"Revolutionizing your Business with AI" is a comprehensive yet digestible overview of Artificial Intelligence and Machine Learning. This presentation elucidates their fundamental concepts, showcases real-world applications, and equips attendees with strategic tools like the AI Idea Canvas and Evaluation Template. Whether you're a business leader or an intrigued learner, this presentation simplifies AI, aiding you in confidently navigating its transformative landscape.

1. Revolutionizing your
Business with AI
Omar Maher
/OMaher
@OmarAITips
/OmarMaherAI

6. This is a big moment..

7. Probably the biggest in
known history..

8. You could be part of it

9. Your company could be part
of it

10. Egypt could be part of it

11. #AI4Egypt: Let’s make Egypt a Generative AI Leader

12. Cairo Generative AI Meetup
Coming Soon!

13. What?
How?

14. What?
How?
Why

15. Omar’s Bio
● 14 Years AI Experience
● Helped 100+ clients implement AI
● Fortune 500, National Governments
● X-Global Director of AI at Esri

16. Omar’s Bio
● 14 Years AI Experience
● Helped 100+ clients implement AI
● Fortune 500, National Governments
● X-Global Director of AI at Esri
● Co-founded Trustious & Homna
● X-Director of Advanced Analytics @ ITWorx
● Director @ Parallel Domain
● Founder of AI-Cases.com

17. Customers
National and Local Governments, Fortune 500
US National & Local
Government
Banking &
Insurance
Retail, Telecom, &
Utilities
Oil & Gas

18. https://ai-cases.com/

19. Outline
1. What is AI?
2. How does it work?
3. Types of AI
4. Use-cases
5. What shall we do?
6. Resources

20. Outline
1. What is AI?
2. How does it work?
3. Types of AI
4. Use-cases
5. What shall we do?
a. Adoption Levels
b. Selecting your first use cases
c. Running Experiments (POCs)
d. Scaling
6. Resources

21. Outline
1. What is AI?
2. How does it work?
3. Types of AI
4. Use-cases
5. What shall we do?
6. Resources

24. Machine
Learning
Deep
Learning
Artificial Intelligence

25. Outline
1. What is AI?
2. How does it work?
3. Types of AI
4. Use-cases
5. What shall we do?
6. Resources

30. Machine Learning
A = 5x + 3y + 2

31. Making Predictions: Training Models
Call
Drops
# Complains Subscribed
Package
Call Rate
Decline
Churned?
4 5 ABC 20% Yes
6 2 ABC 5% No
9 4 XYZ 12% Yes
Features Output (label)
Training Data
(Historical)
For Learning..
New Data Prediction
Learning
Models
Trained
Model
Problem: Predicting Churn
7 5 KLM 8% Yes (75%)

32. Teaching Machines via Input > Output Examples

33. Outline
1. What is AI?
2. How does it work?
3. Types of AI
4. Use-cases
5. What shall we do?
6. Resources

34. Types of Machine Learning

35. Patterns for AI Use-cases
Prediction
Clustering
(Segmentation)
Anomaly Detection Computer Vision
Content Generation
Chatbots, NLP, Voice
Analytics

36. Making Predictions

37. Image Understanding

38. Natural Language Understanding
Entity Extraction Document Classification
Sentiment & Tone Analysis Chatbots
Optical Character Recognition

39. Anomaly Detection

40. Unsupervised Learning (Clustering)
https://medium.com/@chisoftware/supervised-vs-unsupervised-machine-lea
rning-7f26118d5ee6

41. Unsupervised Learning (Clustering)
https://www.metamaven.com/14-ways-machine-learning-can-boost-m
arketing/

42. Generating Realistic Content
Art Generation by
Midjourney
Text Generation by ChatGPT

43. Outline
1. What is AI?
2. How does it work?
3. Types of AI
4. Use-cases
5. What shall we do?
6. Resources

44. Personalized Recommendations
More about this use case here

45. Personalized Recommendations

46. Personalized Recommendations (ROI)
Source: https://www.recombee.com/case-studies.html

47. Personalized Marketing
Offers, Coupons, Discounts..
More about this use case here

48. Starbucks uses AI for Hyper-Personalization
• 3X increase in marketing
campaign effectiveness
• 2X increase in email
redemptions
• 3X increase in incremental
spends via offer redemptions
• 24% of total transactions
coming from the mobile app

49. Marketing & Sales (1)
Personalized
Marketing
Predict top
promotions per
customer, best time,
best channel
Next Best Offer
Predict a specific action or
offer for a specific
customer that will likely
drive a purchase
Cross & Upselling
Predict best
products to push
per sale
Channel
Optimization
Predict best channel
that would yield the
highest ROI
Dynamic Pricing
Predict best price
that would yield
highest revenues -
based on demand,
time of the year,
location, and other
attributes

50. Demand Forecasting
Accurately forecast products demand based
on seasonality, weather, historical purchasing
patterns, and other factors.
Automate replenishment orders by
forecasting demand per product and
geography.
More about this use
case here

51. Demand Forecasting (Results)
● Reduce Forecasting Errors by 30 to
50% in supply chain networks
● 65% Reduction in lost sales due to
inventory out-of-stock
● 10 to 40% Decrease in warehousing
costs

52. Other use-cases in Retail
More about these use cases here

53. Supply Chain

54. ETA Prediction
Precisely predict the estimated time of
arrival..
..by taking into account various factors such
as:
- Product/package type
- Season, origin, destination, weather
- Historical delivery records, customer
feedback, and other relevant
parameters.
More about this use case here

55. ETA Prediction (Results)
● Reduction of Delivery Time
Prediction Errors by upwards of
65%
● Reduce Call Center volumes by
40%
● Reduce used Vehicles by 35%,
miles driven by 22%, and driving
time by 18%

56. Smart Document Processing
Streamline the process of analyzing
supply chain documents such as
invoices, purchase orders, bills of
lading, and customs documents..
..by swiftly scanning, digitizing, and
extracting valuable insights
More about this use case here

57. Smart Document Processing (Results)
● Process documents in less than
2 minutes versus 20 hours by
humans
● 50% cost reduction by applying
automated ways of document
processing

58. Predict Supply Chain Disruption
Identify potential risks in supply
chain networks by, including news
outlets, weather feeds, social media,
and unstructured reports
More about this use case here

59. Predict Supply Chain Disruption (Case Study)
https://www.prewave.com/wp-content/uploads/2021/09/Prewave-Whitepaper-VW-EN.pdf

60. Predict Supply Chain Disruption (Results)
● Ability to respond to disruption 36
hours faster than manual responses
● Increase early Risk Detection by 85%
● A company was able to anticipate
80% of late purchase orders due to
dashboard alerts and reduce inventory
by 2 to 3%, which could translate into
$15 million to $20 million in savings

61. Other Supply Chain Use-cases
More about these use cases here

62. Health

63. Diagnosis of Medical Imaging
Extracting insights and detecting
anomalies from X-rays, CAT scans,
MRIs, and other testing modalities
(e.g. retinal scanning).
Those anomalies could be used for
early diagnosis of possible diseases
like Cancer, Pneumonia, COVID-19,
Diabetes, and more
More about this use case here

64. Diagnosis of Medical Imaging (Results)
● Reduce Diagnosis of Brain Tumors from 40
minutes to 3 minutes
● AI model trained to find metastasized breast
cancer tumors was able to detect 92.4% of
the tumors, compared to the human
pathologist average of 73.2%
● Mammography Screenings: Radiologists’
accuracy increased from 75.3% to 84.8%
when they used AI

65. Precision Medicine
From one-size-fits-all to Personalized Treatment
(and Medicine) designed for each Patient based
on their:
- Genetic history, genomic sequencing,
medical records
- Location, environmental factors, and more.
AI is used to predict the effectiveness of these
tailored treatments.
More about this use case here

66. Eliminate Medication Errors
In the US alone, there are over 1 Million injuries
that happen annually as a result of Prescription
Errors.
AI has the ability to Identify and prevent
medication related errors, possibly via outlier
analysis and anomaly detection. Flag
medications that conflict with the profile of the
patient, physician, or institution
More about this use case here

67. Surgical Assistance
AI can assist surgeons during operations by
identifying critical components, indicating safe
dissection areas (CVS), issuing relevant warnings,
and highlighting well-performed surgical actions.
More about this use
case here

68. Surgical Assistance (Results)
● A study conducted on 379 orthopedic patients
revealed that AI-assisted surgery resulted in 5
times lesser complications compared to the
surgeons operating alone
● Machine learning helped UI Health Care reduce
surgical site infection by 74%, save $1.2 million

69. Other Health Use-cases
More about these use cases here

70. Financial Services
Banking, Insurance, Fintech

71. Credit Risk Assessment
Predict the Risk of Default per Credit Applicant
(not being able to pay the loan installments on
time).
Assign individualized credit score based on
factors including current income, employment
opportunity, recent credit history,
More about this use case here

72. Credit Risk Assessment (Results)
● 37% Reduction in Default
Losses
● JPMorgan Chase introduced a
contract intelligence platform in
2017 that used ML to review
12,000 credit agreements in
seconds. In human effort units,
it would take approximately
360,000 hours every year to go
through this volume

73. Fraud Detection
Flag unusual transactions and behaviors that
might indicate fraud attempts.
Analyzing historical transaction patterns per
customer/customer segment, spot anomalies.
Examples of fraud include credit card fraud, loan
fraud fraud, onboarding customers fraud
More about this use case here

74. Fraud Detection (how it works?)

75. Fraud Detection (how it works?)

76. Fraud Detection (how it works?)

77. Fraud Detection (how it works?)

78. Predictive Maintenance
https://azure.microsoft.com/en-us/features/iot-accelerators/predictive-mainte
nance/demo/
More about this use case here

79. Customer Service
Customer Support
Automation
Automate transaction calls
using voice recognition
algorithms and cognitive
agents. Chatbots for
Automated Customer
Support
Voice of the Customer
Extract Insights about
customer top problems,
interests, and topics from
social media, emails, and
customer service chatter
Predictive Request
Management
Route call-center cases based
on multimodal data to
increase customer
satisfaction and reduce
handling costs.
More about these use cases here

80. Chatbots for Automated Customer Support
More about this use case here

81. Chatbots for Automated Customer Support
SFR has managed to
automate 25% of all
demands in weeks
Bouygues Telecom chatbots
on mobile and their website
to manage mobile
subscriptions and support.
Groupe Mutuel uses
Chatbots for
modifying,
cancelling or
suspending
insurance contracts.

82. Smart Complain Routing

83. Customer Voice Analysis

84. AI for Recruitment
Optimize Job Description,
Predict Best Advertising
Channels and Times,
Automate Campaign
Design
Predict Top Performers
based on your historical
performance data, and
external candidate data
Automate Candidate
Onboarding, Meetings
Scheduling, and Next
Steps
Engage & Select
Identify
Advertise
Predict Employees
who are likely to leave,
and mechanisms to
retain them
Retain

85. 1. Advertise
Optimize Job Description Wording
Select best words for Job Description that would generate highest
ROI
“An above-average Textio Score will bring
us about a 30% increase in the number of
people qualified for an assessment.”
Brad Miller, Site Director, P&G Smart Lab

86. Deploy your job campaign and ads that
will be A/B tested and automatically
improved for the best results.
AI automatically sets up the best
performing ads for your campaign
across all media channels (e.g.
Facebook, Instagram, Google)
1. Advertise
Predict Best online channel to buy job ad-space, best time to publish

87. 2. Identify
The software learns which
candidates moved on to become
successful and unsuccessful
employees based on their
performance, tenure, and
turnover rates
It learns what existing employees’
experience, skills, and other qualities
are and applies this knowledge to new
applicants in order to automatically
rank, grade, and shortlist the strongest
candidates.

88. 3. Engage & Select
Never lose touch with
potential future candidates
Give successful candidates a
head start through
on-boarding
Attract and engage top
talent across multiple
platforms
Automatically
schedule qualified
candidates on your
calendar, or
integrate and
request additional
assessments

89. Generative AI Use cases
Art Generation by
Midjourney
Text Generation by ChatGPT

92. Retrieval Augmented Generation (RAG)
(Less hallucination, more facts w/ sources)

93. Scenario:
Employees inquiring about internal policies

95. Scenario:
Contract Analysis & Inspection

96. Chat with Enterprise Data

97. Scenario:
Generating Marketing Copy (images + text)

99. Scenario:
E-Commerce: return policy, product inquiries..

100. Chat with Enterprise Data

101. Outline
1. What is AI?
2. How does it work?
3. Types of AI
4. Use-cases
5. What shall we do?
6. Resources

102. What’s the ideal state for AI adoption?

103. Level 3: AI applied across the board
Major Competitive Differentiator
Massive Cost Savings & Revenue Boost
Top-notch Customer Experience

104. Supply Chain Manufacturing Marketing
Product
● Demand Forecasting
● Logistics Optimization
● Document Processing
● Pred Maintenance
● Visual Inspection
● Personalized XP
● Interact via Chat
● Hyper-Targeting
● Price Optimization
● Content Generation
Customer Support Legal Other
IT & Software
● Chatbots 2.0
● Smart Routing
● Chat w/ Data
● Contract Inspection
● Code Generation
● Threat Detection
● Fraud Detection
● Proposal Writing
● Chat w/ Data
AI in
Core Functions
AI in
Support Functions

105. Level 2: AI applied in all core functions

106. Supply Chain Manufacturing Marketing
Product
● Demand Forecasting
● Logistics Optimization
● Document Processing
● Pred Maintenance
● Visual Inspection
● Personalized XP
● Interact via Chat
● Hyper-Targeting
● Price Optimization
● Content Generation
Core
Functions

107. Level 1: AI applied in some core functions

108. Supply Chain Manufacturing Marketing
Product
● Demand Forecasting
● Logistics Optimization
● Document Processing
● Pred Maintenance
● Visual Inspection
● Personalized XP
● Interact via Chat
● Hyper-Targeting
● Price Optimization
● Content Generation
Some Core
Functions

109. How to you get there?
Find the right
use-case(s)
Run Experiments Scale
- Understand AI
- Understand relevant use-cases
- Brainstorm personalized use-cases
- Evaluate & select (ROI + feasibility)
- Get the right tech team
- Design the right experiment
(scope, data, biz & tech metric)
- Continuous Adaptation
- From Science to Engineering
- Change Management (process &
people)
- Continuous Monitoring &
Improvement

110. 1. Finding the Right Use case
Finding the Right Use case:
1. Get Educated on AI (concepts + use cases)
○ AI-Cases.com for use cases
2. Brainstorm (AI Idea Canvas)
3. Evaluate and select top use case(s) (AI Idea Evaluation Template)

111. https://ai-cases.com/

112. AI Idea Canvas
Problem (or
Value)
AI Idea Expected ROI Data
AI Patterns &
Tools
End Users & Adoption POC Scope

113. AI Idea Canvas (Examples)
Problem (or
Value)
AI Idea Expected ROI Data
AI Patterns &
Tools
End Users & Adoption POC Scope
Could be either an existing pain or a
new value to be created
Examples:
Process X takes too much time
Low Marketing ROI for Campaign Z
Better Customer Service
Higher Revenue per Customer
How AI could be used to solve this
problem or create identified value
Examples:
Predictive Maintenance
Personalized Mobile Marketing
Chatbot for Customer Service
Why should we consider this idea?
$$, Time, Customer Satisfaction
Examples:
5% increase in digital sales
30% cut in customer calls
15% cut in maintenance costs
Do we have the needed data?
Where is it residing?
Examples:
CRM for customers data
SAP for transactions
XYZ for Products data
Which of the 6 AI Patterns is used? What AI
services/tools could be leveraged?
Examples:
Prediction and Clustering
Amazon Personalize, Amazon Forecast
Who will be using this? What’s the motivation?
Examples:
Digital Marketing, Operations, Field sales
They have asked for a similar need before
They have a new mandate to cut X costs
How can we test this concept with little
investment?
Examples:
Detecting one type of product damages with 70%+
accuracy
Chatbot for two topics with 10% of customers,
targeting 20% decrease in support time

114. Evaluating AI Ideas
● Data Readiness
● Business Impact
● Feasibility
● Expected Adoption
Explore the dynamic AI Idea Evaluation Template here

115. 2. Run Experiments
Finding the Right Use case:
1. Decide if you’ll outsource, train, or hire
2. Leverage AI Cloud Services as feasible (plug-n-play)
3. Design the right Proof of Concept

116. AI Capacity: Outsourcing vs. Hiring

117. AI Team
Detailed scenarios here

118. Amazon’s AI
Services

119. Amazon Recognition

120. Amazon Rekognition

121. Amazon Comprehend

122. Azure Speech AI

123. Azure Form Recognizer

124. Amazon Lookout for Vision

125. Amazon Lookout for Vision

126. Amazon Lookout for Equipment

127. Amazon Lookout for Metrics

128. Amazon Fraud Detector

129. Amazon Forecast

130. Azure AI Services
Decision Making, Text, Speech

131. Design your Experiment (Proof of Concept)
● Problem
● Hypothesis
● Scope of Work
● Success Criteria
● Data
● Modelling & Tools
● Infrastructure
● Deliverables
● Team
● Time

132. 3. Scale
● From Science to Engineering
● Change Management (process & people)
● Continuous Monitoring & Improvement

133. Outline
1. What is AI?
2. How does it work?
3. Types of AI
4. Use-cases
5. What shall we do?
6. Resources

134. Resources AI-Cases.com
AI for Everyone

135. Resources (Generative AI)
https://www.coursera.org/learn/generative-ai-with-llms
https://cloud.google.com/blog/topics/training-certifications/ne
w-google-cloud-generative-ai-training-resources

136. Omar’s Contacts
+1-909-488-1133
omar@ai-cases.com

137. Thank You!