Functionalities in AI Applications and Use Cases (OECD)

Functionalities in AI Applications and Use Cases (OECD)

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  Functionalities in AI Applications andUse Cases Dr. Anand S. Rao, Global AI Lead, PwC
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  PwC Experience Center THEMETHOD 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
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  PwC Experience Center THEMETHOD 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
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  PwC Where in thevalue 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
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  PwC What are thedifferent 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
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  6 Automated intelligenceAssisted intelligence Augmentedintelligence Autonomous intelligence Hardwired / specific systems Adaptive systems No human in the loopHuman in the loop + How is AI being used – with or without humans?
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  PwC How impactful willthe use of AI be? 7 Source: PwC Global AI Study: Sizing the Prize – Exploiting the AI Revolution AI Impact Index for Financial Services
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  PwC Over what timehorizon 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
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  PwC Combination of valuechain, 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
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  PwC Augmented intelligence enablesunderwriting 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
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  PwC’s Digital Services Confidentialinformation 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?
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  PwC PwC’s Digital Services Thankyou. © 2020 PwC. All rights reserved. Not for further distribution without the permission of PwC. “PwC” refers to the network 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/