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Artificial Intelligence use cases, SAPInsider Prague

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Artificial Intelligence use cases, SAPInsider Prague

  1. 1. Timo Elliott, SAP Artificial Intelligence Meets Digital Transformation: Examples from the Front Lines
  2. 2. 1© 2018 SAP SE or an SAP affiliate company. All rights reserved. AI and machine learning overview Automation examples Internet of things examples Chatbot examples Customer service examples Machine vision examples Other examples Wrap-up Agenda
  3. 3. AI and Machine Learning Overview
  4. 4. 3© 2018 SAP SE or an SAP affiliate company. All rights reserved. Introduction: Learning by doing Learning video games Learning to walk, jump, and run
  5. 5. 4© 2018 SAP SE or an SAP affiliate company. All rights reserved. Artificial intelligence AI is a “sociotechnical construct” indicating machine capabilities that solve complex tasks that were recently only possible by humans (equally well or better) Technical disciplines that solve business problems through the extraction of knowledge from data. Deep Learning Machine Learning Data Science Big Data Advanced Analytics Predictive Analytics Data Mining
  6. 6. 5© 2018 SAP SE or an SAP affiliate company. All rights reserved. How enterprise data is transformed into business value with machine learning Input Machine Learning Output Train model Prepare data Apply model Capture feedback Text Image Video Speech … and more Services (e.g., invoice processing, profile matching) … and more Applications (e.g., Cash Application)
  7. 7. 6© 2018 SAP SE or an SAP affiliate company. All rights reserved. Machine learning everywhere Source: “What’s Now And Next In Analytics, AI, And Automation:” (Briefing Note, May 2018) McKinsey & Company Machine learning has broad potential across industries and use cases “the value of the potential benefits of automation – calculated as a percentage of operating costs – could range from between 10– 15% for a hospital emergency department to 25% for aircraft maintenance, and to more than 90% for mortgage origination.”
  8. 8. 7© 2018 SAP SE or an SAP affiliate company. All rights reserved. Machine learning automation is a huge opportunity “In 2018, half a billion users will save two hours a day thanks to AI-powered tools” Gartner “About 30% of the activities in 60% of all occupations could be automated” McKinsey Sources: Gartner, McKinsey, McKinsey
  9. 9. 8© 2018 SAP SE or an SAP affiliate company. All rights reserved. 60% Of companies see ML as critical for competitive advantage $18B Enterprise Machine Learning Market by 2020 94% Transactional Enterprise Digital Enterprise Intelligent Enterprise Of human tasks will be automated by 2025 97% Image recognition accuracy (human: 95%) 95% Speech recognition accuracy (human: 94%) Human repetitive tasks Enterprise system Human high value tasks (augmented by AI) Automation give more power to humans Source: SAP CSG analysis, McKinsey Quarterly Report July 2016, Google PR, Microsoft PR, SAP Market Model
  10. 10. 9© 2018 SAP SE or an SAP affiliate company. All rights reserved. Reimagine your value chain with Machine Learning • Trend Analysis (Face, Age, Gender, Emotion, Apparel) • Personalized Design Design • Learning Recommender • Synchronous Translation of training content • Career Path Recommender Human Resources • Predictive Maintenance • Quality Inspection • Optimal Planning & Scheduling Operations • Cash Application • Accounts Payable • Remittance Advices • Predictive Accounting • SAP Business Integrity Screening Finance • Image-based Purchasing • Goods & Services Classification • Supplier Risk Assessment Inbound Logistics • Routing Optimization • Supply Chain Resilience • Last-mile Delivery Outbound Logistics• Brand Impact • Social Media Analysis • Customer Behavior Segmentation Marketing • Conversational AI • Service Ticketing • Customer Support • Solution Recommender Sales & Service DATA DECISIONS ACTIONS
  11. 11. 10© 2018 SAP SE or an SAP affiliate company. All rights reserved. Machine learning embedded across the SAP portfolio Finance Marketing Sales Service Human Resources Procurement Supply Chain Platform Cash Application Accounts Payable Predictive Accounting … …Brand Impact Customer Behavior Segmentation … Service Ticketing Customer Retention Sales Forecasting CoPilot … … Goods & Services Classifier … Solution Recommender Profile Completeness …Resume Matching Learning Recommender openSAP Translation Financial Advising Forecasting (IBP) Stock in Transit Available now Wave 2 Wave 3 Machine Learning Foundation …Model Training Infrastructure
  12. 12. 11© 2018 SAP SE or an SAP affiliate company. All rights reserved. Build the Intelligent Enterprise Machine Learning Roadmap Excerpt Learning Recommender Job Analyzer Employee Self Service Bot Total Workforce Insights Resume Matching Manager & Administrator Self Service Bot Career Planning "People like me" Knowledge Bots Payroll Fraud Detection SAP Fieldglass Live Insights Job Matching for Candidates Support and Productivity Bots Job Seeker Resume Ranking Intelligent Customer Experience Suite Lead Intelligence Customer Retention Ticket Intelligence Product & Offer Recommendation Influencer Map & Deal Finder Multi-Touch Customer Attribution Contextual Merchandizing Self-Writing Expense Computer Vision Receipts Anomaly Detection AI Expense Approvals Invoice Digitization AI Invoice Processing Itinerary Capture Chatbot BookingsRisk Impact Predictions Automated Duty of Care Proactive Assistant Semantic Contract Repository Item Recommendation Self-Service Contracts Attribute Normalization Semantic Search Item Normalization Sourcing Optimization Sourcing Recommendation Job Matching Timesheet Anomaly Detection Program Office Guidance Job Normalization Statement of Work Builder Contract Consumption SAP Tax Compliance Smart Automation Payment Block- Cash Discount at Risk Smart Alerts for Real Spend and P&L Analysis Demand-Driven Replenishment Adjustment Stock in Transit Sales Performance Prediction Cash Application Predictive Engineering Insights Predictive & Prescriptive Maintenance Demand Sensing Predictive Overall Equipment EffectivenessPredictive Quality Management Smart Worker Enablement on Shop Floor Supply Chain Segmentation Advanced Forecast AccuracyDIGITAL SUPPLY CHAIN AND MANUFACTURING Machine Learning Foundation Conversational Artificial Intelligence Data Science Platform SAP Concur SAP Ariba SAP C/4HANA SAP S/4HANA® Technology SAP SuccessFactors SAP Fieldglass
  13. 13. 12© 2018 SAP SE or an SAP affiliate company. All rights reserved. SAP Hybris machine learning solutions Key innovations Sales Deal Intelligence Lead Intelligence Imagine Intelligence by Ricoh Deal Influencer Map Account Intelligence* Predictive Ordering* Predictive Forecasting* Sales Assistant* Service Ticket Intelligence Conversational Bot API Similar Ticket Recommender* Solution Recommender * Parts Recommender* Supervisor Insights* Service Assistant* Commerce Personalized CX Contextual Merchandizing Conversational Bot* In-Store Assistant* Marketing Product and Offer Recommender Best Channel and Sending Time Affinity Scoring Sentiment Analysis Customer Attribution Customer Journey Insights* Smart Campaigns* Brand Intelligence* Customer Retention* Behavior Segmentation* SAP Hybris This presentation and SAP‘s strategy and possible future developments are subject to change and may be changed by SAP at any time for any reason without notice. This document is provided without a warranty of any kind, either express or implied, including but not limited to, the implied warranties of merchantability, fitness for a particular purpose, or non-infringement. * Prototype / Planned This is the current state of planning and may be changed by SAP at any time.
  14. 14. 13INTERNAL© 2018 SAP SE or an SAP affiliate company. All rights reserved. ǀ
  15. 15. 14INTERNAL© 2018 SAP SE or an SAP affiliate company. All rights reserved. ǀ Internet of Things Big Data Data Network Blockchain Analytics Machine Learning SAP Leonardo Technologies SAP Leonardo digital innovation system SAP Cloud Platform Multi-Cloud Infrastructure Microservices | Open APIs | Flexible Runtimes | Integration SAP Data Center Data Management SAP HANA SAP Data Hub SAP Vora Other SAP Open Source Storages SWIFT AWS S3 Hadoop …
  16. 16. 15INTERNAL© 2018 SAP SE or an SAP affiliate company. All rights reserved. ǀ SAP Leonardo machine learning: Portfolio of capabilities Data Science Platform & Tools Developer (Citizen)DataScientist Text/Document Services (e.g., Sentiment Analysis) Image/Video Services (e.g., Image Classification) Speech/ Audio Services (e.g., Voice Recognition) Structured Data Services (e.g., Time Series Analysis) Business Services (e.g., Service Ticket Intelligence) Graph Services (e.g., Link Recommender) Predictive Services (e.g., Forecasting) Intelligent Services Data Exploration Data Integration Data Preparation End-to-End Automation In-Application Deployment Lifecycle Management ML Model Creation Model Storage Production Readiness TensorFlow Integration Integration of machine learning into existing applications (e.g., SAP Analytics Cloud, SAP Business Integrity Screening, SAP Cash Application) Standalone Machine Learning Applications (e.g., SAP Brand Impact) Intelligent Apps SAP Cloud Platform SAP HANA Platform EndUser Conversational Interfaces (SAP CoPilot)
  17. 17. 16INTERNAL© 2018 SAP SE or an SAP affiliate company. All rights reserved. ǀ SAP’s vision for enterprise machine learning SAP Cloud Platform and SAP HANA Do the ImpossibleAutomate Knowledge Work  Image-based Ariba commerce  Contextual Concur travel concierge  Self-driving customer service  Conversational sales bots  Customer retention insights  Vision-enabled manufacturing  Contextual logistics  Video-aware marketing  Visual store execution  Drone and satellite-based asset management  Transformational HR services  Lights out finance operations Create your own intelligent infrastructure SAP Leonardo Machine Learning
  18. 18. 17INTERNAL© 2018 SAP SE or an SAP affiliate company. All rights reserved. ǀ SAP Leonardo machine learning foundation services portfolio Tabular Image Text Audio/ Video General availability*  Time series change point detection  Time series forecasting (AA algorithm)  Clustering  Key influencer analysis  Outlier detection  Recommendation  What-if analysis  Image classification  Image feature extraction  Earth observation analysis  Topic detection/keyword extraction Alpha  Time series forecasting (R algorithms)  Similarity scoring  Product image classification  Machine translation  Document feature extraction  Language detection  Product text classification Road map  Time-to-failure forecasting  Association rule learning  Image segmentation  Face detection  Document optical character recognition  Image text extraction  Image NER/extraction  Apparel detection  Sentiment analysis  Named entity recognition  Text classification  Hate speech detection  File-to-text conversion  Speech-to-text  Text-to-speech  Voice recognition (speaker identification)  Video object segmentation  Video classification  Video human action recognition NOW AVAILABLE on the SAP API Business Hub: SAP Leonardo ML – Functional Services
  19. 19. Automation Examples
  20. 20. 19© 2018 SAP SE or an SAP affiliate company. All rights reserved. 40% 70% 94% Invoice matching
  21. 21. 20© 2018 SAP SE or an SAP affiliate company. All rights reserved. Training recommendations
  22. 22. 21© 2018 SAP SE or an SAP affiliate company. All rights reserved. Blurring of operations and analytics: Translytics/HTAP/OLTAP “The translytical data platform creates new business opportunities” Forrester Q4 2017 Real-time analytics = fast enough to make a real difference in a business process The Forrester Wave™: Translytical Data Platforms, Q4 2017 November 28, 2017
  23. 23. 22© 2018 SAP SE or an SAP affiliate company. All rights reserved. Predictive finance Actual Prediction Using the power and flexibility of in-memory architectures, create a separate ledger for predictions
  24. 24. 23INTERNAL© 2018 SAP SE or an SAP affiliate company. All rights reserved. ǀ
  25. 25. 24 LAB PREVIEW Building blocks T€ Posted actual EBIT Presumed margin from incoming orders Predicted Recurring entries (e.g., salary postings) Predicted extraordinary effects Predicted closing (e.g., currency remeasurement) EBIT prediction 50 40 30 20 10 - - + Predictive Close – predicting month end KPIs within the period Status as of: 15. September Predicted: figures derived from machine learning algorithms based on prior patterns Presumed: for each incoming sales order in the system, calculate revenue and costs as if the order had been issued and invoiced
  26. 26. 25 See the incoming orders used to calculate the presumed profit Revenue Margin See presumed profit, revenue, etc. by any company, product segment, etc See the list of presumed transactions that are used to calculate these values …
  27. 27. 26 See the details for each presumed transaction Presumed revenue for region Presumed costs for region Presumed margin for region Filter and view by company, period, segment, product, etc Detailed list
  28. 28. 27 Assistance Systems (SAP CoPilot, Robotic Process Automation, Smart alerts, Data Quality Assurance) Financial planning and analysis Accounting and financial close Treasury management Financial operations Governance, risk, and compliance for finance  SAP Predictive Analytics Library  Predictive Planning, Budgeting and Forecasting  P&L Prediction  Cost Object Controlling for IoT  SAP Closing Cockpit  Predictive Accounting  Invoice and Goods Receipt Account Reconciliation  Automated Accruals and Depreciations (incl. IoT)  Cash and Liquidity Forecasting (incl. market knowledge, market shift, historical FX)  Intelligent Hedging (Analyzing stocks, funds, insurance, derivate products )  Trade Finance  SAP Cash Application  Service Ticket Intelligence for Shared Service Framework  Remittance/ Payment Advice  Dispute Proposal/Cash Collections Service  Customer Payment and credit scoring Digital Payments (BitCoin)  SAP Business Integrity Screening  Predictive Detection Methods and Risk Scores Predictive Scenarios (Forecasting by key KPIs e.g. Accounts Receivables Mgt., Accounts Payables Mgt. and Cash Discount Analysis, Alerts) S/4HANA Finance: The Foundation for latest automation solutions Available Prototype Future Direction Idea Colour Coding Subject to Change
  29. 29. 28© 2018 SAP SE or an SAP affiliate company. All rights reserved. Artificial intelligence + analytics = “smart data discovery” Preparing data Finding patterns Sharing and operationalizingNatural language interfaces
  30. 30. 29© 2018 SAP SE or an SAP affiliate company. All rights reserved. Automatic discovery
  31. 31. 30© 2018 SAP SE or an SAP affiliate company. All rights reserved. Smart grouping
  32. 32. 31© 2018 SAP SE or an SAP affiliate company. All rights reserved. Conversational analytics — search to insight
  33. 33. Internet of Things Examples
  34. 34. 33© 2018 SAP SE or an SAP affiliate company. All rights reserved. Predictive maintenance
  35. 35. 34© 2018 SAP SE or an SAP affiliate company. All rights reserved. Predictive Maintenance Kaeser Compressor, a global leader in air compressors ≈€500 million, 4,800 employees, 50 countries, partners in additional 60 countries
  36. 36. 35© 2018 SAP SE or an SAP affiliate company. All rights reserved. Modeling Example E.g. Total energy consumption • Aggregation of 10 sec values • Calculation of typical consumption patterns • Pattern associated with each compressor and day Repeat for temperature, pressure, vibration, etc.
  37. 37. 36© 2018 SAP SE or an SAP affiliate company. All rights reserved. Predictive Examples Model combines sensor readings and ERP data (location, type of usage, last service, etc.) • Status alerts: “Oil change / oil analyze / no action” • Predict machine failure 24 hours in advance
  38. 38. 37© 2018 SAP SE or an SAP affiliate company. All rights reserved. High-Level Technical View Predictive Model (in-memory) Long-term disk storage User Interfaces CRM ERP Event Stream Processing all sampled Customer Field Svs Sales R&D DW
  39. 39. 38© 2018 SAP SE or an SAP affiliate company. All rights reserved. 38
  40. 40. 39© 2018 SAP SE or an SAP affiliate company. All rights reserved. Benefits Customers • Less downtime • Decreased time to resolution • Optimal longevity and performance Kaeser • More efficient use of spare parts, etc • New sales opportunities • Better product development “We are seeing improved uptime of equipment, decreased time to resolution, reduced operational risks and accelerated innovation cycles. Most importantly, we have been able to align our products and services more closely with our customers’ needs.” Kaeser CIO Falko Lameter
  41. 41. 40© 2018 SAP SE or an SAP affiliate company. All rights reserved.
  42. 42. 42© 2018 SAP SE or an SAP affiliate company. All rights reserved. Swiss Railways problem: High peak demand for electricity Peaks of <1 minute can require a new power band
  43. 43. 43© 2018 SAP SE or an SAP affiliate company. All rights reserved. How it works Railway electricity grid control SAPHANAEnergy ManagementSystem — Plausibilitycheck — Peakdetection — Trigger signalgeneration — HMI (Human MachineInterface) — Datalogging Power demand management platform Momentaneousnet demand Triggersignalsfor off-/-onswitching Pool of flexibly switchable power OFF ON Enable Disable Enable Pool of flexibly switchable power Telementryplattform for train car heaters Telementryplattform for point-heaters SAP Streaming Analytics Streams the power data real-time to SAP HANA
  44. 44. 44© 2018 SAP SE or an SAP affiliate company. All rights reserved. Architecture IBM WebSphere Message Broker Energy Management System RemoteControlof Consumers SAP HANA Platform XSA Engine TASE.2 interface control analysis Measurement data (power demand) Trigger signals: to rail vehiclesMQ,Rest HANA DBSmart Data Streaming Logic Data management Signal Handling MQ,Rest FZPF-Z (central system) Internet Browser (SAP UI5 on Laptop) LSS-CH (central system) & railroad switches
  45. 45. 45© 2018 SAP SE or an SAP affiliate company. All rights reserved.
  46. 46. 46INTERNAL© 2018 SAP SE or an SAP affiliate company. All rights reserved. ǀ Predictive maintenance — for humans!
  47. 47. 47INTERNAL© 2018 SAP SE or an SAP affiliate company. All rights reserved. ǀ Drone image analysis
  48. 48. Chatbot Examples
  49. 49. 49© 2018 SAP SE or an SAP affiliate company. All rights reserved. SAP CoPilot SAP CoPilot is an Enterprise Digital Assistant — what Siri, Alexa, and Cortana are to consumers.
  50. 50. 50INTERNAL© 2018 SAP SE or an SAP affiliate company. All rights reserved. ǀ
  51. 51. 51© 2018 SAP SE or an SAP affiliate company. All rights reserved. Service Chatbot
  52. 52. 52© 2018 SAP SE or an SAP affiliate company. All rights reserved. Finance Cockpit
  53. 53. 53© 2018 SAP SE or an SAP affiliate company. All rights reserved. Conversation is the new UI: Finance Chatbot
  54. 54. 54© 2018 SAP SE or an SAP affiliate company. All rights reserved. Customer examples of chatbots in production
  55. 55. 55© 2018 SAP SE or an SAP affiliate company. All rights reserved. Order groceries by Chatbot
  56. 56. 56© 2018 SAP SE or an SAP affiliate company. All rights reserved. Internal IT bot Contract manager bot Invoice manager bot Invoice manager and dispatcher bot Account manager bot Insurance bot Hi, I forgot my Outlook password There’s something wrong with my box… What’s the total of my August invoice? I want to download my invoice Can I get my payment schedule? I need to suspend my contract Many Brands Have Chosen SAP Conversational AI to Build Their Bots
  57. 57. Customer Service Examples
  58. 58. 58© 2018 SAP SE or an SAP affiliate company. All rights reserved.
  59. 59. 59© 2018 SAP SE or an SAP affiliate company. All rights reserved. Predictive call centers
  60. 60. 60© 2018 SAP SE or an SAP affiliate company. All rights reserved. CuRT*, the new Virtual Colleague at BASF… ...Runs on SAP Service Ticket Intelligence What is it? Machine learning can help you efficiently sort ticket input from a variety of channels, suggest relevant service proposals, and route tickets to the appropriate service agent. • Cloud deployment • Automated processing • Integration with SAP Hybris Service Cloud • Faster digital interaction processing *Customer Request Tracking What are the benefits? • Frees contact center agents from repetitive, tedious tasks • Less re-routing leads to increased speed of resolution • Improving service response times due to automated processing • Allowing customer service to scale with increased digital interactions • Increasing customer satisfaction • Lowering the overall cost of providing customer service “With our virtual colleague CuRT, we automate incoming inquiries of multiple channels, to deliver a higher quality and service level to our customers based on SAP Leonardo Machine Learning.” Pedro Ahlers, Digital Growth Manager, BASF SE
  61. 61. 61© 2018 SAP SE or an SAP affiliate company. All rights reserved. Deal intelligence Deal insights to grow your revenue, predictively Opportunity Score indicates probability of deal winning Key factors surfaces most influential features that affect the score Activity Summary shows how engaged is the account is in the deal cycle Activity Score feeds into the Opportunity Score and reflects the overall sentiment during the deal cycle. (Heat map indicates hot and cold areas of engagement during deal cycle) Indicates number of days left before close date Indicates number of days deal has been sitting in that phase and how it compares to average of all other deals Indicates Key Risks identified for the deal during that phase Indicates if the deal has slipped and if so how many times Indicates number of times the close date has been changed Indicates most recent change to opportunity amount Indicates if the deal status has been upgraded or downgraded Tell me what is going on with this opportunity
  62. 62. Machine Vision Examples
  63. 63. How many dogs?!
  64. 64. 64© 2018 SAP SE or an SAP affiliate company. All rights reserved.
  65. 65. 65© 2018 SAP SE or an SAP affiliate company. All rights reserved. Event Rider Masters
  66. 66. 66© 2018 SAP SE or an SAP affiliate company. All rights reserved.
  67. 67. 67© 2018 SAP SE or an SAP affiliate company. All rights reserved. Merchandising compliance via image recognition
  68. 68. 68© 2018 SAP SE or an SAP affiliate company. All rights reserved. Fashion trends and advice
  69. 69. 69© 2018 SAP SE or an SAP affiliate company. All rights reserved. Face recognition
  70. 70. 70© 2018 SAP SE or an SAP affiliate company. All rights reserved. Face recognition
  71. 71. Other Examples
  72. 72. 72© 2018 SAP SE or an SAP affiliate company. All rights reserved. Predictively saving rainforests
  73. 73. 73© 2018 SAP SE or an SAP affiliate company. All rights reserved. Predictive mental health to keep people out of jail
  74. 74. Wrap-up
  75. 75. 75© 2018 SAP SE or an SAP affiliate company. All rights reserved. Look at the full list of S/4HANA and other machine learning- enabled applications that are already available: sap.com/ml Look for areas:  Where you have lots of high-quality data  That don’t involve personal data (see compliance)  Where complex, repeatable decisions are being taken many times a day  Where the action can be taken automatically, without big changes to existing workflows Step 1: Find quick-win automation opportunities
  76. 76. 76© 2018 SAP SE or an SAP affiliate company. All rights reserved. Get existing functionality out to many more people, easier than ever before Chatbots for your employees  SAP CoPilot  SAP Analytics Cloud  SAP Recast.AI Chatbots for customers  Hybris Charley  Recast.AI Step 2: Invest in new machine interfaces
  77. 77. 77© 2018 SAP SE or an SAP affiliate company. All rights reserved. Education programs Arrange a design-thinking workshop Arrange “hackathons” Step 3: Organize design-thinking workshops
  78. 78. 78© 2018 SAP SE or an SAP affiliate company. All rights reserved. You’re outsourcing decision-making to machines!  Transparency: If your customers would be annoyed if they found out what you’re doing, you probably shouldn’t be doing it!  Audits to check that bad things aren’t happening  Always include some human checks and balances Laws (e.g., GDPR Article 22)  “The data subject shall have the right not to be subject to a decision based solely on automated processing, including profiling, which produces legal effects concerning him or her or similarly significantly affects him or her”  “… the data controller shall implement suitable measures to safeguard the data subject’s … right to obtain human intervention … to express his or her point of view and to contest the decision.” Somebody has to be in charge of this! Step 4: Don’t forget governance and ethics
  79. 79. 79© 2018 SAP SE or an SAP affiliate company. All rights reserved. Machine learning adoption: The time is now Companies across all industries are starting to adopt machine learning and see it as a critical requirement to gain a competitive advantage 94% Of companies believe machine learning will become critical to gain competitive advantage Source: IDC and SAP survey, Q3 2016 19% Are exploring machine learning but have no plans to adopt at this time 15% Have adopted machine learning 40% Are planning to adopt machine learning within 2 years 26% Are planning to adopt machine learning in 2-5 years Within 2 years, 55% Of companies will adopt machine learning
  80. 80. 80© 2018 SAP SE or an SAP affiliate company. All rights reserved. SAP enables the intelligent enterprises of the future 76% of the world’s transaction revenue touch an SAP system 25 industries 12 lines of business The world’s largest business network Business Outcomes Increase revenue Re-imagine processes Quality time at work Customer satisfaction Enabling innovations Data Science Platform Intelligent Services Intelligent Apps Conversational Interfaces Machine Learning
  81. 81. 81© 2018 SAP SE or an SAP affiliate company. All rights reserved. sap.com/ml SAP Leonardo Machine Learning site, links to more information about the applications and the machine learning platform www.partnershiponai.org/ Machine learning means you’re delegating decisions to a machine – you need to think about the ethics of what you are doing! SAP Community, Machine Learning Tag Take part in the SAP Community! Read the latest blogs that touch on real-world uses of machine learning TimoElliott.com/blog My blog  I’m passionate about these uses – lots of articles on what it means to the new digital economy Where to find more information
  82. 82. 82© 2018 SAP SE or an SAP affiliate company. All rights reserved. 1. Find quick wins to get started 2. Invest in new natural language interfaces 3. Brainstorm new opportunities 4. Don’t forget governance! Key points to take home
  83. 83. Thank you. Contact information: Timo Elliott Global Innovation Evangelist, SAP +33628985650 @timoelliott timoelliott.com
  84. 84. © 2018 SAP SE or an SAP affiliate company. All rights reserved. No part of this publication may be reproduced or transmitted in any form or for any purpose without the express permission of SAP SE or an SAP affiliate company. The information contained herein may be changed without prior notice. Some software products marketed by SAP SE and its distributors contain proprietary software components of other software vendors. National product specifications may vary. These materials are provided by SAP SE or an SAP affiliate company for informational purposes only, without representation or warranty of any kind, and SAP or its affiliated companies shall not be liable for errors or omissions with respect to the materials. The only warranties for SAP or SAP affiliate company products and services are those that are set forth in the express warranty statements accompanying such products and services, if any. Nothing herein should be construed as constituting an additional warranty. In particular, SAP SE or its affiliated companies have no obligation to pursue any course of business outlined in this document or any related presentation, or to develop or release any functionality mentioned therein. This document, or any related presentation, and SAP SE’s or its affiliated companies’ strategy and possible future developments, products, and/or platforms, directions, and functionality are all subject to change and may be changed by SAP SE or its affiliated companies at any time for any reason without notice. The information in this document is not a commitment, promise, or legal obligation to deliver any material, code, or functionality. All forward-looking statements are subject to various risks and uncertainties that could cause actual results to differ materially from expectations. Readers are cautioned not to place undue reliance on these forward-looking statements, and they should not be relied upon in making purchasing decisions. SAP and other SAP products and services mentioned herein as well as their respective logos are trademarks or registered trademarks of SAP SE (or an SAP affiliate company) in Germany and other countries. All other product and service names mentioned are the trademarks of their respective companies. See www.sap.com/corporate-en/legal/copyright/index.epx for additional trademark information and notices. www.sap.com/contactsap Follow all of SAP

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