2018 FORRESTER. REPRODUCTION PROHIBITED.

Transcription

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2 Climbing the Ladder to AI: Driving Business Transformation With Artificial Intelligence Kjell Carlsson, PhD Senior Analyst September 18, 2018

3 When you say AI, what do most people think of? Enormous development cost Extreme time to value Misaligned expectations Humanlike robots Self-driving cars Virtual agents What do these examples have in common? Image Source: Darpa, Aleksandar Mishkov DocumentaryTube, Patrick McCarthy Dealerscope 3

4 The mountain of interest in AI is real What are your firm's plans to use Artificial Intelligence? and challenging Base: 2094, 2106, 1697 data and analytics decision-makers Source: Forrester Data Global Business Technographics Data And Analytics Survey, 2016, 2017,

5 Enterprises are expecting a broad range of outcomes Artificial Intelligence Usage Drivers Operational efficiency Base: 2,594 Data and analytics decision-makers whose firm is interested in using/planning to use/currently using AI Source: Forrester Data Global Business Technographics Data And Analytics Survey, 2018 Core business outcomes 5

6 Challenges fall into three categories Artificial Intelligence Usage Barriers We don t know what the right problems are We don t know how to do it We don t trust it Base: 2,594 Data and analytics decision-makers whose firm is interested in using/planning to use/currently using AI Source: Forrester Data Global Business Technographics Data And Analytics Survey,

7 Tackling the right problems 7

8 What is AI? Human-like ability to sense, think, act and learn ~85% believe AI is a human-like ability to understand the world around them interact with it solve problems and improve automatically Note: Don t know excluded. Base: 1,711 data and analytics decision-markers Source: Forrester Data Global Business Technographics Data And Analytics Survey,

9 What is AI? AI is a collection of insights & automation technologies Analytics & ML Automation Traditional machine learning & statistics Decision management Speech analytics Text analytics & NLP Virtual agents Robotic process automation Image & video analytics Deep learning Natural language generation Source: Forrester, TechRadar: AI Technologies and Solutions, Q

10 AI is a good complement not a substitute for human subject matter expertise AI delivers superhuman insight AI automates standard processes AI struggles with uncertainty & judgement Data beyond human scope Effectively tackles tasks you feel bad asking a human to do Struggles with the long tail of possible situations Analysis more powerful than any mind Patterns too complex to perceive At lightning speed Takes rapid action based on human direction Can not fill gaps in the context Can not reason or explain Struggles to instill trust and build engagement 10

11 Augmented Intelligence Humans leveraging AI s superhuman insights and orchestration abilities AI Insights + AI Orchestration Better decisions Value faster Exceeds human cognitive abilities Greater productivity & less change management + Human Judgement & Engagement Faster to develop Avoids the long tail 11

12 Personal Transportation: We already take Augmented Intelligence for granted AI Insights + AI Orchestration + Human Judgement GPS navigation Matching algorithm Jon 12

13 Examples of delivering value faster through augmented intelligence Sales Customer service Litigation 13

14 Building transformative AI capabilities 14

15 Even the most sophisticated firms find it challenging to drive outcomes with AI at scale I have built 10 PoCs and I have no hope that any of them will be put into production We waste so much time trying to figure out why models that run on one computer don t run on another I can run my model for a few thousand square km, the business wants it done for countries The performance of our model declined by 30% when we put it into production on Spark Our processes for updating our models are too manually intensive we can t do this at scale 15

16 Common AI project roadblocks Model didn t work Couldn t get the tools or infrastructure The data was unusable Couldn t get the data Start We couldn t build it Model wasn t operationalized No end-user app developed Model / App not adopted by end-users Finish We couldn t deploy it 16

17 The AI Ladder Make it intuitive for end-users to adopt Enable iterative model development Provide self-service tools & infrastructure Make the data simple to use & reliable Access the data you need Embedded AI Scalable ML Embed models into end user apps Streamline model deployment Quality Data Rich Data Access 17

18 How are enterprises accessing AI capabilities? What is your AI capabilities strategy? Both Buy Build Base: 2,594 Data and analytics decision-makers whose firm is interested in using/planning to use/currently using AI Source: Forrester Data Global Business Technographics Data And Analytics Survey,

19 Embedded AI Scalable ML Quality Data Rich Data Access Source: The Forrester Wave : Machine Learning Data Catalogs, Q

20 Embedded AI Scalable ML Quality Data Rich Data Access Source: The Forrester Wave : Multimodal Predictive Analytics And Machine Learning Solutions, Q

21 An explosion of AI components Vision Image or video labelling and analysis including facial recognition and OCR Speech Speech-to-text, text-to-speech, translation, speaker identification and speech analytics Language NLP text analytics including entity/topic/intent extraction, sentiment/persona analysis, and text-to-text translation Conversation Chatbots and other conversational interfaces that parse and map intents to actions Knowledge Find relevant information either through enhanced search, enhanced data, and decision rules engines 21

22 Climbing The AI Spiral Staircase Increasing investment in data and capabilities New projects with greater and greater transformative potential Rapid success based on existing or easily acquired capabilities 22

23 Related research: The Forrester Wave : Multimodal Predictive Analytics And Machine Learning Solutions, Q Kjell Carlsson, PhD kcarlsson@forrester.com The Forrester Wave : Notebook-Based Predictive Analytics And Machine Learning Solutions, Q Now Tech: Predictive Analytics And Machine Learning Solutions, Q Best Practices: Scaling Data Science Across The Enterprise Thank you FORRESTER.COM