and mid-size business leaders who are interested in getting the ROI from AI.
Originally presented at Syracuse University's NEXT Technology Conference in Syracuse, NY, November 8th, 2019.
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Critical Lessons for Near-Term AI ROI
1. Near-Term Trends and ROI of AI
by Daniel Faggella
CEO, Emerj Artificial Intelligence Research
2. Presentation Preview
● What Emerj Does
● The Impending AI Transformation
● AI as a Competitive Advantage
● The Right and Wrong Ways to Get Started
● Next Steps for Business Leaders
emerj.com
3. Key Takeaways
1. The competitive advantage that ANY firm
can develop today (even before you
adopt AI)
2. Four steps to get started with AI the right
way
emerj.com
4. At Emerj, we have a singular focus:
Mapping the applications of AI to help
leaders execute on winning AI strategies.
Global organizations trust us to support their AI
goals and strategies with critical data and insight
(World Bank, global healthcare firms, etc).
Presenting our AI Research at
United Nations HQ, NYC
Emerj Artificial Intelligence Research
8. Impact
Emerj:
Our hundreds of AI expert interviewees differ in their opinions on many
topics, but they unanimously agree that the workflows, processes, and ways
of servicing customers will change in every industry.
PwC:
AI could contribute up to $15.7 trillion to the global economy in 2030.
emerj.com
10. The State of AI in Business
Appearance:
Everyone is doing it
It’s transforming all
industries already
Just add data scientists or
an AI vendor and get
results
Reality:
Everyone is talking about it
It’s bumbling to find a fit in
the enterprise
Many internal changes in
the enterprise are required
before any results are
possible
emerj.com
11. State of AI in Business
Of “AI companies” even
have requisite AI talent on
their teams.
⅓ ⅓
Of AI companies with
talent have any kind of
meaningful adoption.
12. Challenges
1. AI is Not IT
● Iteration required
● Data access
required
● Cross-functional
teams
A change in culture,
workflows, and teams
is necessary to enable
it.
2. AI Ignorance
● What does AI do?
● How does AI
work?
● Where could I
apply it?
● etc...
3. Nascent Use-Cases
AI is experimental by
nature, and the current
use-cases for
enterprise are new.
When startups stay
afloat from revenue,
not VC money there will
be more tried and true
use-cases.
emerj.com
13. AI as a Competitive Advantage
emerj.com @danfaggella
14. 1 - Critical Capabilities
Is Not:
Chatbots
“Cognitive RPA”
ANY individual AI
application
Is:
Skills
Culture
Knowledge
The “Critical Capabilities”
that allow us to leverage AI
into the future
emerj.com
15. 1 - Critical Capabilities
Data Infrastructure
Cross-Functional AI
Teams
Contextual AI Knowledge
(Leadership)
Data Science Talent
More...emerj.com
16. 2 - Data Dominance
● Collect a lot of data with a product or process
(sometimes at a loss to start)
● Use that data to create a better product or process
● Scale that product or process to more
users/customers because it is better
● New users provide more data
● Repeat until nobody can catch up
17. 2 - Data Dominance
HVAC Company Recreational Boating
Insurance
emerj.com
19. Getting Started
Don’t:
Believe and follow what
you read in press releases.
Ask “where can we use AI”
and engage in “toy”
applications.
Believe most AI ROI to be
short-term and
measurable.
Do:
Expect adoption to be
challenging.
Expect advantage from
long-term capability
building, not any one
solution.
Ensure the AI savviness of
your leadership team.
emerj.com
23. Next Steps
1. Educate Your Leadership:
(a) What AI can do broadly
(b) Use-cases in your sector and adjacent sectors.
(c) Realistic requirements of adoption
2. Talk to and Study Adopters: This could be done online, at events, etc.
3. Inform Your Plans: With consultants, data scientists, stakeholders.
4. Decide on Next Steps:
(a) Talent
(b) Initiatives