How AI technology can make ‘light work’ of data discovery

Law firms are facing a number of challenges in a modern, globalised world. There is a huge amount of data, and collective wisdom, in the sector that law firms are unable to utilise without embarking on costly, labour-intensive processes. There is also a burgeoning demand for tools that have been developed with cognizance of the time pressures that lawyers are facing.

PwC’s Legal Firm Survey for 2021 demonstrates that firms need to adopt more advanced technology to face the future with confidence. Historically, analysis of the adoption of Artificial Intelligence (AI) technology across six industries: government, healthcare, insurance, legal, science/medical and banking, shows that the legal sector is lagging behind. However, more firms are beginning to realise the value of AI and machine learning technology to support their operations; Statista research highlights that 25% of International Legal Technology Association members are now actively investigating how to utilise AI/machine learning tools as part of their knowledge management strategy to increase productivity and effectiveness. AI technology should be at the top of the agenda for any firm which wants to discover previously inaccessible data and transform this into insights to inform, and improve, their professional practice.

Accessing knowledge is challenging

With large volumes of internal and external data, and no mechanism for easy discovery, legal firms have historically relied on labour-intensive, costly methods of indexing to create their own retrieval systems. The majority of current systems rely on Boolean searching, which enables users to combine keywords and modifiers to retrieve relevant information, but these often yield irrelevant results as the search parameters are so large and there is a lack of context.

There has also been a huge increase in the use of email, video chat, messenger services and other non-traditional channels for dispensing advice and information which is not readily accessible for collation and indexing. Capturing and re-using information conveyed via email, instant message or even video call transcripts is even more complex than with traditional documentation. Being able to quickly find contextually relevant precedents and case files is paramount for law practitioners.

The trend for remote working has resulted in senior partners and decision makers in legal firms using MS Teams, Zoom and other platforms to communicate, hold meetings, and make decisions. Accessing knowledge created in MS Teams, for example, is challenging, especially since one meeting can cover multiple topics and multiple clients.

All of these tools – iManage, email, MS Teams, Sharepoint – have different search interfaces which requires multiple and repeated searches to find information.

AI technology can overcome this by bringing all of these sources of information together in one place, indexing and segmenting the knowledge created, and allowing this to be discoverable. This provides for better and more accurate results and means that decision sources can be quickly and easily identified, increasing business compliance and helping to reduce business risk.

Preparing data for search is labour intensive and costly

Every day, law firms are generating huge amounts of data, including emails, letters and transcripts, and preparing this information for search access is time-consuming. Traditional methods require investing significant amounts of human time and labour to interpret, label and rank data, ready for inclusion in the search database. It is impossible to pre-empt every keyword and synonym that may be used and documents will require multiple labels to prepare for all eventualities that cannot be pre-empted. This leads to irrelevant returns when using traditional search methods. It has been suggested that lawyers and paralegals lose more than 3 hours a week searching, but not finding, the right documents and this wasted time, and subsequent loss of productivity impacts profitability.

Using AI-enabled technology allows a richer input of information as a query, including dragging and dropping full documents into the insight engine – which means results are more accurate, relevant and refined. This is particularly useful for lawyers working on cases, where there are potentially thousands of different results per keyword. The context enabled by AI data discovery refines the returned results to a manageable number that can easily be reviewed and utilised to avoid a loss of productivity.

Lost in translation limitations

With a wealth of information archives worldwide, the data available to today’s lawyers and legal administrators is almost limitless. However, accessing this in an efficient manner can be difficult – especially when the information is in another language and time and money must be spent on translation services to understand the result, let alone apply it to the case in hand.

Being able to access archived information from across the world has huge advantages but translating this information into a common language can be prohibitive. Natural Language Processing (NLP) combined with Neural Networks and deep learning models enable computers to understand the full meaning of information including sentiment and intent without the need for translation.

Using advanced language agnostic AI tools such as those developed by iKVA enables lawyers to discover relevant information regardless of the language it was created in.

Conclusion

Artificial Intelligence, Advanced Machine Learning, Natural Language Processing and Semantic Technology can all be combined to solve the modern legal firm’s challenge of working with siloed unstructured data from almost any source including document archives, email, chat, and video, to maximise productivity, reduce wasted time and improve profitability.

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Professor Jon Crowcroft, iKVA