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2 Microsoft Future Decoded 2018 November 6th Why AI Empowers Our Business Today Roberto Chinelli Data and Artifical Intelligence Market Unit Lead Avanade

3 Roberto Chinelli Avanade Italy Data and AI Market Unit Lead Base in Italy I m electronical engineer, I m working since 2000 in Avanade a global join venture from Accenture and Microsoft, and I m leading the Data and AI market unit

4 Get ready for the AI-first world Avanade s view is that businesses need to focus first on artificial intelligence (AI) a broad collection of technologies and processes that has become a reality and is already beginning to add value to businesses, as well as becoming more affordable and accessible. We see for themes that will take your business into this new era: New User Experiences: Deliver more meaningful and magical interactions Augmented Workforce: Take human capabilities to new heights Platform Economy: Gain exponential value from new ecosystems Digital Ethics: Leap into the unknown with a clear conscience 4

5 What is AI? Back in the 1950s, the fathers of the field Minsky and McCarthy, described artificial intelligence as The theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.

6 Why perception is so complex for a computer and even more for humans some times? Let s make a simple experiment

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9 Understanding Interpret meaning of data including text, voice, images Reasoning Form conclusions based on imperfect data and learn over time What is AI? Natural UI Engage with humans in natural ways 9

10 Artificial Intelligence describes a collection of multiple technologies that enable machines to sense, comprehend, act & learn on their own Sense Comprehend Act Perceive the world Analyse & understand Make informed decisions Artificial Intelligence Text processing Computer vision Audio processing Sensor processing Natural language processing Knowledge representation Learn Inference engines Machine learning Expert systems

11 Why Now? DATA (TONS OF) ALOGRITHMS TAGED DATA COMPUTATIONAL POWER

12 Why Now? DATA (TONS OF) ALOGRITHMS TAGED DATA COMPUTATIONAL POWER 12

13 How AI today can change our business Intelligent Robotic Process Automation Take a human-centred approach to identifying, building, scaling automation with applied intelligence Cognitive Services Enhance customer and employee interactions with intelligent agents Advanced Analytics Rethink your data approach by asking the questions to unlock it s hidden value 13

14 DiPA (Digital Personal Advisor) An innovative digital tool for a digital workforce Accenture in India looked at its challenge of addressing the experience of its many employees who often had to work through a maze of websites, products and services to find and get a wide range of human resources-related information. 14

15 DiPA (Digital Personal Advisor) An innovative digital tool for a digital workforce Deployment goal (1st year) employees with 50% of adoption First-year Q&A > DiPA is built on the Microsoft Bot Framework and Microsoft Cognitive Services product stack and hosted in Microsoft Azure. 15

16 Baxi Forecasting boiler failure service The current forecast on boiler failure service requests has no regional level drill downs or granularity for effective engineer scheduling. Baxi wants to reduce its current 3 day average response time to a same day response Avanade ran a 3 week Insight Discovery led approach that uses external sources like weather data to build a blended forecasting approach with 450+ machine learning models The new forecasting approach gives Baxi a 98% forecast accuracy, region level and day of the week based granularities, a ranking of factors driving forecast accuracy and insights not known before. The models predict with a 98% accuracy, leading to significant savings per year. 16

17 AI Adoption: take away AI project couldn't be a traditional project or a magic box $ Goal/KPI Functional Results Analysis Data and AI Programs Data Machine Learning??? $ Ideas/Profits Developers How and way an AI project can fail? How do I de-risk my AI-driven analytics projects? Waterfall/Agile method can help to avoid pitfalls? 17

18 AI Adoption: take away Make your AI project to a successful project Clarity on scope definition And Define Success Creteria Working Prototype Rapid Innovation Deploy to Production Continuos Development 18

19 Questions?

20 Thanks