Skip to main content
The Business of AI
An overview of business applications, opportunities and
challenges of Artificial Intelligence
MJCET Canada Alumni Talks | May 2020
Nabeel Adeni (IT ‘10)
Analyst - AI, CX
1@NabeelAdeni Nabeel.Adeni@Gmail.com NabeelAdeni.Medium.com
2
AI = The New Electricity
“Just as electricity transformed
almost everything 100 years ago,
today I actually have a hard time
thinking of an industry that I don’t
think AI will transform in the next
several years.”
Andrew Ng
Co-founder, Coursera
Adjunct Professor, Stanford University
Former Chief Scientist, Baidu
Founder, Google Brain
3
“Software is eating the world,
but AI is going to eat software”
Jensen Huang
Founder and CEO, NVIDIA
4
What the heck is AI?
- Artificial Intelligence is the field of computer
science dedicated to solving cognitive problems
commonly associated with human intelligence,
such as learning, problem solving & pattern
recognition.
- Techniques to enable the software to learn from
the data fed into it.
- Predictions or Insights
5
Why is it a big deal now?
- More data than ever before
- Faster compute power
- Cloud storage
- Advanced algorithms
- Investment in data & analytics
- CX focus
- 5G (coming soon)
6
How enterprises can leverage AI?
7
How enterprises can implement AI?
8
AI use cases: in our daily lives
● Chatbots: website customer support
● Virtual assistants: Siri, Alexa
● Facial recognition
● Autonomous driving: Tesla (Autopilot)
● Robotics
● Recommendation systems:
○ Uber: who to ride with
○ Amazon: what to buy next
○ Facebook: who should I connect with
○ Google Maps: what’s the best route
9
AI use cases: Vertical-specific
- Manufacturing
defect inspections, quality inspections, logistics planning and
supply management
- Finance
fraud detection, risk analysis for loans and mortgages, stock
prediction or company valuation predictions
- Healthcare
drug discovery, aided diagnosis, case capture, product design
- Environment
monitor water quality contaminants, predict and identify
contaminants
10
AI use cases: Function-wise
- Marketing
Audience segmentation, Targeting, Customer journeys
- Sales
Lead scoring, forecasting, account info aggregation
- Risk
Automated loan processing, churn
- Commerce
Product recommendation, dynamic pricing
- Product
Product design, demand forecasting, software testing
11
AI in Marketing
12
Potential Roadblocks
- Adoption rate: Pilot to production
- Access to data
- Data privacy & security
- Ethics and Bias in algorithms
- No one-size-fits-all approach
- Talent gap
- Ownership in the enterprise
- Measuring RoI
- Integration with existing stack
13
Actions you need to take (to stay ahead of the curve)
- Investigate how AI will impact your industry
Identify the skills, tools and certifications you need to stay
ahead of the curve
- Study the impacts of AI on your current role
Identify use cases, read white papers and solution blueprints
- Read
Prediction Machines, Andrew Ng’s Blog
- Take a course
Microsoft AI Business School
14
Thank you!
@NabeelAdeni
Nabeel.Adeni@Gmail.com
NabeelAdeni.Medium.com