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

• t 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

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

Th The Op e Opportunit ity y for B Busin ines ess 1/2 1/2

$357 million – Worldwide Enterprise AI Investment in 2016 *Tractica

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

Th The Op e Opportunit ity y for B Busin ines ess 2/2 /2

$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

• f 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%
• f overall potential



AI Business researched FTS E100 and Fortune 500 organisations in 2016 and found that 32% are already implementing some form of AI



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.

AI AI-ena nabl bled E d Ent nterprise se: Curr Current t State te of

• f Pla

lay

Who is

• is develop

lopin ing g th the te tech chnolo

• logy?



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%

• f investments are made at S

eed or S eries A



Corporate Investors overshadowing VC investment with more than $1 billion invested

*S

• urce CB Insights

Hottest Areas

Healthcare focused companies leading the way with more than $500m

• f start-up investment in the past 2 years

*S

• urce 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%

• f 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

• ftbank, S
• ny, 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 RBS : Intelligent assistant, Luvo, recently made headlines in digital customer support. 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%

• f 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

• rganisation?

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.

Top-down strategy

Where does AI sit within the business?

• Traditionally the remit of the CIO, but more widespread applications mean

AI is now relevant to the entire board – most of all the CEO

• No two businesses are yet following the same thought-process for where to

hand responsibility – causing paralysis in some cases

• New roles appearing including CDO, and CAO mean there is even further

confusion as to where AI belongs

• The argument for when we start to see the CAIO has already begun

The The C CAIO

Gettin tting s g starte rted

Setting an AI strategy is vital for today’s enterprise:



Decide where to start within the organisation



Allocate responsibility to a department for heading the project and implementation



Ensure the board is involved in the process from inception to delivery



Plan for the recruitment of new expertise



Choose the right partner – there’s many and more are born every minute!



Set specific pilot projects and with realistic time-scales and desired

• utcomes

Decision-making & planning stages

Change management

• How will staff be impacted by the implementation of AI?
• Which roles will need to be re-shaped and how will that impact the

business as a whole? Measuring success

• Looking at the business impact and having a results driven approach
• Reviewing new partners as they enter the space with new solutions and

technologies

• Keeping pace with technology advancement and areas for optimisation

Implementation & Evaluation Stage



The world’s leading news portal and online community on Artificial Intelligence for enterprises



www.aibusiness.com



Twitter Handle (50k+ followers): @business_AI



Linkedin Group: Artificial Intelligence for Business



Facebook Page: Artificial Intelligence for Business (facebook.com/aibusinessnews)



YouTube: AIB TV



The world’s first and largest event series for business professionals with an interest in Artificial Intelligence



Summits in London, San Francisco, New York, Tokyo, and Hong Kong



www.theaisummit.com



During dinner discuss among your peers the below topics – the end goal is to compile 5 key takeaways per roundtable on the specific topic set out.



Y

• ur table leaders will facilitate the discussion and ensure you are all able to get your perspective

across.



We will then feedback to our moderator Clint Wheelock and a summary will be emailed out with the key findings.

Topics

1.

Technologies with the biggest opportunity

2.

AI and Ethics – how to regulate

3.

Workforce Transformation

4.

Where to focus your investment in Practical AI solutions

5.

AI in your sector – what are the challenges and opportunities as you see them

Roundtable Discussion

E: daniel@ aibusiness.org