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Artificial Intelligence Trends 2019 Roundup Presented by ARTIFICIAL INTELLIGENCE TRENDS 2019 ROUNDUP March 2019 The artificial intelligence (AI) ecosystem is complex and in a state of constant flux. Though far from perfect, one thing is certain: Many business leaders are already bullish about AI’s ability to improve operations. eMarketer has curated this Roundup of articles, insights and interviews to help you understand the latest trends in AI. TABLE OF CONTENTS 3 Sponsor Message 4 Overview 6 Explain Yourself, AI 7 The AI Terms You Need to Know 9 Making Sense of Large Data Sets Is AI’s Strength 10 Enthusiasm Runs High for AI, but Many Are Still on Learning Curve 12 Why Marketers Use AI for Audience Targeting 13 Successful AI Adoption Requires Clear Strategies 14 Get Your AI House In Order 16 Can AI and GDPR Co-Exist? 17 Retailers and Shoppers Are on Totally Different Pages About Tech 19 How Financial Brands Create Virtual Assistants that Respect Users’ Privacy 21 About this Roundup ARTIFICIAL INTELLIGENCE TRENDS 2019 ROUNDUP SPONSORED BY: 2 SPONSOR MESSAGE Braze is a customer engagement platform that delivers messaging experiences across push, email, apps and more. Braze is set apart as the platform that allows for real-time and continuous data streaming, replacing decades-old databases that aren’t built for today’s on-demand, always-connected customer. The Braze Intelligence Suite is a set of features built to help you answer the what, when, and who of your marketing campaigns by targeting the right customers, selecting the strongest message, and delivering it all at the optimal time for each individual customer, at scale. Braze has been at the forefront of embracing AI to automate decision making at key engagement points in the customer journey. We’re glad to bring you the latest data and best practices on the future trends of AI to explore how you can use AI to enhance your customer experiences. Braze is a venture-backed company with offices in New York City, San Francisco, London and Singapore. Learn more at braze.com ARTIFICIAL INTELLIGENCE TRENDS 2019 ROUNDUP SPONSORED BY: 3 OVERVIEW The AI ecosystem is complex and Measured another way, Gartner estimated in Business Value of Artificial Intelligence Among 2018 that the business value derived from AI Enterprises Worldwide, 2017-2022 in a state of constant flux. Though trillions and % change far from perfect, one thing is for among enterprises worldwide—based on its 3.923 impact on customer experience, new revenues (17%) certain: Many business leaders are 3.346 and cost reduction—would hit $3.923 trillion (26%) already bullish about AI’s ability 2.649 to improve operations. In a 2018 by 2022, up from $692 billion in 2017. (39%) survey, the Economist Intelligence 1.901 Among AI’s top selling points is its ability (62%) Unit (EIU) found that senior 1.175 to help humans make quicker and more (70%) executives worldwide expect AI informed decisions that lead to greater 0.692 to improve growth, productivity, efficiency. The EIU research found that innovation and job creation in their businesses were applying AI technology to 2017 2018 2019 2020 2021 2022 respective countries and industries. a variety of use cases across the enterprise. Note: defined as value derived from AI's impact on customer experience, new revenues and cost reduction The most common included predictive Source: Gartner as cited in press release, April 25, 2018 Which Operational Areas Do Senior Executives analytics, real-time operations management, 238192 www.eMarketer.com Worldwide Expect AI to Improve in the Next 5 Years? % of respondents, 2018 customer service, risk management, And April 2018 research by UBM found that unearthing customer insights and improving Growth 90% tech professionals in North America expected customer experiences. Productivity 86% AI to have the most impact on enterprises Innovation 84% for its ability to provide new operational Job creation 69% intelligence, automate repetitive tasks and Note: those responding "expect improvement" Businesses are in improve workforce productivity. Source: The Economist Intelligence Unit (EIU), "Intelligent Economies: AI's transformation of industries and society" sponsored by Microsoft, July 29, 2018 Businesses are in various stages of 244545 www.eMarketer.com various stages of implementation. A December 2018 PwC As a result, AI is attracting significant implementation. report found that 27% of companies surveyed investment. A December 2018 forecast from had already deployed it in multiple areas tech research firm Tractica estimated that of their organization, while another 20% the worldwide market for AI software was planned to implement it throughout the worth $5.4 billion in 2017, and would grow to enterprise in 2019. $105.8 billion by 2025. This amounts to 45% compound annual growth over an eight-year forecast period. ARTIFICIAL INTELLIGENCE TRENDS 2019 ROUNDUP SPONSORED BY: 4 —CONTINUED What Do Senior Executives Worldwide See as the Top AI is no longer a futuristic, sci-fi trope. After In Which Areas Do Tech Professionals in North Use Cases for AI? years of development, AI technologies— America Expect AI to Have the Most Impact on % of respondents, 2018 Enterprise Business? including machine learning (ML), natural % of respondents, April 2018 Predictive analytics (e.g., demand and inventory forecasting, predictive maintenance) language processing (NLP) and computer Providing new operational intelligence 26% vision—are transforming organizations and 45% Real-time operations management (e.g., improved internal Automating repetitive tasks efficiencies) freeing up employees to do higher-value 38% 23% work. For marketers and advertisers, AI is Improving workforce productivity Customer services 32% 21% already disrupting core functions, including Automating areas of knowledge work Risk management and analytics ad targeting, media buying, content creation 28% 20% and propensity modeling. This Roundup Improving customer service Customer insight 28% 18% will explore these AI trends to help you Enabling new products and services Customer experience (e.g., personalization) get started. 24% 17% Improving information security Research and development 23% 17% Reducing costs Supply chain, procurement or logistics optimization AI [...] is freeing up 23% 17% Identifying new business opportunities Fraud detection (e.g., financial crime prevention) 17% 16% employees to do Improving brand differentiation Human resources 6% 16% Knowledge creation Note: maximum 3 responses allowed higher-value work. Source: UBM Technology Group, "AI: Hype or Substance," July 16, 2018 16% 243984 www.eMarketer.com Pricing and promotion 13% Social engagement 12% Source: The Economist Intelligence Unit (EIU), "Intelligent Economies: AI's transformation of industries and society" sponsored by Microsoft, July 29, 2018 244292 www.eMarketer.com ARTIFICIAL INTELLIGENCE TRENDS 2019 ROUNDUP SPONSORED BY: 5 EXPLAIN YOURSELF, AI 61% of execs say creating provable AI methods is a critical step this year As use of AI grows (27% of Samsung used machine-learning systems How Far Along Are US Executives in Deploying AI? executives in a PwC study have to recommend products to users, but it was % of respondents, 2018 Implemented pilot already implemented AI), so do calls difficult to measure return on investment projects within discrete for ways to interpret how AI models (ROI) and compare new models to older areas Investigating Plan to deploy 16% use of AI enterprise-wide make decisions. This has given rise ones, Paka told CNBC. At Facebook, Gade’s 22% 20% challenge was measuring how well the News to a new buzzword: explainable AI, Already implemented Feed was working on any given day. “We in multiple areas which refers to algorithms that make Plan to 27% needed to build tools and platforms to unlock deploy in decisions humans can explain. PwC, multiple areas this thing and provide those insights to an 15% for example, says it “integrates risk engineer all the way to an executive within Note: n=633 at companies that are investigating or implementing AI Source: PwC, "2019 AI Predictions: Six AI Priorities You Can't Afford to mitigation and ethical concerns Facebook,” he said. Ignore," Dec 1, 2018 into algorithms and data sets from 243968 www.eMarketer.com the start.” New buzzword: Sixty-one percent of executives surveyed by PwC said creating transparent, explainable, provable AI methods was a step they planned explainable AI to take in 2019. Krishna Gade, a former engineering manager of Facebook’s News Feed, and Amit Paka, who worked on Samsung’s shopping apps, saw a need for a platform that could clearly explain to company shareholders how AI models make decisions. They founded Fiddler Labs to do just that. ARTIFICIAL INTELLIGENCE TRENDS 2019 ROUNDUP SPONSORED BY: 6 THE AI TERMS YOU NEED TO KNOW An Overview of AI Tech In its most broadly understood Deep learning: A complex branch of ML It also incorporates image processing, definition, AI involves the ability that involves building and training neural pattern recognition and image understanding of machines to emulate human networks with multiple layers. Each network (turning images into descriptions that can thinking, reasoning and decision- layer can use output from the layer above it be used in other applications). Computer making. But the terminology can to learn and make intelligent decisions on its vision underpins many up-and-coming often get confusing. Here is a own. Deep networks shine when sorting and innovations, including self-driving cars and classifying data and identifying anomalies in cashierless stores. rundown of some common AI terms. data patterns and excel at image and speech Natural language processing (NLP): A branch Machine learning (ML): The branch of recognition, but they need more powerful of AI that deals with a machine’s ability to AI computing that involves training machines than ML, and it’s often difficult for understand spoken or printed words in human algorithms to perform tasks by learning humans to understand how they work. (natural) languages, as opposed to computer from previous data and examples rather Neural networks: ML algorithms and programming languages.
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