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AI / Cognitive Computing Trend Report, 2017

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Purpose: The slides provide an overview on the AI/Cognitive Computing trend
Content: AI/Cognitive Computing market trends, drivers, spending trends, industry business cases, and adoption challenges. Also included are links to additional resources.
How To Use This Report: This report is best read/studied and used as a learning document. You may want to view the slides in slideshow mode so you can easily follow the links
Available on Slideshare: This presentation (and other Trend Reports for 2017) will be available publically on Slideshare at http://www.slideshare.net/horizonwatching
Please Note: This report is based on internal IBM analysis and is not meant to be a statement of direction by IBM nor is IBM committing to any particular technology or solution.

Published in: Technology

AI / Cognitive Computing Trend Report, 2017

  1. 1. Note: This report is based on internal IBM analysis and is not meant to be a statement of direction by IBM nor is IBM committing to any particular technology or solution. Welcome to the new era of Cognitive Computing Andrew Onda, Manager – Cognitive Solutions, Market Development & Insights Bill Chamberlin, Distinguished Market Intelligence Professional, MD&I HorizonWatch February 15, 2017 AI / Cognitive Computing Trend Report, 2017
  2. 2. Note: This report is based on internal IBM analysis and is not meant to be a statement of direction by IBM nor is IBM committing to any particular technology or solution. About This Trend Report 15Feb2017  Purpose: The slides provide an overview on the AI/Cognitive Computing trend  Content: AI/Cognitive Computing market trends, drivers, spending trends, industry business cases, and adoption challenges. Also included are links to additional resources.  How To Use This Report: This report is best read/studied and used as a learning document. You may want to view the slides in slideshow mode so you can easily follow the links  Available on Slideshare: This presentation (and other Trend Reports for 2017) will be available publically on Slideshare at http://www.slideshare.net/horizonwatching  Please Note: This report is based on internal IBM analysis and is not meant to be a statement of direction by IBM nor is IBM committing to any particular technology or solution. AI / Cognitive Computing Trend Report, 2017 (External Version)2
  3. 3. Note: This report is based on internal IBM analysis and is not meant to be a statement of direction by IBM nor is IBM committing to any particular technology or solution. Welcome to the Cognitive Era and the rise of Cognitive Business 3 We have entered a new era of computing called cognitive computing. It signifies a fundamental shift in how machines interact with us, other machines and the environment. It will provide much value, but it will be highly disruptive. The Cognitive Era will result in entirely new model of computing that includes a range of technology innovations in analytics, natural language processing and machine learning “Cognitive computing is quickly emerging as a transformative technology that enables organizations to gain business advantage. This shift to systems that can reason and learn is especially germane to the bottom line; the cognitive era is here in large part because it makes practical business sense.” IBM 15Feb2017 AI / Cognitive Computing Trend Report, 2017 (External Version) Key Insights IBM: How Watson Works (video)
  4. 4. Note: This report is based on internal IBM analysis and is not meant to be a statement of direction by IBM nor is IBM committing to any particular technology or solution. Cognitive computing combines AI technologies, relevant content and deep subject matter expertise 4 Capability Required Advanced Ultimate Understand domains deeply • Has task-specific knowledge • Also has contextual knowledge relevant to asks • Also has common sense & general knowledge Reason towards specific goals • Uses specific approach • “Deductive or Inductive” • Also explains • “Abductive” • Also combines approaches • “Adaptive” Learn continuously from experience • Uses explicit training • “Supervised learning” • Also uses implicit training. • “Unsupervised learning” • Also uses feedback from the environment. • “Reinforcement learning” Interact naturally with cognitive agents • Transactional request response • Session-oriented contextual, affective interactions • Life-long conversational interactions 15Feb2017 AI / Cognitive Computing Trend Report, 2017 (External Version) Key Insights
  5. 5. Note: This report is based on internal IBM analysis and is not meant to be a statement of direction by IBM nor is IBM committing to any particular technology or solution. Cognitive Computing – Trend Overview 5 Drivers  Advances in enabling AI technology areas  Increasingly large complex datasets that can be the source of major insights and hold the answers to critical questions  Third computing platform – Cloud, IoT, Mobile, Big Data, Analytics, Social Challenges  Much more work on enabling technologies required  Documented use cases and ROI impact not yet fully understood  Education future of AI’s impact on jobs and society  Window of opportunity: Partnerships / Ecosystems / Developers Implications  First movers will have an advantage.  This is a technology that learns. Accuracy will increase over time.  Cognitive services will be delivered via the cloud to mobile device  Expect the mass market to develop around consumers at a fast pace.  Business processes and whole industries will be transformed.  Changes will be required in employee workforce, corporate culture, and partner ecosystems.  New IT architectures, systems design, data management/analytics and workload optimized systems.  Job displacement will happen, but new jobs will be created. Scenario planning needed to understand long term implications. 15Feb2017 AI / Cognitive Computing Trend Report, 2017 (External Version) Market Trends “The cognitive era will create new jobs, such as robot monitoring professionals, data scientists, automation specialists, and content curators: Forrester forecasts 8.9 million new jobs in the US by 2025.” Forrester “Widespread adoption of cognitive systems and artificial intelligence (AI) across a broad range of industries will drive worldwide revenues from nearly $8.0 billion in 2016 to more than $47 billion in 2020” IDC World of Watson: Ginni Rometty keynote
  6. 6. Note: This report is based on internal IBM analysis and is not meant to be a statement of direction by IBM nor is IBM committing to any particular technology or solution. Top trends to watch in 2017 include vertical industry use cases, chatbots and the impact of consumer AI 6  Verticals: Healthcare, Life Sciences, and FSS AI start- ups are using machine learning and both structured and unstructured data. customer facing departments are leading or evaluating the investments and adoption in AI systems. Enterprise buyers are partnering with AI software providers as they start their AI journey  Conversational services explode: In 2017, expect increased activity in conversational services (e.g. chatbots, virtual agents). Vendors with best UX will succeed. Apps & services must be easy to use and the UX needs to be immersive, ambient, conversational and accurate. It must also learn our preferences from past conversations.  Consumer AI tech drives market. AI will be used by consumers everywhere: IoT devices, home devices, robots, vehicles, drones, digital assistants and wearables. As usage grows, it will influence how B2B markets develop with AI solutions migrating into the enterprise, starting with the automotive, electronics, and banking industries 15Feb2017 AI / Cognitive Computing Trend Report, 2017 (External Version) Market Trends Forrester: Predictions 2017: Artificial Intelligence Will Drive The Insights Revolution “Near-term opportunities for cognitive systems are in industries such as banking, securities and investments, and manufacturing” Jessica Goepfert, IDC IBM: The Future of Cognitive Services
  7. 7. Note: This report is based on internal IBM analysis and is not meant to be a statement of direction by IBM nor is IBM committing to any particular technology or solution. Vertical industry use cases include diagnosis, conversational services, and recommendation systems 7 Industries Near-Term Use Case Examples Banking / FM / Insurance Sales, Marketing, Service, Regulatory, Claims, Risk • Program Advisors and Recommendation • Fraud Analysis and Investigation • Regulatory Intelligence • Automated Claims Processing • Automated Threat Intelligence and Prevention Systems Healthcare & Life Sciences Services and decision support • Diagnosis and Treatment • Pharma R&D • Claim Management • Personalized Health Services Consumer (Retail, CPG) Sales, Marketing, Merchandising, Supply chain logistics • Automated Customer Service Agents • Expert Shopping Advisors and Product Recommendations • Omni-channel merchandising Telco, M&E Sales, Marketing, IT • Virtual Agents • Digital Advertising • Automated Threat Intelligence Government, Education Core operations, Threat intelligence • Threat Intelligence and Prevention • Defense, Terrorism, Investigation • Program Advisors and Recommendation Systems • Public Safety and Emergency Response • Adaptive Learning 15Feb2017 AI / Cognitive Computing Trend Report, 2017 (External Version) Market Trends
  8. 8. Note: This report is based on internal IBM analysis and is not meant to be a statement of direction by IBM nor is IBM committing to any particular technology or solution. Technologies to watch include neural networks, machine learning, NLP, and pattern recognition  Neural Networks: Neural networks are providing rapid advances in speech and image recognition and machine translation. some systems perform as well as humans  Advancements in machine learning feed off access to IoT- generated data. As the IoT generates more real-time data, machine learning algorithms will use that data for planning, forecasting and making critical business decisions.  Natural language processing (NLP) sweet spot is customer service. Enterprises will use NLP-based solutions, including chatbots, to handle customer service inquiries without human interaction, improving overall efficiencies and costs.  Rich media & IoT analytics fuel pattern recognition advancements. Combining historical and traditional data with real time rich media & IoT unstructured data will reveal new patterns in data that can inform future decision processes.  Knowledge representation and reasoning efforts focus on supporting decision making. Look for efforts to build large- scale knowledge databases that cognitive systems can use to drive unbiased support for subject-matter experts. 8 15Feb2017 AI / Cognitive Computing Trend Report, 2017 (External Version) Market Trends “Cognitive advances — combined with robotics, IoT, artificial intelligence, augmented reality/virtual reality, machine intelligence, and massive data sets — increase the ability of systems to mimic and enhance human intelligence in real time.” IDC “By 2018, deep learning (deep neural networks) will be a standard component in 80% of data scientists’ tool boxes..” Gartner IBM Research: Cognitive Computing
  9. 9. Note: This report is based on internal IBM analysis and is not meant to be a statement of direction by IBM nor is IBM committing to any particular technology or solution. The AI startup and vendor ecosystem will continue to grow and expand in in 2017 9  VCs and Startups: The market landscape has 2,000+ start- ups. Venture Capital funding was nearly $4.5B in 2016; investments in core AI technology, chatbots, and Advanced Analytics have grown over the last two years. The majority of AI start-ups are using machine learning and both structured and unstructured data  Large vendors continue to acquire talent and capabilities. Continuing a trend we have seen the last three years, expect all large vendors to look to acquire AI startups and capabilities in order to build economies of scale and fend off the competition. AI acquisitions have been strong over the past 3 years, with a focus on machine learning capabilities; Virtual Agents / Chatbots acquisitions were also strong last year  Vendors continue to court developers to their platforms. To accelerate innovation and monetize assets, platform players will increasingly target development communities.  Patents: AI patent applications peaked in 2014 with a significant drop in 2016. IBM has been the most active in regard to patenting core AI technology. Look for increased patent activity for niche and industry vertical applications. “The startups have raised $3.8B in aggregate funding across 263 deals since 2012, and include startups at different investment stages of development, from seed/angel companies to well-funded unicorns.” CBInsights: AI 100: The Artificial Intelligence Startups Redefining Industries 15Feb2017 AI / Cognitive Computing Trend Report, 2017 (External Version) Market Trends VentureBeat: 5 deep learning startups to follow in 2017 “From stopping cyberattacks to operating autonomous vehicles to visually searching through a wine database, over 550 startups using AI as a core part of their products raised $5B in funding in 2016.” CB Insights
  10. 10. Note: This report is based on internal IBM analysis and is not meant to be a statement of direction by IBM nor is IBM committing to any particular technology or solution. A recent survey of early adopters indicate there are real business benefits of cognitive computing 10  65% say adopting cognitive is very important to their organization’s strategy and success  58% say cognitive computing is essential to digital transformation  50% say they already gain major competitive advantage from their cognitive initiatives  53% say cognitive computing will unlock the hidden value of their organization’s dark data  49% say it helps improve customer engagement and customer service  49% say it has improved productivity & efficiency  42% say it is enabling business growth through an expanded ecosystem “Organizations already gain major competitive advantage from their use of cognitive computing. They achieve a range of business outcomes–from customer engagement to productivity & efficiency and business growth.” IBM: The cognitive advantage report IBM: The cognitive advantage report 15Feb2017 AI / Cognitive Computing Trend Report, 2017 (External Version) IBM: The cognitive advantage report Market Trends
  11. 11. Note: This report is based on internal IBM analysis and is not meant to be a statement of direction by IBM nor is IBM committing to any particular technology or solution. Top Challenges to Adoption 11 1. Implementation effort / cost. In some cases, the effort and cost to implement AI technologies can be high. Enterprises want to understand the business value and ROI. Limited case studies exist for cognitive computing, creating potential hurdles to large-scale investment. 2. Data management and security / privacy Concerns. . Cognitive systems will rely heavily on data derived from multiple systems and sources. As such, it is important to ensure data is consolidated and sourced in a consistent, secure manner. Safeguards are needed against data overreach and abuse of privacy. 3. Insufficient Skills. AI technologies and cognitive computing solutions are emerging at a fast pace. Like any emerging tech area, there is limited skills in the marketplace.  Lack of industry definitions and standards. Similar to other emerging areas, the lack of industry standards and definitions around artificial intelligence and cognitive solutions may create hesitation in adoption.  Limitations of current technology. While there are important reasons to move forward with cognitive technology, firms must consider the constraints of existing platforms relative to their ultimate goals. 15Feb2017 AI / Cognitive Computing Trend Report, 2017 (External Version) Adoption Challenges “93% of automation technologists feel unprepared or only partially prepared to tackle the challenges associated with smart machine technologies.” Forrester O’Reilly: 3 challenges for artificial intelligence in medicine The Verge: These are three of the biggest problems facing today's AI
  12. 12. Note: This report is based on internal IBM analysis and is not meant to be a statement of direction by IBM nor is IBM committing to any particular technology or solution. Selected IBM websites 12  IBM Website IBM Watson  Watson APIs  Products  Blog: Built with Watson  Watson Internet of Things  Watson Health  IBM DeveloperWorks Cognitive Computing  IBM Research: Cognitive Computing / DeepQA White paper: Computing, cognition and the future of knowing IBM DeveloperWorks Cognitive Computing IBM Website IBM Watson 15Feb2017 AI / Cognitive Computing Trend Report, 2017 (External Version) Featured Links
  13. 13. Note: This report is based on internal IBM analysis and is not meant to be a statement of direction by IBM nor is IBM committing to any particular technology or solution. Example Cognitive Computing Use Cases 13 1. MD Anderson Cancer Center (Healthcare) Solution that aggregates large volumes of unstructured patient data from a variety of sources, enabling clinicians and researchers to run analytics in near-real time to identify patterns and gain important insights. 2. The Chinese University of Hong Kong (Healthcare) Cloud-based solution that enables research teams to accelerate their exploration of large, complex cancer data sets and identification of cancer trends. 3. Baylor College of Medicine (Education) Cognitive technology is used to accelerate medical research by analyzing over 300,000 articles automatically, looking for key words and phrases that indicate correlations among studies. 4. Guiding Eyes (Education) Solution that advances the art and science of raising guide dogs by analyzing structured and unstructured data to discover genetic, health, temperament and environmental factors that correlate with success. 5. Alpha Modus (Financial Markets) Cloud-based solution that can analyze large volumes of unstructured and natural language data from financial services industry sources, including stock exchanges, social media, and other market indicators, making it easy to explore new ideas and turn them into practical investment applications. 6. WayBlazer (Travel & Transportation) Travel application and APIs that use analyze unstructured social media content from thousands of sites and deliver personalized recommendations to travelers who issue natural- language questions. 7. Honest Cafe (Retail) Analytics are used to explore vending machine transactions, payments and weather data, find correlations, and uncover patterns in customer behavior. 8. Pon Holdings (Automotive, Industrial Products) Solution that extracts and analyzes unstructured data from millions of web pages, using the insights to generate leads for sales and marketing departments and also to improve pricing. 15Feb2017 AI / Cognitive Computing Trend Report, 2017 (External Version) Featured Links
  14. 14. Note: This report is based on internal IBM analysis and is not meant to be a statement of direction by IBM nor is IBM committing to any particular technology or solution. Selected public-facing analyst websites and resources 14 “The main driver for global cognitive computing market is increasing trend of large and complex data-set. This complex data is available in various form such images, video, and natural language. These data-sets cannot be processed with help of existing big data analytics systems, hence business organizations are turning their heads towards the cognitive computing.” MarketsandMarkets “Smart machines are no longer science- fiction; they are here, being used by businesses right now and only growing in capabilities. The disruption they will cause over the next decade will leave no industry untouched.” Gartner  Forrester: Artificial Intelligence (blogs) and Cognitive Computing (search)  Frost & Sullivan: Artificial Intelligence (search)  Gartner: Smart Machines (search) and Machine Learning  IDC: Intelligent Systems (search) and Machine Learning and Cognitive Computing  MarketsandMarkets: Cognitive Computing Gartner Press Release: Smart Machines Will Enter Mainstream Adoption By 2021 15Feb2017 AI / Cognitive Computing Trend Report, 2017 (External Version) Featured Links
  15. 15. Note: This report is based on internal IBM analysis and is not meant to be a statement of direction by IBM nor is IBM committing to any particular technology or solution. Selected media websites 15 “Artificial intelligence suffered a long winter, but a new name -- cognitive computing -- and a flood of data, innovation, and compute power now has thousands smart applications flourishing.” Infoworld: It's springtime at last for cognitive computing “The opportunities for cognitive computing are compelling. Organizations that move forward with this innovative capability will have the opportunity to push new boundaries for growth and gain advantage over their competition.” Forbes: Four Steps To Get Started With Cognitive Computing  CIO.com Artificial Intelligence (search) / IBM Watson (search)  ComputerWorld Artificial Intelligence (search) / IBM Watson (search)  DataVersity Cognitive Computing  eWeek Cognitive Computing (search) / Artificial Intelligence (search)  Forbes Cognitive Computing (search) / Artificial Intelligence (search)  GIGAOM Artificial Intelligence (search  HBR.org Cognitive Computing (search) / Artificial Intelligence (search)  InformationWeek Cognitive Computing (search) / Artificial Intelligence (search)  InfoWorld Cognitive Computing (search) / Artificial Intelligence (search):  Wired Artificial Intelligence (search) / IBM Watson (search) Wired Artificial Intelligence is More Artificial than Intelligent HBR: How Artificial Intelligence Will Redefine Management 15Feb2017 AI / Cognitive Computing Trend Report, 2017 (External Version) Featured Links
  16. 16. Note: This report is based on internal IBM analysis and is not meant to be a statement of direction by IBM nor is IBM committing to any particular technology or solution. Selected IBM social media resources 16  Twitter: @ibmwatson Hashtags #ibmwatson  Linkedin: IBM Watson Group  Facebook: IBM Watson  YouTube: IBMWatson  Instagram: Watson  Slideshare.net search for IBM Watson  Blogs: Watson Blog Twitter: @ibmwatson Blog: Watson Blog 15Feb2017 AI / Cognitive Computing Trend Report, 2017 (External Version) Featured Links
  17. 17. Note: This report is based on internal IBM analysis and is not meant to be a statement of direction by IBM nor is IBM committing to any particular technology or solution. Selected links to additional articles and resources  CIO: 2017 will be big year for AI thanks to tech giants  Cognitive Computing Consortium: Where Are We With Cognitive Computing Today? Part 1  Cognitive Computing Consortium: Where Are We With Cognitive Computing Today? Part 2.  ComputerWorld: Artificial Intelligence: Transparency isn't just a trend  Forbes: Crawl With Analytics Before Running With Artificial Intelligence  Forbes: 10 Powerful Examples Of Artificial Intelligence In Use Today  IBM: Planning for 2017? Top 3 ways you can add business value with cognitive solutions  Information Age: How artificial intelligence will support business growth in 2017  O'Reilly: 7 AI trends to watch in 2017  Technology Review: 5 Big Predictions for Artificial Intelligence in 2017  Technology Review: Survey: Machine Learning Trends, Challenges, and Opportunities  VentureBeat: 3 big trends for AI in 2017 17 15Feb2017 AI / Cognitive Computing Trend Report, 2017 (External Version) Featured Links
  18. 18. Note: This report is based on internal IBM analysis and is not meant to be a statement of direction by IBM nor is IBM committing to any particular technology or solution. More Insights on Technology Trends are Available 18 Other slide decks in this 2017 Trend Report series have been posted to Slideshare You are also invited to check out the following IBM websites and resources – IBM Academy of Technology – IBM Institute for Business Value – IBM Research and Research News and 5 in 5 – IBM’s THINK blog – IBM Think Academy on YouTube 15Feb2017 AI / Cognitive Computing Trend Report, 2017 (External Version)

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