This presentation was given at the OECD Network of AI Specialists (ONE) held in Paris on February 26 and 27. It covers the methodology for assessing AI use cases by technology, value chain, use, business impact, business value, and effort required.

1. Functionalities in
AI Applications
and Use Cases
Dr. Anand S. Rao, Global AI Lead, PwC

2. PwC Experience Center
THE METHOD
2
TWO PATHS TO AI
Enterprises are
realizing the value from
digitization to AI along
two distinct but related
paths—to enhance
productivity, increase
profits and enhance
experience.
Digitization
Productivit
y
Experienc
e
Profit
s
Revenue
s
Data (Volume, Velocity, Variety, Veracity, Value)
Artificial Intelligence
Simplification
Standardization
Automation
Cognification
Analytics
Productivity Experience ProfitsRevenues
Automation Path Analytics Path
Personalization

3. PwC Experience Center
THE METHOD
3
WHAT IS AI?
AI is the theory and
development of
systems that sense the
environment, make
decisions, and act that
would normally require
human intelligence.
Hear
See
Speak
Feel
AI that can act…
• Robotic process automation
• Deep question & answering
• Machine translation
• Collaborative systems
• Adaptive systems
AI that can sense…
• Natural language
• Audio & speech
• Machine vision
• Navigation
• Visualization
AI that can think…
• Knowledge & representation
• Planning & scheduling
• Reasoning
• Machine Learning
• Deep Learning
Statistics Econometrics Optimization
Complexity
Theory
Computer
Science
Game
Theory
FOUNDATION LAYER
Understand
Plan
Assist
Learn
Digital
Reactive
Physical
Creative

4. PwC
Where in the value chain can we use AI?
4
Operations & Development
Product
Development
Service &
Support
Operations
Outbound Logistics
Sales &
Distribution
Customers &
Marketing
Strategy &
Growth
Supply Chain &
Procurement
Finance, HR,
Planning
Inbound Logistics
How will we ensure our
product supply is meeting
demand?
VP, Supply Chain
How can we engage with our
customers to enhance their
experience?
Director, Marketing
How can we grow our market
share and which markets to
enter, exit or expand?
Director, Strategy
How do we innovate and
introduce new products and
services?
Director, Products
How do we increase customer
satisfaction and retain more
customers?
Director, Service
How can we reach more
customers and price our
products to increase sales?
Director, Sales
How can we increase
efficiency and effectiveness of
our operations?
Director, Operations
How can we get a better
return on our talent, capital,
and assets?
Director, Finance & HR
• Market Share
• Customer Experience
• Acquisition Rate
• Innovation Rate
• Operational Efficiency
• Customer Satisfaction
• Talent Retention
• Inventory Turn
Over 400+ AI Use Cases Across 8 Sectors – Sizing the Prize
Source: PwC Global AI Study: Sizing the Prize – Exploiting the AI Revolution

5. PwC
What are the different AI technologies that can be used?
Machine Learning (ML) ML Ops/Model OppsDeep Learning
Automated ML Digital Twins & RL Responsible AIEmbodied AI
• Natural Language processing
and text mining
• Natural Language generation
• Chatbots and discourse
understanding
• Sentiment & emotion analysis
• Speech-to-text and
text-to-speech
• Convolutional Neural Nets
• Recursive Neural Nets
• Capsule Networks
• Generative Adversarial Networks
• Deep reinforcement learning
• Hybrid learning models
• Regression & classification
• Bayesian learning
• Probabilistic programming
• Anomaly detection
• Optimization techniques
• Support Vector Machines
• Various supervised, semi-
supervised, and
unsupervised techniques
• Big data architecture
• Big and Fast data
• Apache tools
• Cloud computing
• Cloud ML – AWS, GCP, Azure
• Machine Learning deployment
• Microservices architecture
• Docker, Kubernetes
• Agent-based simulation
• Reinforcement learning
• Augmented and synthetic
data generation
• System dynamics modeling
• Discrete event simulation
• Calibration of models
• IoT and Industrial IoT – Edge
computing and Smart sensors
• Drone – Autonomy &
Image analytics
• Robots – Navigation & Learning
• Brain-Machine Interfaces
• Explainable AI
• Beneficial AI
• ‘Black box’ Interpretability
• Maturity models
• Ethics and Law
• AI Governance
• AI Controls framework
• Automated data preparation
• Automated feature engineering
• Automated algorithm selection
• Automated
explanation generation
• Meta-model inference
Natural Language

6. 6
Automated intelligenceAssisted intelligence
Augmented intelligence Autonomous intelligence
Hardwired / specific systems
Adaptive systems
No human in the loopHuman in the loop
+
How is AI being used – with or without humans?

7. PwC
How impactful will the use of AI be?
7
Source: PwC Global AI Study: Sizing the Prize – Exploiting the AI Revolution
AI Impact Index for Financial Services

8. PwC
Over what time horizon would we see the impact?
8
Adoption
Feasibility Usability Full Adoption
Backlash
Market adoption level of AI applications in AWM
Strategic scenario
simulation
Robotic &
Cognitive
Process
Automation
Customer Emotion
Detection*
Automated
marketing &
customer service
Sales practices
monitoring
AI-based
hedge funds*
Robo-
advisor/person
alized financial
planning *
Trend based
product
innovation*
Compliance
Monitoring*
AI in IT
transformation
Source: PwC Global AI Study: Sizing the Prize – Exploiting the AI Revolution
Levelof
sophistication
Automated Intelligence
Assisted Intelligence
Augmented Intelligence
Autonomous Intelligence
Types of AI
LowHigh

9. PwC
Combination of value chain, sophistication of AI, and time horizon by
industry sector
9
Top use cases by value chain and time to adoption stage
C1. Strategic
scenario simulation
C2. Automated
marketing and
customer service
C3. Sales practices
monitoring
C12. Optimize supply
chain
C4. Customer Emotion
Detection
C5. Robotic & Cognitive
Process Automation
(RPA/IPA)
C9. Fraud detection
C10. Attrition modeling
A1. AI-based hedge
funds
A2. Robo-
advisor/personalized
financial planning
C6. Trend-based product
innovation
C13. Inter-organizational
Supply Chain Planning
C7. Compliance
monitoring
C8. AI in IT
transformation
C11. Smart office
NearTerm
(0-3yrs)
LongTerm
(7+yrs)
Med.Term
(3-7yrs)
Time to Adoption Rationale
Time to adoption was determined based on conversations with
industry and AI experts, and accounts for drivers and
inhibitors of adoption such as:
• Current maturity of AI technique; nature
of development challenges
• Barriers to data acquisition
• Regulatory barriers
• Physical implementation limitations
• Dependencies on other players
• Degree of damage if AI fails
Source: PwC Global AI Study
Strategy &
Business model
Enabling Functions
Marketing &
Customer
Sales &
Distribution
Product
Development
Operations &
Service Support
1 2 3 4 5 6
Color of use case - Common in FS (C)
- Asset Wealth Management (A)
Levelof
sophistication
Automated Intelligence
Assisted Intelligence
Augmented Intelligence
Autonomous Intelligence
Types of AI

10. PwC
Augmented intelligence enables underwriting staff to allocate more
time on core activities and make better risk assessment
10
Top Use Case in Insurance: Augmented Underwriting (#I2)
Opportunity Summary Real Examples: Company Highlights
• Cape Analytics (P&C):
- leverages machine learning and geospatial imagery to identify property attributes
at scale allowing insurance companies to provide more accurate quotes to
their consumers.
• P4 Medicine (Life):
- Predictive Preventive, Personalized and Participatory
- Multi-dimensional data of individual health offers insurers better insights that they
can apply to life and disability underwriting
Economic Impact & Adoption to Maturity
• Effort/cost of implementation: High
• Economic impact: High
• Time to adoption: near term (0~3 years)
• Drivers/Inhibitors of Adoption:
- Premium leakage is another profit loss for insurers.
- Faster and (semi-)automated responses to customer underwriting inquiries
Source: Cape Analytics;P4 Medicine
1
2
3
4
5
Data Availability
Personalization
Customer Time SavedUtility Increase
Tech Feasibility
• Challenge:
- Optimization of the financial advisor's
processes when assessing a customer's
risk for insurance contracts
• Opportunity & Products Impacted:
- Expert system for assessing risks
• AI Aspect:
- Augmented intelligence:
Machine learning, NLP, Deep QA,
deep learning, etc..
- Soft-robotics and simulation modeling
to understand risk drivers and
automate underwriting.
• Data Requirements:
- sensor (internet of things – IoT) data,
unstructured text data (e.g., agent or
physician notes), call center voice data
Strategy &
Business model
1
Marketing &
Customer
2
Sales &
distribution
3
Product
Development
4
Operations &
Service Support
5
Enabling
functions
6

11. PwC’s Digital Services
Confidential information for the sole benefit and use of PwC’s client.
Example output
0 months 24+ months
Automate Underwriting (3,4)
Market Risk Management
(3,2)
Value Added Services (2,2)
LTV (2,4)
Segmentation (1,4)
White Space Analysis (2,2)
Attrition (2,3)
Treasury Risk Management
(3,2)
M&A Acquisition Efforts (3,3)
LowHigh
Level of Effort
BusinessValue
New Sales (3,4)
Product Penetration (2,4)
Business Risk Management
(3,2)
Competitive Analysis (2,2)
2
3
4
5
6
7
8
9
10
11
12
13
1
Profitable
Growth
Customer
Insights
Risk
Management
Business
Performance
Shareholder Reporting (3,1)
Finance Automation (4,3)
Predictive Forecasting (3,3)
Operational Excellence (2,2)
Key Performance Indicators
(2,2)
Margin Analysis (3,4)
Self Service Reporting (2,3)
Operational Risk Management
(2,2)
Report Delivery (3,3)
Trans / Vol / RevTracking (1,2)
Definition Standardization
(2,1)
Sales Performance (3.2)
15
17
18
19
20
21
22
23
24
25
26
14
Reporting
Excellence
1
2
3
4
5
6
7
8
10
11
12
13
14
15
17
18
19
20
21
22
2324
25
26
Quick wins with
high value
Ideal future state
capabilities
“Low hanging
fruit”
0 4321
0
1
2
3
4
9
Scenario Planning (4,2)16
16
What does our portfolio of AI use cases look like for Client X?

12. PwC
PwC’s Digital Services
Thank you.
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of member firms of PricewaterhouseCoopers International Limited (PwCIL), or, as the context requires, individual
member firms of the PwC network. Each member firm is a separate legal entity and does not act as agent of PwCIL or
any other member firm. PwCIL does not provide any services to clients. PwCIL is not responsible or liable for the acts
or omissions of any of its member firms nor can it control the exercise of their professional judgment or bind them in
any way. No member firm is responsible or liable for the acts or omissions of any other member firm nor can it control
the exercise of another member firm’s professional judgment or bind another member firm or PwCIL in any way.
Dr. Anand S. Rao
Global AI Lead
anand.s.rao@pwc.com
@AnandSRao
https://www.linkedin.com/in/anandsrao/