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AI Foundations Course Module 1 - An AI Transformation Journey

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The chances of successfully implementing AI strategies within an organization significantly improve when you can recognize where your organization is on the maturity scale. Over this course, you will learn the keys to unlocking value with AI which include asking the right questions about the problems you are solving and ensuring you have the right cross-section of talent, tools, and resources. By the end of this module, you should be able to recognize where your organization is on the AI transformation spectrum and identify some strategies that can get you to the next stage in your journey.

To find additional videos on AI courses, earn badges, join the courses at H2O.ai Learning Center: https://training.h2o.ai/products/ai-foundations-course

To find the Youtube video about this presentation: https://youtu.be/PJgr2epM6qs

Speakers:
Chemere Davis (H2O.ai - Senior Data Scientist Training Specialist)
Ingrid Burton (H2O.ai - CMO)

Published in: Technology
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AI Foundations Course Module 1 - An AI Transformation Journey

  1. 1. AI Foundations Module 1: An AI Transformation Journey Session 1: An AI Transformation Journey Primer
  2. 2. 2 What you can expect in this session 01 Introduction 02 What is AI and Why Is It Important Now? 03 The AI Journey & The Keys to Unlock AI 04 AI in Action: Real World Use Cases 05 Summary & What’s Next
  3. 3. Why We Are Here Module 1: An AI Transformation Journey Session 1: An AI Transformation Journey Primer Part: 1
  4. 4. 4 AI & ML Foundations AI Foundations ● Intro to Key AI Concepts ● No prior AI knowledge or background necessary ● No technical or coding experience necessary ● Exercises: Non-Technical and introductory ML Foundations ● Applied AI Concepts ● Some experience with Python or R would be helpful to success ● Exercises: Technical and deeper In both courses you get access to H2O.ai experts and community makers! You can earn a badge for AI & ML Foundations by successfully completing the assessments at the end of each module (not required). Session: X
  5. 5. 5 Module 1: An AI Transformation Journey Session 1: An AI Transformation Journey Primer Session 2: Shifting to the Next Step in the AI Transformation Journey Study Group Session 3: AI Transformation and Covid-19 Module 2: Demystifying AI Module 3: Machine Learning Foundations AI Foundations Overview You Are Here Interested in knowing the full schedule for the AI Foundations course? View the schedule on the community learning site
  6. 6. 6 You are in Good Company
  7. 7. 7 Technical Background & Industry
  8. 8. 8 AI Projects & Challenges Not Currently Working on an AI Project 59%
  9. 9. What is Artificial Intelligence? Module 1: An AI Transformation Journey Session 1: An AI Transformation Journey Primer Part: 2
  10. 10. 10 Artificial intelligence (AI) • A field of computer science that provides the ability for a computer to learn and reason like humans using several available techniques. • It is an important field for those who want to extract meaningful insights from massive amounts of data in a timely and systematic manner AI & The Role of Machine Learning AI today is largely powered by Machine Learning (ML) • ML happens when a computer can take lots of data (examples) and learn patterns from it to make predictions on new data based on those learned patterns.
  11. 11. 11 AI ML NLP Expert Systems RL DL AI is more than just Machine Learning Math Optimizations Grammars Knowledge and Graph Systems Computer Vision Robotics H2O.ai’s AI Glossary Module: 3
  12. 12. 1212 AI Transformation Why Now? 1950s 1980s 2000s 20202010s Digital transformation AI transformation • Math • Statistics • Algorithms • Expensive computing • Early AI in research • Expert Systems • Rules Engines • CPU and storage enterprise wide • WWW • Search • IoT begins • Big Data (Hadoop) • Rise of GPUs for AI • Efficient storage • Faster compute • IoT miniaturization • Networks everywhere • Data science skills • Public cloud emerges Businesses are ready for an AI transformation Perfect storm ✔ Open source algorithms & frameworks ✔ High performance and cost-effective compute & storage ✔ Advanced data science skills available ✔ More data than ever before ✔ AI can solve complex business problems ✔ Fast on ramp & cloud economics Algorithms, Data and Compute become Commodities
  13. 13. 13 AI Spans Industries and Use Cases Wholesale / Commercial Banking • Know Your Customers (KYC) • Anti-Money Laundering (AML) Card / Payments Business • Transaction frauds • Collusion fraud • Real-time targeting • Credit risk scoring • In-context promotion Retail Banking • Deposit fraud • Customer churn prediction • Auto-loan Financial Services • Early cancer detection • Product recommendations • Personalized prescription matching • Medical claim fraud detection • Flu season prediction • Drug discovery • ER and hospital management • Remote patient monitoring • Medical test predictions Healthcare and Life Science • Predictive maintenance • Avoidable truck-rolls • Customer churn prediction • Improved customer viewing experience • Master data management • In-context promotions • Intelligent ad placements • Personalized program recommendations Telecom • Funnel predictions • Personalized ads • Fraud detection • Next best offer • Next best action • Customer segmentation • Customer churn • Customer recommendations • Ad predictions and fraud Marketing and RetailMarketing and Retail
  14. 14. Confidential14 Examples of the impact of AI Transformations …real-time individualized experience …dynamic yield optimizationBreak then fix …personalized quality of serviceCustomer service silos …personalized healthcareMass treatment …real-time trade surveillanceDaily risk analysis Mass branding WITH AIPRE-AI AI allows organizations to shift interactions from… Reactive Post Transaction Proactive Pre Decision
  15. 15. The AI Journey & The Keys to Unlock AI Module 1: An AI Transformation Journey Session 1: An AI Transformation Journey Primer Part: 3
  16. 16. Confidential16 AI Business Value: A Journey in Four Phases 1 2 3 4Potential Operational Strategic Data-Driven Enterprise AI Journey Awareness & Interest Evaluate Business Value Technical Evaluation Point Deployment Point Production Enterprise Deployment Enterprise Production Modern Data Architecture Industry Leadership Session: 2
  17. 17. 17 Who is on the team? Business leader, data scientists, IT professional Determine the problems you want to solve with metrics (time, money, # of customers, etc) Determine where you have data, need data, and can use technology to find answers and predictions. Find answers efficiently. Learn from others in the data science community Ask the Right Questions Data & Technology Community Create a Data Culture Understand and explain the models. Use leading edge technologies to guard for bias, explain a model, and present this to regulators Trust in AI 2 1 3 4 5 5 Keys to unlock AI
  18. 18. Confidential18 Machine learning is as much a cultural transformation as a business transformation. 1Who’s On Your Team? IT Leader Business Leader Data Scientist Find the right talent within. Data. Data. Data.
  19. 19. 19 Data is the fuel for AI TEXT IMAGES VIDEO AUDIO
  20. 20. 20 • Basing decisions on data rather than intuition • Data-driven decisions + big data technologies = Improved business performance Why Data-Driven Decision Making Is Vital Discover new meaning in data Predictive & actionable insights Build confidence in decision-making Communicate data stories for impact Create valuable Data Products
  21. 21. Confidential21 AI Enables Data Products To Be Created That… Provide insight Increase revenue Open Markets Improve OperationsCreate new features Data
  22. 22. Confidential22 Saving Lives Supply Chain Optimization Digital Marketing Insurance Underwriting Fraud Detection Customer ChurnModel BuildingDebt Scoring Propensity to Lease Bad credit detection + 700% Marketing Campaign Effectiveness $ 20M/year Savings + 2X Effectiveness in Identification 25% Time Reduction in Planning 10% Increase in Sepsis Detection $ 10M/month Debit Reduction $ 1.5M/month Call Center Savings 50% Time Reduction in Model Building 25% Increase Customer Churn Prediction 8% More Accurate Predictions of Bad Credit Winning with AI
  23. 23. Confidential23 Confidential23 Talent is Scarce Needs Reality Session: 2
  24. 24. Confidential24 AI Teams Can Be Organized Differently Centralized Decentralized Hybrid
  25. 25. Confidential25 Executive Sponsorship Needed for AI to Succeed Centralized Organization – Hub & Spoke model where the data science team supplies analytics to multiple business units AI Teams
  26. 26. Confidential26 Executive Sponsorship Needed for AI to Succeed Decentralized Organization – Each business unit has its own data science capabilities
  27. 27. Confidential27 Executive Sponsorship Needed for AI to Succeed Hybrid Organization – Contains both a centralized AI team, but each business unit has its own AI capabilities AI Team
  28. 28. Confidential28 Determine the problems you want to solve with metrics. 2Ask the Right Questions Want to save time? Want to save money? Increase customer base?
  29. 29. 29 Turning Business Questions to ML Problems   How Much • How much will each customer invest? • How much will each customer invest each month? • What will the cost of stock X be? • How will the exchange rate change next week? Which One • Who will default on a loan? • Which customer will churn? • Which customers can I upsell? • Who will pre-pay their mortgage? • Which product is a customer likely to buy? • How does a customer feel about a product or company? Grouping • How should we segment customers? • What topics are in our customer feedback? • Based on similar customers, what is the next best offer? Module: 3
  30. 30. Confidential30 Learn from others in the data science community 3Communicate. Community. Share. Learn from others. Participate.
  31. 31. Confidential31 Build or Buy?Open Source? Cloud on on-prem? Data. 4Technology Considerations Determine where you have data, need data, and can use technology to find answers and predictions. Find answers efficiently.
  32. 32. Confidential32 Rich AI Ecosystem - Too Many Choices? https://miro.medium.com/max/1400/0*j1pqHqSkGg-sS2x4.png
  33. 33. Confidential33 Rich AI Ecosystem - Too Many Choices? Databases Big Data/Distributed Computing Cloud Computing Programming Languages Business Intelligence Data Science/Analytics/AI • Typical frontline store of data (relational, graph, etc) • May be hosted in cloud if volume of data warrants it • If data is too big to be useful for accessing it you can use big data platforms for distributed, parallel, high-performance computing • In terms of accessing, isolating, cleaning, transforming data, these are the big 3. • Python + R are consistently used for DS & modeling • Most common resources for descriptive statistics and dashboarding (specialize in descriptive stats) • For predictive & advanced analytic insights use Data Science/AI platforms (and py+R) to apply the highest quality methods. • Cloud computing may be needed to run heavy math for these models. Module: 5 ML Foundations ML Foundations
  34. 34. Confidential34 Regulations.Explain. Document. Humans. 5Trust in AI Understand and explain the models. Use leading edge technologies to guard for bias, explain a model, and present this to regulators
  35. 35. Confidential35 How Can You Build Trust in AI? Data Scientist Why did they do that? Why not something else? When will customer churn? When will customer not churn? When can I trust you? What if an attribute changed? How do I correct an error? Training Data Learning Function Training Model Output / Scores Customer Churn Customer Activity Learning Process Module: 6
  36. 36. Confidential36 Why Does Machine Learning Explanation Matter? I understand why I understand why not I know when customer will churn I know when customer will not churn I know when to trust ML model When can I trust you? I know what influences the prediction I know why you erred Training Data explainable model Explanation Interface Customer Churn Customer Activity New Learning Process Business Analyst
  37. 37. AI In Action: Real World Examples Module 1: An AI Transformation Journey Session 1: An AI Transformation Journey Primer Part: 4
  38. 38. Confidential38 AI is a Journey! For You and For Enterprises
  39. 39. Confidential39 AI Journey at PwC 3. Digital Transformation Digital Transformations enabled PWC to generate new, larger insights with more dynamic data 1. Talent Challenges PWC needed a rapid & innovative approach to attrittion and upskilling 2. Manual Limitations PWC Auditors were stuck doing far too many repetitive and redundant tasks, that were prime for automation 4. The Future + AI PWC wanted to leverage the foundation built through digital to identify high-value, innovative use cases leveraging AI alongside H2O
  40. 40. Confidential40 GL.ai 2015-2017 • Co-innovation with H2O.ai • Saved months or even years pinpointing errors, reducing risks and finding fraud immediately • Enables PWC experts to work on high risk situations, not mundane tasks A Multi-Ye ar AI Journey
  41. 41. Confidential41 cash.ai 2018 to today A Multi-Year AI Journey • Driving audit quality, accuracy and reliability with intelligent automation and AI • Pilots are live today • PwC is re-imagining audit • Finds anomalous behavior in near real-time
  42. 42. Confidential42 Confidential42 Empowering PwC to be an Award-Winning AI Company “The reason this is such a brilliant tool is its ability to look at different risks, in context, at the same time. For example, it would be uneconomical for an auditor to look at every single user’s pattern of activity to decide what’s unusual. With GL.ai, the algorithms do it for us.” “ Gary Rapsy Global Assurance Disruption and Innovation Leader at PwC “Part of the reason for wanting to work with H2O.ai is the passion and purpose around advancing finance and democratizing AI for Finance.” “ Laura Needham Partner, PwC UK
  43. 43. Confidential43 Wells Fargo has an Enterprise-wide AI Initiative Underway 100+ Data Scientists on Driverless AI across business units Trust Using MLI to explain results to consumers and regulators “H2O.ai has the best and fastest GLM. They listen to us, and are addressing our needs. I am very impressed.” Agus Sudjianto EVP, Head of Corporate Model Risk Wells Fargo Anti-money laundering Predictive Banking Consumer 360 Personalized Banking Transactions Financial Decision Making Consumer spending insights Credit Card Fraud Data Quality Use Cases “ Time Savings Decreased deployment time
  44. 44. Confidential44 A Decade of Data Science at Nationwide Insurance 45+ Centralized data science team using H2O.ai Millions $ Annual savings “H2O.ai provides us the power and flexibility we need to solve business problems with machine learning. We are able to do more with less and do it faster. Our results are proof of the power of AI in action.” Shannon Terry Vice President, Predictive Analytics Customer churn Customer retention Call routing Risk segmentation Business segmentation Fraud Underwriting Customer expansion Customer 360 Use Cases “ 25 Billion Scored from 500K models instantiated in 10 years
  45. 45. Confidential45 Capital One Transformation Yielding Results Customer Satisfaction Using AI to streamline customer calls and answer questions bette New Business Established a new revenue stream with new data products “H2O.ai worked closely with Capital One on not only identifying opportunities in our business, but they were a true partners in transforming our business and leading us to the path of data and AI transformation.” Karthik Aaravabhoomi Former Capital One Transformation Leader Cybersecurity Anti-money laundering Predictive Banking Consumer 360 Personalized Banking Transactions Financial Decision Making Consumer spending insights Credit Card Fraud Data Quality Use Cases “ $ Tens of Millions Enhanced and personalized transactions saving millions of dollars
  46. 46. Confidential46 Major US Telecom Creating a Model Factory 100+ Models in production in a model factory Trust Using MLI to explain results to consumers and regulators “Driverless AI is giving amazing results in terms of feature and model performance.” Customer subscriber churn Recommendation engines Network anomaly detection Fraud detection Campaign optimization Customer propensity Next best offer Tower placements (5G) Predictive Maintenance Use Cases “ Time Savings Distributed data science team getting results faster
  47. 47. Confidential47 Leveraging AI for Bond Pricing 5 50+ Leverage AI to buy personal loans for funds and separate accounts “H2O Driverless AI speeds up machine learning by automating our data science workflow. With the new recipe capability, we can extend and customize the platform to meet our needs, such as estimating the prepayment risk of underlying loans in fixed-income assets like mortgage-backed securities. Driverless AI is helping us accelerate our AI journey.” “ Chris Pham Senior VP Data Management and Data Science Franklin Templeton Customer segmentation Next Best Offer Loan Default Prediction Buying Pattern Prediction Exchange Rate Prediction Investment Prediction Customer Sentiment Use Cases Business Groups Using AI Data Scientists on Driverless AI Millions $
  48. 48. Confidential48 Using AI to Deliver Fresh Fruit in the Fastest Possible Way Speed 2 Leverage AI to find the fastest route to reduce spoilage “We are getting great results with H2O Driverless AI. What once took us 3 to 5 months using traditional data science methods, can now be done in 3 to 5 weeks without having to add any additional data scientists to the team.” “ Gonzalo Bustos Head of Data Analytics Hortifrut Supply chain transportation optimization Perishable predictions Reducing claims Use Cases Reduction of modeling time 3 to 5 months to 3 to 5 weeks Data Scientists on Driverless AI Millions $ PRODUCER AND DISTRIBUTOR OF 25% OF THE WORLD’S BERRIES
  49. 49. Confidential49 Protecting Your Assets with AI “After evaluating several solutions in our search for the ideal AI platform, we chose H2O.ai because it provides us with the transparency we needed into our machine learning processes, much more flexibility than the other tools we evaluated, and the strongest machine learning explainability capabilities on the market. H2O.ai provides new avenues of innovation and allows us to build quality and insightful ML tools for our business stakeholders.” “ Andrew Langsner Underwriting Customer experience Claim evaluations Inventory stocking Loss prevention Lifetime value of a customer Use Cases Engagement Increased customer satisfaction (both the insured and the retailers) Trust Using MLI to explain results to consumers and regulators $ Millions Increased insurance policies with both consumers and retailers
  50. 50. Confidential50 Improving Leads to Leases with AI 95% 85% Monthly savings on marketing expenses for Real Estate clients “Driverless AI helped us gain an edge with our Intelligent Marketing Cloud for our clients. AI to do AI, truly is improving our system on a daily basis.” “ Martin Stein Chief Product Officer G5 COVID-19 impact on senior housing Sentiment analysis Customer call center predictions Use Cases Level of accuracy of leads to leases Leasing agents now have qualified leads 85% of the time $1.5M/ month REAL ESTATE MARKETING
  51. 51. Confidential51 Driving Marketing Engagement with AI 700% 11% Model training time savings “Driverless AI has made it easy to try AI solutions in our own environment and context. It allowed us to quickly see the benefits in our domain. Driverless AI has cut down the overall model development time in about half. ” “ Scott Pete Director of Analytics and Insights Predicting churn Fraud detection Next best experience Brand marketing campaigns Use Cases Marketing campaign cost savings and effectiveness ROI on marketing and loyalty programs 25-30% BRAND LOYALTY AND MARKETING
  52. 52. What’s Next? Module 1: An AI Transformation Journey Session 1: An AI Transformation Journey Primer Part: 5
  53. 53. Confidential53 • AI is not only ML & doesn’t exist without data • AI Transformation requires a journey through the phases of maturity: – Potential – Operational – Strategic – Data-Driven • Unlocking the value of AI Requires: – Resources: Data & Talent – Asking the right question for the problem you are solving – Communication & Community – Getting the right technology in place – Building trust in the use of AI What We’ve Covered So Far Recording will be posted w/in 2 days
  54. 54. Confidential54 1. The next session Shifting to the Next Step in the AI Transformation Journey will be held on Thursday July 2, 2020 @ 7:00AM PDT 2. There’s a special session on Monday July 6, 2020 @7:00AM PDT on AI Transformation Stories related to Covid-19. Upcoming Sessions
  55. 55. Confidential55 Confidential55 Quizzes & Study Groups • Each session within a module will have a small quiz to complete and all quizzes for that module will be due before the next module starts. • There are 2 options available for you to ask additional questions or get assistance on AI concepts covered in the sessions: – A Study Group for each Module will be held on Saturdays @ 7:00AM PDT – Ask Me Anything will be held on Sundays @7:00AM PDT • Reminder: Don’t forget to complete Quiz 1: An AI Transformation Journey by Tuesday July 7, 2020 to earn your badge!
  56. 56. Resources
  57. 57. Confidential57 Confidential57 Additional Resources H2O.ai’s AI Glossary

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