Ascertus blog

Legal AI: What’s driving AI adoption?

Categories: AI

AI holds the mantle of “the” game-changing technology of the 21^st century. AI has made its way into our daily lives, almost becoming invisible and ubiquitous – online shopping, wearables, social media, personal assistants, chatbots, and more – using a variety of technologies including machine learning and natural language processing to deliver personalised customer experiences.

Today, in business operations, AI can optimise supply chains, predict market trends, and streamline processes. For customer service, AI-powered chatbots and virtual assistants provide 24/7 support. In marketing, AI enables targeted advertising and content recommendations. Enterprises benefit from AI in cybersecurity, fraud detection, data protection, compliance, and risk assessment. Healthcare is leveraging the technology for diagnostics, and the list goes on.

The AI wave

Adoption of AI grew a whopping 270 percent between 2015 and 2019. We haven’t even scratched the surface. The global AI market is forecast to reach $1.81 trillion by 2030, growing by over 13 times over the next decade.

The UK AI market itself is worth a substantial £16.8 billion, estimated to grow to £801.6 billion by 2035. Interestingly, the IT and telecommunications (29.5%) and legal (29.2%) are neck and neck when it comes to AI adoption.

However, it is generative AI that has made AI the “game changer”. Generative AI has surged in popularity due to its ability to create content rapidly and efficiently. It can produce text, images, and even code, saving time and resources. The technology has become more accessible, with user-friendly interfaces allowing non-experts to harness its power. Businesses see the potential for increased productivity, while individuals enjoy creative applications. Continuous improvements in quality and capabilities have fuelled widespread adoption across various industries.

Generative AI sparks explosion in legal

Law firms and corporate legal departments alike have astutely spotted the productivity-enhancing potential of generative AI. Law firm Allen & Overy started exploring GPT-4 and Harvey when they were still in beta in November 2022 and by December 2023 had started rolling out a generative AI contract negotiation tool to over 1000 lawyers. More notably, a number of the firm’s clients in the banking, pharma, technology, media, and private equity practices signed up to also use the solution in January 2024.

Clifford Chance was one of the first law firms globally to build its own private and secured AI tool, Clifford Chance Assist, developed on Microsoft's Azure OpenAI platform. Today, Microsoft Copilot for Microsoft 365 is also available across the firm’s workforce.

Many other law firms – DLA Piper, Ashurst, Bird& Bird, Dentons, Irwin Mitchell, Norton Rose (the list goes on) – have all made significant investments in generative AI.

Noteworthy is that in-house legal teams expect their external counsel to adopt generative AI, perhaps having experienced the benefits of this technology first-hand. They recognise the value of this technology to deal with the typically high volume of a variety of low-value tasks – drafting contract templates, reviewing contracts, summarizing copious documents, proofreading, answering repetitive questions, filling in RFPs, and so on. All these time-intensive tasks are ripe for automation and its impact on the costs of external counsel is tangible. This is perhaps why AI is becoming a key criterion in the selection of external law firms, with 72 percent of law departments requiring the "use of appropriate technologies" when choosing their legal partners.

Why legal is betting on AI?

No legal professional services organisation or corporate legal department can afford to ignore the business-led transformational impact of all forms of AI, not just generative AI. The key business drivers that make AI adoption not just advantageous, but also a business imperative are:

Efficiency: AI markedly streamlines time-consuming tasks such as document review, due diligence, and legal research. By automating these processes, legal professionals can redirect their focus and efforts toward higher-value activities that require nuanced judgment and strategic thinking.

Competitive advantage: Early adopters of AI in the legal sector are already reaping benefits. Firms that fail to embrace AI risk falling behind more innovative competitors. The ability to provide tailored, faster, and more accurate services at competitive prices and in a value-driven manner is a commercial necessity. With AI adoption well on its way to becoming ubiquitous, no legal organisation can afford to abstain from its adoption.

Customer experience: Clients expect responsiveness and care. AI-powered tools can enhance client interactions through faster response times, and more personalised services. This improved customer experience leads to higher client satisfaction, loyalty, and ultimately, retention.

Data-driven: The legal profession generates vast amounts of data in the form of case documents, summaries, clauses, practice notes, contracts, and so on. AI can analyse this information at scale, in a fraction of the time, uncovering insights that can then inform strategic decisions. From predicting case outcomes to optimising pricing strategies, data-driven decision-making reduces risks and enhances firm performance.

Innovation: AI opens doors to new service offerings and business models. Embracing AI fosters a culture of innovation, attracting top talent and positioning the firm as a forward-thinking leader in the legal industry. Travers Smith is a case in point. The firm has established an independent company, Jylo, to take its proprietary AI products to market.

Therefore, AI is not merely a technological upgrade; it's a strategic priority for legal organisations to thrive in an increasingly competitive and digital landscape. By harnessing AI's potential, organisations can drive growth, enhance their value proposition, and secure the firm's future in a rapidly evolving legal market.

Legal AI’s greatest hits thus far

Some of the most common use cases that deliver immediate benefits to the legal sector are:

Legal research and analytics: AI-powered platforms can quickly search vast databases of case law, statutes, and legal documents, providing relevant information and insights to lawyers. These tools can analyse legal trends, predict case outcomes, and identify precedents.

Contract analysis and management: AI systems can review, categorise, and extract key information from contracts, streamlining due diligence processes and contract management. They can flag potential issues, inconsistencies, or non-standard clauses.

eDiscovery: AI tools assist in processing and analysing large volumes of electronic data during litigation, identifying relevant documents, and reducing the time and cost of document review.

Intellectual property management: AI solutions can search patent databases, analyse patent landscapes, and assist in trademark searches, helping lawyers and businesses protect their intellectual property more effectively.

Document automation: AI-powered platforms can generate legal documents, such as contracts or pleadings, based on input parameters and templates, saving time and reducing errors.

Search and knowledge management: AI solutions can help lawyers quickly find work products such as examples, checklists, legal updates, templates and so forth. Likewise, AI can be utilised for submission of knowledge documents, automatic classification and extraction, saving lawyers and knowledge managers time.

Predictive analytics: By analysing historical case data, AI can predict litigation outcomes, settlement values, and case durations, aiding in strategy development and risk assessment.

Virtual assistants: These AI-driven tools can answer basic legal questions, provide initial guidance to clients, and assist with client intake processes. Similarly, AI tools can automate email filings based on pre-defined settings, email analyses and lawyers’ past behaviours.

Billing and time management: AI systems can analyse time entries, suggest appropriate billing codes, and identify inefficiencies in legal workflows.

Compliance management: AI tools can help organisations stay compliant with changing regulations by monitoring legal and regulatory updates and flagging potential compliance issues. It can help with conflict checking and know your customer processes, which when manually undertaken are error-ridden and time-consuming.

Legal risk assessment: AI can analyse an organisation's data, contracts, and operations to identify potential legal vulnerabilities and compliance issues. These systems can prioritise risks based on likelihood and potential impact, allowing legal teams to proactively address the most critical issues and develop targeted risk mitigation strategies.

This list is by no means comprehensive. AI solutions for these use cases (and more) are genuinely transforming legal practice, enabling lawyers to work more efficiently and provide more data-driven, cost-effective services to clients.

See the new iManage AI features to help streamline document and email management

Legal Ai challenges

While AI offers significant advantages, there are challenges. Businesses must navigate these challenges to harness AI's full potential and maintain competitiveness in an increasingly digital world.

Data quality and integration: Legal organisations often struggle with fragmented, unstructured data across various systems. Ensuring data quality and integrating diverse data sources is crucial for effective AI implementation but this process can be complex and time-consuming.

Accuracy and reliability concerns: AI systems can make errors or produce unexpected results. In the legal field, where often accuracy and precision are crucial, training systems to ensure AI outputs are accurate and reliable is a significant challenge. Data quality is paramount.

Ethical and privacy concerns: AI use in the legal context raises ethical questions about decision-making transparency, potential bias, data protection, and client confidentiality.

Compliance: Staying compliant with evolving regulations while simultaneously adopting a rapidly developing AI technology can be complex. In addition to a myriad of existing data protection regulations, there’s the EU’s AI Act alongside other similar country-specific legislations. Some courts are also introducing rules about the use of generative AI to ensure transparency of content and data sources for documents submitted and judicial decisions.

Fear of job loss: Technology replacing humans has been a longstanding discussion in legal, but with generative AI, this fear (and perception) of job displacement and even loss of traditional legal skills has never been greater. Overcoming this cultural resistance requires careful change management and education. For instance, while AI can automate many routine tasks, human skills for client interaction, negotiation, strategy development, critical evaluation, courtroom advocacy, and such high-value activities are vital requirements.

Cost and ROI uncertainty: Implementing AI solutions can be expensive, and the return on investment may not be immediately clear. Law firms and legal departments may struggle to justify the initial costs, especially in this early phase of the technology.

Vendor selection and management: With numerous AI solutions available, selecting the right vendors and managing relationships can be difficult, especially for organisations with limited IT resources and expertise. Likewise, knowing which types of AI skills will deliver the most benefit to the organisation can be difficult.

Addressing these challenges requires a strategic approach, involving collaboration between legal professionals, technologists, AI experts, and vendors to develop and deploy solutions that enhance traditional legal processes and ways of operating.

AI for pragmatic innovation

The recent advancements in artificial intelligence have left many in awe, from language models that can converse fluently to AI-generated art that rivals human creativity. At the same time, as the hype subsides, we will see a more practical approach to AI adoption in the form of augmented intelligence and pragmatic innovation. In fact, we already are – document management in its broadest form is a case in point.

What are the drivers for legal AI?

Efficiency and productivity, competitive advantage, customer experience, data-driven legal services delivery and innovation.

Is legal AI adoption slowing?

On the contrary, legal AI adoption is increasing at a rapid pace in law firms, driven by their own innovation-led aspirations and expectations from corporate legal departments. However, adoption rates in corporate legal departments themselves range from slow to moderate, primarily on account of budget constraints.

Are both law firms and corporate departments deploying legal AI?

Most organisations in the legal sector are either already deploying and using AI in some form or have plans to implement the technology in the imminent future.