Artificial intelligence in professional services Report … · · 2018-04-23Artificial...
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Artificial intelligence in professional services Report summary This document aims to help legal professionals understand why AI is important to their business and how to take it from theory to practice. 1. Understanding AI AI is the theory and development of computer systems able to perform tasks that normally require human intelligence. 1 Previously, lawyers had a limited number of mainly paper-based documents to review, while now they are faced with large quantities of data in different formats. According to the World Economic Forum, the ‘tipping point’ for AI in white collar jobs is expected to fall around 2025. 2 Below is a glossary of the different types of AI technologies that law firms could be using. TECHNOLOGIES Rule‑based systems Capture and use experts’ knowledge to provide answers to tricky problems that are governed by fixed rule‑sets. Robotic process automation (RPA) RPA robots are software programmes designed to automate transactional, rules‑based tasks by mimicking human interactions. Machine learning Takes place without explicit programming. By trial and error, computers learn, mining information to discover patterns in data that can help predict future events. Source: Adapted from Deloitte Centre for Government Insight, 2017. Computer vision The ability to identify objects, scenes and activities in naturally occurring images. Natural language processing The ability of software to read and understand a variety of written documents, such as contracts and websites, in a human way. Speech recognition Transcribes human speech automatically and accurately. The technology improves as the machines collect more examples of conversation. We have provided insight around four key areas: 1. Understanding AI 2. Building a case for AI in professional services 3. From theory to AI strategy 4. Putting AI strategy into practice To explore any area in more detail, please read our full report, or contact a member of our team. A glossary of AI-based technologies Machines with purpose: From theory to practice Report summary
Transcript of Artificial intelligence in professional services Report … · · 2018-04-23Artificial...
Artificial intelligence in professional servicesReport summaryThis document aims to help legal professionals understand why AI is important to their business and how to take it from theory to practice.
1. Understanding AIAI is the theory and development of computer systems able to perform tasks that normally require human intelligence.1
Previously, lawyers had a limited number of mainly paper-based documents to review, while now they are faced with large quantities of data in different formats. According to the World Economic Forum, the ‘tipping point’ for AI in white collar jobs is expected to fall around 2025.2
Below is a glossary of the different types of AI technologies that law firms could be using.
TECHNOLOGIESRule‑based systemsCapture and use experts’ knowledge to provide answers to tricky problems that are governed by fixed rule‑sets.
Robotic process automation (RPA)RPA robots are software programmes designed to automate transactional,
rules‑based tasks by mimicking human interactions.
Machine learningTakes place without explicit programming. By trial and error, computers learn, mining information to discover patterns in data that can help predict future events.
Source: Adapted from Deloitte Centre for Government Insight, 2017.
Computer visionThe ability to identify
objects, scenes and activities in naturally occurring images.
Natural language processingThe ability of software to read and understand a variety of written documents, such as contracts and websites, in a human way.
Speech recognitionTranscribes human speech
automatically and accurately. The technology improves as the machines collect more
examples of conversation.
We have provided insight around four key areas:
1. Understanding AI
2. Building a case for AI in professional services
3. From theory to AI strategy
4. Putting AI strategy into practice
To explore any area in more detail, please read our full report, or contact a member of our team.
A glossary of AI-based technologies
Machines with purpose: From theory to practiceReport summary
2. Building a case for AI in professional servicesWhy should professional services consider AI? Why should they look to improve the efficiency of their operations, especially as the business models in the sector have tended to evolve around hourly charge rates? Fewer hours spent would therefore mean less revenue, wouldn’t it?
Put simply, professional services companies should consider AI because they have no choice. Their clients are asking for more efficient and cost effective services; their staff want to spend more time on value-adding activities; and the financial incentives are improving as the cost of technology declines.
Source: Deloitte, 2018
CLIENTDEMANDS
STAFFEXPECTATIONS
ADOPTING AIIN PROFESSIONAL
SERVICES
FINANCIALGAINS
FASTER RESPONSETO CLIENTS
Source: Deloitte, 2018
Review existing plans
and processes, e.g. talent, operations
Analyse internal and
external risks relating to
AI use
AI STRATEGY
• What is AI? Do we understand the technology and what it can and cannot do?
• What are the business issues that AI could help us solve?
• Are our existing processes working well? Can AI be used as part of those?
• What impact does using AI have on our talent and recruitment plans now? How will these need to change in the future?
• Do we need to work with external parties to help us get and develop the talent we need?
• What is our risk appetite with respect to AI?
• What are the key external and key internal risks?
• How can we mitigate against these?
• Explain what you plan to do with AI
• Describe how it will benefit the organisation as well as different functions/groups of employees
• Consult with people about their views on the proposed approach
Agree on aims and
role of AI in implementing
business strategy
3. From theory to AI strategyAdopting AI for the sake of ‘ticking the box’ will not generate return. Professional services must assess how AI fits in with their strategy and ambitions.
The first step in the AI adoption process should always be the formulation of an AI strategy. This should focus on building an understanding of how AI as a capability could solve the key challenges the business is likely to face in implementing its current strategy.
Adopting AI for the sake of ‘ticking the box’ will not generate return. Professional services must assess how AI fits in with their strategy and ambitions.
Reasons to adopt AI in professional services
Building an AI strategy
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Machines with purpose: From theory to practice Report summary
4. Putting AI strategy into practiceKeeping the AI strategy and higher level business objectives at the heart of the implementation process is crucial for the successful implementation of AI.
It is important to be realistic about what AI can achieve. AI projects often try to start in the most complex and difficult areas. Instead they should focus on relatively simple activities.
The process of implementing AI
Proof of ConceptRapidly test and evaluate the
feasibility of solving the business problem with a selected AI tool and
draft the business case for the next stage
Production pilotTake the POC into production with a defined, narrow scope to test the
solution in the real environment and validate the business case
Scale upImplement the technology at the desired scale, identify roadmap
and expansion options
An AI‑powered system could be trained to empower legal professionals to quickly answer specific types of questions of the documents given, e.g. “How many contracts related to the issue of XYZ are under English governing law?”
It would carry out the following stages:
Search and index • Traverses document management systems, file systems and email servers to identify and tag documents
Interpret and annotate • Reads the contents of each contract
• Identifies contracts likely to be related to each other
• Identifies clauses of certain types, interprets dependencies between clauses
• Creates metatags to capture all analysis outputs
Present results • Visualises outputs of its findings
How would an AI system for contract analysis work?
Keeping the AI strategy and higher level business objectives at the heart of the implementation process is crucial for successful implementation of AI.
1. Demystifying artificial intelligence: What business leaders need to know about cognitive technologies, David Schatsky, Craig Muraskin, Ragu Gurumurthy, Deloitte Insight, November, 2014. 2. Deep Shift Technology Tipping Points and Societal Impact: Survey report, Global Agenda Council on the Future of Software and Society, World Economic Forum, 2015.
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Machines with purpose: From theory to practice Report summary
This publication has been written in general terms and we recommend that you obtain professional advice before acting or refraining from action on any of the contents of this publication. Deloitte LLP accepts no liability for any loss occasioned to any person acting or refraining from action as a result of any material in this publication.
Deloitte LLP is a limited liability partnership registered in England and Wales with registered number OC303675 and its registered office at 2 New Street Square, London EC4A 3BZ, United Kingdom.
Deloitte LLP is the United Kingdom affiliate of Deloitte NWE LLP, a member firm of Deloitte Touche Tohmatsu Limited, a UK private company limited by guarantee (“DTTL”). DTTL and each of its member firms are legally separate and independent entities. DTTL and Deloitte NWE LLP do not provide services to clients. Please see www.deloitte.com/about to learn more about our global network of member firms.
© 2018 Deloitte LLP. All rights reserved.
Designed and produced by The Creative Studio at Deloitte, London. J14496
Peter SaundersLead partner, Professional Practices Group+44 (0)20 7007 [email protected]
Jeremy BlackProfessional Practices Group Audit Partner+44 (0)20 7007 [email protected]
Karen McNichollsProfessional Practices Group Tax Partner+44 (0)20 7007 [email protected]
Paul Garel-JonesPartner, AI and RegTech Lead+44 (0)20 7303 [email protected]
Jarrod HaggertyPartner, Financial Assurance+44 (0)20 7007 [email protected]
Oliver HemmingPartner, Consulting+44 (0)20 7007 [email protected]
Danny McConnellPartner, Technology Consulting+44 (0)2890 53 [email protected]
Matt HowardDirector, AI Technology Monitor Deloitte+44 (0)20 7007 [email protected]
Alan TuaDirector, Risk Advisory AI lead +44 (0)20 7007 [email protected]
Nick ConwayDirector, Financial Assurance+44 (0)20 7007 [email protected]
Aino TanManager, Insight+44 (0)20 7007 [email protected]
Other contributorsTom Bigham, Philip Brocklehurst, Tom Brunt, Michelle Lee, Karol Satka and Laila Takeh
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