CEO speaks: Justice in the Age of AI: Challenges & Opportunities
The legal profession, traditionally very cautious in its approach to change, now finds itself at a crossroads shaped by rapid advances in AI. From automating routine legal tasks to influencing judicial decision-making, AI is poised to transform not only how lawyers practice but also how justice itself is administered. This transformation, while still in its early stages, is already prompting significant reflection across courts, law firms, regulators, and academic institutions.
AI has made considerable inroads in augmenting legal workflows. Tasks that once consumed countless billable hours—document review, legal research, and contract analysis—are now increasingly handled by AI-powered platforms. Tools such as Harvey (developed in partnership with OpenAI), Casetext’s CoCounsel, Lexis+ AI, and ROSS Intelligence employ NLP and ML to extract insights from vast repositories of legal information. They can identify relevant precedents, flag inconsistencies, and even draft first-level contract language. As a result, the role of the lawyer is shifting from that of primary researcher to that of strategic advisor and quality controller.
The McKinsey Global Institute estimates that approximately 23% of a lawyer’s workload could be automated using existing AI technologies—a figure that is expected to increase as AI becomes more sophisticated and context-aware. While this may initially be seen as a threat to traditional roles, in practice it is leading to a reallocation of legal expertise towards more complex, judgment-intensive tasks.
AI is also beginning to influence judicial decision making. In the United States, the United Kingdom, and China, risk-assessment algorithms are used to inform bail and sentencing decisions. In Estonia, always pushing the boundaries of technology, a pilot project introduced AI to resolve small claims disputes. However, these developments raise pertinent ethical and procedural questions: To what extent should judges rely on algorithmic recommendations? How can the legal system ensure transparency and accountability when such tools are used?
Such concerns are not unfounded. AI systems trained on historical legal data may perpetuate existing biases, leading to outcomes that are statistically consistent but ethically problematic. The “black box” nature of many ML models—wherein the rationale behind an output is opaque—poses a serious challenge to principles of due process and judicial reasoning. Addressing these risks requires robust regulatory oversight and clear frameworks for the responsible use of AI in legal settings.
Efforts to develop such frameworks are already underway. The European Union’s proposed Artificial Intelligence Act designates the use of AI in judicial and law enforcement contexts as “high risk,” mandating stringent standards for transparency, human oversight, and data governance. In India, the Supreme Court has constituted an AI committee to examine the responsible integration of AI tools in court administration and case management.
For the legal profession, AI is not merely a new technology; it is a new competency. Law firms are investing heavily in digital transformation, and legal technology is now a growing area of practice. Clients increasingly expect lawyers to be conversant with the tools that can deliver faster and more cost-effective legal services. As a result, legal education must evolve in tandem.
Yet, most law schools continue to operate within a traditional framework, often treating technology as peripheral to the core curriculum. This is no longer sustainable. Institutions must integrate AI, data science, and ethics into the foundational training of legal professionals. Courses on algorithmic governance, predictive analytics, and the legal implications of emerging technologies should become part of mainstream legal education.
Some institutions are leading this shift. Harvard Law School now offers integrated courses on AI and law to its students. The National Law School of India University (NLSIU) has initiated discussions on integrating AI into legal pedagogy. Such efforts must be expanded and formalized. Interdisciplinary programs—combining law, computer science, and public policy—can produce graduates capable of shaping both the technological and legal architectures of the future.
Looking ahead, the legal system of the next decade will likely be characterised by hybrid workflows. AI will increasingly handle tasks such as discovery, legal drafting, and even preliminary adjudication in administrative or small claims contexts. Judges will continue to be the final arbiters in complex and value-laden matters, but their work will be informed—and in some cases challenged—by algorithmic insights.
However, amid these advances, it is imperative to recognize that the legitimacy of legal systems rests on human judgment, procedural fairness, and moral reasoning—values that cannot be delegated to machines alone. AI, no matter how advanced, must serve as a tool to enhance, not replace, the human pursuit of justice.
The coming years will test the profession’s ability to harness technological innovation while safeguarding the principles at the heart of the rule of law. This shall help shape a legal system that is more efficient, inclusive, and responsive to the needs of a digital society. However, AI must always remain a tool to expedite justice, guided by human wisdom and ethical scrutiny.
The author is the Group CEO of Techno India Group, a visionary and an educator. Beyond his corporate role, he is also a mentor who guides students towards resilience and self-discovery
