The Next Decade (or so) of Legal AI
In the past few years or I’ve observed how artificial intelligence has been starting to reshape the legal workflow.
Over the next decade, AI won’t just streamline processes it will fundamentally alter how we practise law.
2024–2026: Embracing Practical AI Tools and ‘Wrappers’
In the immediate future, we’ll see a surge in AI applications tailored for legal professionals. Many (99.9%) of these will be built upon existing generative AI models, providing user-friendly interfaces and functionalities specific to legal needs. Now people might label them as “thin wrappers,” but this overlooks their practical benefits.
These tools simplify complex AI models, making them accessible to those without a technical background, and if they offer intuitive interfaces, integrate with our existing software through APIs, and allow customisation to fit our workflows then we're in for some interesting years.
The real value lies in utility. If a tool saves time, reduces errors, and integrates smoothly with our systems, it’s worth adopting, even if it’s built on top of an existing AI model. The focus should be on the problems these tools solve rather than the novelty of the underlying technology.
Advancements in Natural Language Processing
I expect over the next couple of years significant improvements in natural language processing (NLP) will enable AI to better understand and interpret complex legal language. Current AI models often struggle with the nuances and specialised terminology inherent in legal documents. Advancements will allow for more accurate parsing of contracts, legislation, and case law.
This progress means that AI will become an indispensable assistant in tasks like document review and due diligence. Lawyers can rely on AI to identify key clauses, flag potential risks, and suggest edits that align with current laws and regulations. The time saved can be redirected towards strategic thinking and client engagement.
2026–2029: The Ethical Reckoning and Regulatory Landscape
As AI becomes more embedded in legal practices, an ethics reckoning is inevitable. Starting around 2026, the legal industry will confront challenges posed by AI’s increasing role, particularly concerning accountability, transparency, and fairness.
Bias and Fairness in AI Applications
AI systems learn from historical data, which may contain biases. In areas like corporate law, these biases might be less apparent due to the standardised nature of transactions and documents. However, in fields such as employment, immigration, family, and criminal law, biases can have profound and unjust impacts on individuals.
Employment Law: AI tools might unintentionally perpetuate discrimination by reflecting biases present in historical employment data. This could affect case assessments, settlement recommendations, or the identification of discriminatory practices.
Immigration Law: AI systems used to evaluate applications or predict outcomes could disadvantage certain groups if trained on biased data, affecting visa approvals or asylum cases.
Criminal Law: Predictive policing tools and risk assessment algorithms have been criticised for reinforcing systemic biases, potentially leading to unfair sentencing or targeting of specific communities.
These areas often involve vulnerable populations, making the ethical implications of AI bias even more significant.
Addressing Ethical Challenges
The integration of AI into legal processes raises some important thoughts:
Accountability: If an AI system provides faulty advice or overlooks critical information, who is responsible, the developer, the user, or the firm?
Transparency: Legal professionals and clients need to understand how AI tools reach their conclusions. Opaque models can erode trust, especially when dealing with sensitive matters affecting individuals’ rights.
Regulatory Compliance: There will be a need for guidelines and standards governing AI use in legal contexts. Compliance will become crucial, much like adherence to data protection laws today, we will see GDPR for AI sooner rather than later.
Fine-Tuning AI Models and the Importance of Diverse Datasets
If law firms decide to fine-tune AI models to better suit their specific needs, it’s essential to use diverse and representative datasets. Fine-tuning can enhance a model’s performance in specialised areas, but without careful consideration, it may also reinforce existing biases.
Diverse Data Collection: Firms must ensure that the data used for fine-tuning encompasses a wide range of cases and perspectives, particularly in sensitive areas like employment and immigration law.
Pressure on Model Builders: It’s incumbent upon firms to advocate for responsible practices from AI developers. This includes urging model builders to address inherent biases in their base models and to be transparent about the data and methodologies used.
By collaborating with AI providers, firms can contribute to the development of models that are fairer and more equitable. This partnership is crucial in mitigating bias and ensuring that AI tools serve the best interests of all clients.
Embracing Advanced AI Tools
Despite the challenges, this period will also see the development of more sophisticated AI tools. We’ll witness AI systems that can learn from interactions, adapt to individual work styles, and offer personalised assistance. These tools will handle routine tasks like scheduling, email management, and initial client interactions - the stuff no one wants to do but has to.
Criticism of AI tools as “thin wrappers” may persist, but the focus should remain on their functionality and benefits. If a tool improves efficiency and integrates well with existing workflows, it deserves consideration regardless of its construction.
2030–2035 & onwards: Redefining Legal Practice in an AI-Integrated World
As we move into the next decade, AI will evolve from a helpful assistant that you need to prompt to a proactive collaborative partner, these systems will not only execute tasks but also provide strategic insights, predict legal trends, and support decision-making processes.
AI as a Collaborative Partner
AI will analyse patterns across jurisdictions, assess how judges might rule based on historical data, and suggest innovative legal strategies. This assistance will augment a lawyer’s expertise, leading to better outcomes for clients.
As ever, AI will augment lawyers, never replace.
In areas like employment and immigration law, AI could help identify systemic issues or predict the impact of legislative changes on specific populations. However, it’s crucial that these tools are designed to avoid reinforcing existing biases.
Ethical and Regulatory Maturity
By this time, ethical frameworks and regulations governing AI in legal practice will have matured. Law firms will have established best practices for AI deployment, and industry wide standards will ensure accountability and transparency.
New Legal Roles and Skill Sets
The integration of AI will redefine legal roles. There will be a demand for professionals who understand both law and technology legal technologists who can bridge the gap between developers and practitioners. Continuous learning will become essential, focusing on tech literacy alongside traditional legal education.
And so...
The next decade holds immense promise for AI in the legal sector. While scepticism around AI tools, especially those perceived as mere “wrappers” over existing models, is natural, it’s important to assess these tools based on their utility and integration capabilities. If they enhance workflows, improve client outcomes, and can be tailored to our needs, they are valuable assets.
At the same time, we must navigate the ethical and regulatory challenges that come with AI’s expanding role. By proactively addressing issues of bias, accountability, and transparency particularly in areas where individuals’ rights and livelihoods are at stake, we can ensure that AI serves the best interests of both legal professionals and on clients.
If firms decide to fine-tune AI models, they must prioritise the use of diverse datasets. This approach helps mitigate the risk of perpetuating biases present in historical data. However, firms cannot do this alone; it’s essential to pressure model builders to address inherent biases within their base models. Collaboration between law firms and AI developers is crucial to develop tools that are both effective and fair.
Embracing innovation while upholding our ethical obligations will be key. The tools we adopt and the standards we set today will shape the future of legal practice, so we will need approach this future with openness, diligence, and a commitment to excellence, ensuring that AI enhances law rather than inadvertently undermines it.