The e tr true e bu busines iness imp impac act t of AI - PowerPoint PPT Presentation

The e tr true e bu busines iness imp impac act t of AI Daniel Pitchford Director AI Business E: daniel@aibusiness.org

Defin finin ing A g AI I - Practica ctical l AI Narr rrow w AI n I not ot General A l AI! I! Umbrella term:  Machine Learning – to learn for itself, supervised or un-supervised..  Deep Learning – hierarchical learning technique  Cognitive – machines configured to mimic a human brain/ neural nets  Image Recognition – computers to identify, tag and understand images  NLP – full spectrum of U and G - machines ability to understand, translate, generate human language

Th The Op e Opportunit ity y for B Busin ines ess 1/2 1/2 Automating clerical tasks - Contact centres – customer facing applications B2C - Processing vast amounts of data – automated process and predictive analytics - Formulating reports – numerical applications / natural language applications - Monitoring network performance – automated resolutions without human interaction - Preventing cyber attacks – Fraud detection, prevention, more robust firewalls $357 million – Worldwide Enterprise AI Investment in 2016 *Tractica

The Op Th e Opportunit ity y for B Busin ines ess 2/2 /2 Enhancing more complex tasks – Human Collaboration - Predicting human behaviour and enhancing decision-making - Enhancing organisational operations by minimizing human intervention and increasing accuracy - Improving the customer experience and product j ourney - Increase Revenues – S peeding up time to market for new products $31 billion – Worldwide Enterprise AI Investment by 2025 *Tractica

AI AI-ena nabl bled E d Ent nterprise se: Curr Current t State te of of Pla lay  3 Pillars : Advances in Big Data and processing capabilities have made the huge advances in AI of the last couple of years possible  The US A leads the way on current AI investment, followed by Europe, and Asia ($212m/$93m/$46m).  Current implementation rates are 20% -35% of overall potential  AI Business researched FTS E100 and Fortune 500 organisations in 2016 and found that 32% are already implementing some form of AI

AI-ena AI nabl bled E d Ent nterprise se: Current Curr t State te of of Pla lay  82% are planning to do so within the next 12-18 months  From current uptake, 75% are investing in machine and deep learning applications, 45% in NLP and 15% in image recognition technologies.  Financial S ervices, Transport, Manufacturing, and Retail among the earliest adopters and advocates of AI  Legal, Healthcare and Telco are also investing heavily in AI, many in j oint proj ects that also make the most of advances in robotics and automation capabilities.

Who is o is develop lopin ing g th the te tech chnolo ology?  Heavyweights: Amazon, Microsoft, Google, Facebook, IBM, HP , Intel, S AP , S alesforce are among the world’s biggest tech businesses pioneering AI and investing most heavily  Start-ups: Emerging daily - more than 400 start-ups focused on AI driven applications across Europe alone IBM Watson - Cognitive platform Core products – Virtual Agent, Watson Explorer, Watson Analytics, Knowledge Studio Fukoku Mutual Health has decided to implement Watson Explorer in Japan • Replacing 30+ employees with software which can calculate pay-outs to policy holders • Increase productivity by 30% • Investing £1.4m in the software and expects to save £1m per year when live • Analyse unstructured text, image, video – reading thousands of medical certificates in a fraction of the time humans are able to. • Expectations that half of all j obs in Japan could be performed by Robots by 2034.

Investment  Global Equity funding in AI now over $6 billion representing a 700% increase over the past 5 years  Over 1,000 deals meaning the start-up opportunity is hot  65% of investments are made at S eed or S eries A  Corporate Investors overshadowing VC investment with more than $1 billion invested *S ource CB Insights

Hottest Areas Healthcare focused companies leading the way with more than $500m of start-up investment in the past 2 years *S ource CB Insights

The AI Acquisition Race

AI R I Revenue ue by In Indus ustry try

JAP AN: LEADING AI INNOVATION IN AP AC • Percentage of Nikkei 225 enterprises already using some form of AI in calculated by AI Business research at 45% in late 2016 • Machine/ Deep Learning is number 1 investment in AI found among 85% of those implementing AI technologies • S ectors investing most include manufacturing, technology and financial services • Japan is among the leaders across AP AC in enterprise AI adoption • Intersection of Robotics (with Japan holding a world-leading advantage) and AI > a significant advantage for the growth of AI market • Ground-breaking and world-leading research and product development in this space conducted by maj or domestic technology giants including NEC, Toshiba, S oftbank, S ony, and Fuj itsu

JAP AN: Challenges & Opportunities • Japanese technology companies still less outward-facing with their AI products, especially in relation to export markets • Confusion within organisations over who leads AI proj ects – from CIOs, CTOs all the way through to specialised Labs, there still hasn’ t been much talk of a CAIO • Overall investment and government support for AI still trails that of S .Korea and China • Regulatory landscape still unclear • Public perception is a huge opportunity to advance more adoption – utilising corporate schemes similar to American Airlines example in the U.S • Long-term prediction by AI Business shows S . Korea may eventually become most AI-enabled economy in the region as pace of acceleration and government investment very high

Key Industry Applications  Financial Services – From Customer Care through to Fraud Prevention and Algorithmic trading; the financial services sector has seen the largest investment already made into developing an AI strategy.  Pharmaceuticals - Drug discovery; Pfizer partnered with IBM Watson to use their cognitive platform to search for new cancer treatments and accelerate the identification of new treatments and therapies.  Retail – Customer experience; In the U.S Bloomingdales are utilising AI’s capabilities for advanced analytics to provider a hyper-personalised customer j ourney  Transport – from Consumer Automotive through to logistics/ freighting/ delivery of shipments; the sector as a whole will see a huge transformation  Legal Sector – Deloitte believes in the UK alone over 110,000 jobs will be displaced by 2020 in the legal sector. Berwin Leighton Paisner a great example of a live applicat ion for document processing wit hout t he need for Associat e or ent ry level human int ervent ion.

Fin Financia ial l Se Servic vices es Increase efficiency /Automated reports / Risk / Improving customer service / Compliance / Fraud Case Study : Intelligent assistant, Luvo, recently made headlines in digital customer support. RBS Piloted among 1,200 staff and now able to deliver; a personalised service, increased accuracy, faster response time, and ultimately happier customers  Now rolled out to over 10% of online customers  Web chat tool – window pop up  Frees advisors to help with more complex issues which improves experience for customers  Built using IBM Watson’s Conversation tool which utilises NLP to make the process more ‘ human’  Luvo will learn from itself over time through Machine Learning meaning - it will later be applied to more complex tasks and problem solving using predictive analytics capabilities to detect problems before they arise further enhancing a customer’s experience. Current investment in AI already $62m in 2016 *Tractica

Enterprise Perspective  What is the impact for humans?  Debate around j ob loss and j ob creation  How do you manage these changes/ building AI advocates within the business?  Does your recruitment process change? - Is there still a need for graduates and other entry level positions? - If not, how do you reshape your development programs for new staff?  Who is responsible for driving the implementation of AI within the organisation?

What the CIOs are saying globally  AI is top of the agenda when looking at new technology investment over the next 3-5 years.  Current spending per application ranges from $100k-$200k but is set to increase to over $1m over the next 3 years.  Current focus is on improving efficiencies, reducing costs, and improving creativity within the business.  Hottest technologies are Machine Learning, Image recognition, NLP , and RP A.  Customer service ranks as the top area of the business where they see the biggest opportunity, followed by Marketing, S ales, and Process Management.  Unemployment and data privacy are among the most pertinent issues CIOs see affecting their organization through implementing AI  Ultimate decision making on AI still sits between multiple roles including, the CIO, CTO, Head of Analytics/ Data, and Business Unit Leads.