Artificial intelligence and semantic computing technologies can help address challenges facing the legal industry. AI can perform tasks like legal research and contract analytics to help lawyers. It works by analyzing both structured and unstructured data using natural language processing. Semantic computing finds relevant information by understanding relationships between concepts. The legal industry should develop a data strategy, capture different types of data, hire skilled talent, and implement analytic tools to start leveraging AI. This can help automate some legal work and make professionals more efficient.

1. Artificial Intelligence and Legal Industry
It’s not the big that eat the small,
it’s the fast that eat the slow
Presented to

2. Agenda
• Challenges facing the Legal Profession
• What is Artificial Intelligence, and where did it come from
• What is Semantic Computing in AI
• How can AI assist the Legal Profession
• What steps should the Legal Industry adopt to get ready

3. Biggest Issues in the legal industry
• Demand and delivery for services has
changed
• Competition is intensifying and
morphing
• legal services being bought differently
• Company legal departments is just
another shared services
• Cybersecurity will continue to affect
the industry
• Legal industry still not exploiting IT aps
to create seamless working environment
• Legal firms merging to create to add
market share but synergies and value still
elusive
• Firms focus on professionalism in how
they operate, led, and managed
• Changing landscape and a changing
workforce not changing in their talent
model
• There are too many law firms and too
many lawyers
https://bol.bna.com/10-big-issues-facing-the-legal-market-in-2016

4. Five Challenges for Legal Firms Today
• Low-Cost Legal Service Providers
• Technology has also allowed for the creation of legal service providers. offering low-cost legal
services.
• Online legal services also make consumers feel empowered—can get the documents they
need at a lower cost
• Globalization/Competition
• Regulation
• Technology, globalization and competition all play into the regulatory environment of the
legal profession.
• Technology, The Internet And Clients -
• Clients with access to legal information and expect their attorneys will be proactive
• Role of the attorney to educating the client in new ways like sorting through reliable and
unreliable information
• New Lawyer Development
• The younger generation lower learning curve in utilising technology, so challenge will be
about finding the best ways to use new technology

5. Client Engagement Trends
• Clients requesting payments in various types of
alternative fee agreements and less traditional
billable hours
• Clients now utilize metrics, analytics, and data to
gain insight into their legal spend, evaluate counsel,
and benchmark fees etc
• Clients are keeping an increasing amount of legal
work in-house
• Clients use terms “predictability”, “cost certainty”,
and “transparency”

6. Agenda
• Challenges facing the Legal Profession
• What is Artificial Intelligence, and where did it come from
• What is Semantic Computing in AI
• How can AI assist the Legal Profession
• What steps should the Legal Industry adopt to get ready

8. Evolution of Data Analysis
• AI/ Semantic Computing focus is around the Prescriptive Analytics approach
Gartner Descriptive Diagnostic Predictive Analytics**

9. Definition of Artificial Intelligence (1955)

11. Structured vs Unstructured data
• Structured data refers to information with a high degree of
organisation, from a relational database and is seamless and readily
searchable by simple, straightforward search engine algorithms or
other search operations
• machine-language designed for computers
• Data files , CSV
• Unstructured data is essentially the opposite. The lack of structure
makes compilation time and energy-consuming task.
• unstructured data is designed for humans consumption
• Text documents , CCTV video, audio , web pages, social media

12. Different Forms of AI

13. AI Tools Available Today

14. Key Word Search Vs AI/NLP
Key Word
• Keyword searches do not
distinguishing between words that are
spelled the same way but mean
something different
• Search tools still applies the same
keyword pairing principles. So you get
more refined bad results, not more
accurate results.
AL/Natural Language
• Natural Language search systems focus
on meaning and context in the natural
way humans ask and offer answers
• Natural Language is concept-based, it
returns search hits on documents that
are "about" the subject/theme you're
exploring, even if the words in the
document don't match all the words you
query.
https://www.inbenta.com/en/blog/entry/keyword-based-versus-natural-language-search

15. Agenda
• Challenges facing the Legal Profession
• What is Artificial Intelligence, and where did it come from
• What is Semantic Computing in AI
• How can AI assist the Legal Profession
• What steps should the Legal Industry adopt to get ready

16. How Does AI tools Work – Data Flow review

17. How does Semantic Computing Work?

18. Semantic Computing in Action

19. Benefits of Semantic Computing
 Find more relevant and useful information
 Search information from disparate sources (federated search) and
automatically refine our searches (faceted search)
 Better understand what is happening
 Utilise the relationships between concepts to predict and interpret
change.
 Build more transparent systems and communications
 Based on common meanings and mutual understanding of the key
concepts and relationships
• Increase our effectiveness, efficiency and strategic advantage
• Enables us to make changes to our information systems more quickly and
easily.
• Become more perceptive, intelligent and collaborative
• Enables us to ask and answer questions we couldn't ask before.

20. Agenda
• Challenges facing the Legal Profession
• What is Artificial Intelligence, and where did it come from
• What is Semantic Computing in AI
• How can AI assist the Legal Profession
• What steps should the Legal Industry adopt to get ready

21. IT Focus in Legal Industry
• Data strategy and analytics. managing data for
Litigation and M&A will evolve into centrally managing
data and with external specialist firms
• Automated advice. “Algorithmic Law” with
organisations able to leverage online tools /digital
channels to provide advice in Risk & Compliance,
Employment and International Trade.
• Client engagement. As demand for sharing of data
between organisation and firm will generate innovative
ways to provide efficient and accurate solutions for
clients, embedded within their clients business process.

22. Positioning AI in Business Matrix – Legal Industry
http://www.neotalogic.com/ai-business-law-iii-rise-
administrative-automation

23. Examples of where AI helps the Legal Industry
• Knowledge Automation:
• Using intelligent systems, requiring dynamically developed algorithm, to break down complicated
sets of rules eg automate the tax code
• Legal Research:
• Support the Research teams to collect and collate accurate content to implement intelligent
queries against ALL appropriate documents/data for litigation
• Prediction Analysis:
• Streamline and predict the outcome of cases and decisions (M&A).
• Contract Analytics:
• Easier development of corporate documents vs. risk requirements and fraud detection
Michael Mills “AI in Law: The State of Play”
http://www.legalcurrent.com/iltacon-2016-session-ai-in-law-the-state-of-play-in-2016/

24. http://www.slideshare.net/Danielkatz/artificial-intelligence-and-law-a-
primer?ref=http://www.computationallegalstudies.com/2016/07/27/artificial-intelligence-and-law-%E2%80%A8a-
six-part-primer/
Steps to Start
• Develop a Data Strategy
• Legislations, Clients, Matters
• Capture clean , regularised data
• Structured and unstructured
• Source relevant human capital skills
• Legally trained IT literate
• Analytic tools
• Develop environment for Legal Analytics to
grow

25. Thank You…..
Questions ?