A former Google executive has ignited a fierce debate about the future of professional education, arguing that the traditional paths to becoming a doctor or lawyer may no longer justify the years of study and hundreds of thousands of dollars in tuition they demand. The reason? Artificial intelligence is advancing so rapidly that by the time today’s incoming students earn their degrees, the skills they spent years acquiring could already be performed by machines.
Mo Gawdat, the former chief business officer of Google X — the tech giant’s experimental research division — made the provocative claim during a recent interview, asserting that degrees in law and medicine are effectively “a waste of time” given the pace at which AI capabilities are accelerating. His comments, reported by MSN, have struck a nerve among educators, students, and professionals who have invested deeply in these career tracks.
A Silicon Valley Insider’s Warning to the Next Generation
Gawdat’s argument centers on a straightforward calculation involving time. A medical degree in the United States typically requires four years of undergraduate study, four years of medical school, and three to seven years of residency — a commitment that can stretch more than a decade. Law school demands three years after an undergraduate degree. During those lengthy training periods, Gawdat contends, AI systems will have advanced to the point where they can perform many of the cognitive tasks that define these professions, from legal research and contract analysis to medical diagnosis and treatment planning.
“By the time you graduate, AI will be able to do what you spent all those years learning,” Gawdat has argued in various public appearances. His position is not that doctors and lawyers will vanish entirely, but that the economic proposition of spending years and accumulating significant debt for these careers no longer makes rational sense for many prospective students. The former Google X executive has been vocal about AI’s trajectory since leaving the company, authoring books and speaking widely about how artificial intelligence will reshape work and society.
The Numbers Behind the Professional Education Gamble
The financial stakes of Gawdat’s argument are enormous. According to the Education Data Initiative, the average medical school graduate carries approximately $202,000 in student loan debt, while law school graduates average around $130,000. When combined with undergraduate debt and the opportunity cost of years spent out of the workforce, the total investment can easily exceed $300,000 for aspiring physicians and $200,000 for lawyers. These figures assume that graduates will enter high-paying professions where they can recoup their investment over decades of practice.
But the return on that investment depends on the assumption that the professional skills being acquired will remain valuable throughout a career spanning 30 to 40 years. If AI systems can perform significant portions of legal and medical work within the next five to ten years, that assumption begins to crack. Already, AI tools are demonstrating remarkable capabilities in both fields. OpenAI’s GPT-4 passed the Uniform Bar Examination with scores in the 90th percentile when it was tested in 2023. AI diagnostic tools have matched or exceeded the accuracy of experienced radiologists in detecting certain cancers in medical imaging studies.
Where AI Is Already Encroaching on Professional Territory
The evidence supporting at least part of Gawdat’s thesis is mounting. In the legal profession, AI-powered tools are already handling document review, contract analysis, and legal research at speeds and costs that no human associate can match. Major law firms including Allen & Overy have adopted AI assistants for routine legal work. JPMorgan Chase developed an AI system called COiN that can review commercial loan agreements in seconds — work that previously required approximately 360,000 hours of lawyer time annually.
In medicine, the advances are equally striking. Google’s own DeepMind division developed AlphaFold, which solved the protein-folding problem that had stumped biologists for decades. AI systems are being deployed in pathology labs, emergency departments, and primary care settings to assist with diagnosis. Companies like Viz.ai are using artificial intelligence to detect strokes from CT scans faster than human radiologists, potentially saving lives through faster treatment. The FDA has approved hundreds of AI-enabled medical devices, and the pace of approvals is accelerating.
The Counterargument: Why Human Professionals Still Matter
Not everyone agrees with Gawdat’s assessment, and the pushback has been substantial. Critics argue that his view reflects a fundamental misunderstanding of what doctors and lawyers actually do. Medicine is not simply pattern recognition and diagnosis — it involves physical examination, surgical procedures, patient communication, ethical decision-making, and the kind of empathetic human connection that no AI system can replicate. A surgeon performing a complex operation or a physician breaking devastating news to a family requires skills that extend far beyond what any algorithm can deliver.
Similarly, the practice of law involves courtroom advocacy, client counseling, negotiation, and the exercise of judgment in ambiguous situations where the law is unclear or contested. While AI can draft a contract or summarize case law, it cannot stand before a jury, build trust with a frightened client, or make the kind of strategic decisions that define high-stakes litigation. Legal scholars have pointed out that the profession has absorbed technological disruption before — from Westlaw to e-discovery — without eliminating the need for human lawyers.
The Middle Ground: Adaptation Rather Than Elimination
A more nuanced view is emerging among those who study the intersection of AI and professional work. Rather than wholesale replacement, many experts predict a transformation of these professions that will change what doctors and lawyers do on a daily basis without eliminating the need for their expertise. Physicians may spend less time on diagnostic work and more time on complex decision-making, patient relationships, and procedures. Lawyers may shift away from research-heavy tasks toward advisory roles, advocacy, and the kind of creative legal thinking that AI cannot replicate.
This transformation, however, does raise legitimate questions about how many professionals these fields will need. If AI can handle the work that currently occupies junior associates at law firms or first-year residents in hospitals, the pipeline of entry-level positions could shrink dramatically. That would mean fewer job openings for new graduates, potentially undermining the economic case for expensive professional degrees even if the professions themselves survive. The structure of professional education may need to change — perhaps becoming shorter, more focused on the skills AI cannot replicate, and less burdened by the traditions that have kept medical and legal training lengthy and expensive.
What Students Facing These Decisions Should Consider
For the millions of students currently weighing whether to pursue professional degrees, Gawdat’s comments add urgency to an already difficult calculation. The decision to attend medical or law school has always involved significant risk — not every graduate secures a high-paying position, and burnout rates in both professions are notoriously high. Adding AI disruption to the equation makes the calculation even more complex.
Some educators are already responding. Law schools are integrating AI literacy into their curricula, teaching students to work alongside AI tools rather than compete with them. Medical schools are beginning to emphasize skills like complex clinical reasoning, interpersonal communication, and procedural expertise that are harder for AI to replicate. The schools that adapt fastest may produce graduates who are better positioned to thrive in an AI-augmented professional world.
The Broader Question About the Future of Expertise
Gawdat’s provocation touches on something larger than the future of any single profession. It raises fundamental questions about the value of human expertise in an age of increasingly capable machines. If AI can pass the bar exam and diagnose diseases from medical images, what does it mean to be an expert? What is the value of the years of training, the clinical rotations, the moot court competitions, and the grueling examinations that have traditionally served as gatekeepers to these professions?
The answer may be that expertise itself is being redefined. The most valuable professionals of the future may not be those who have memorized the most case law or can recall the most diagnostic criteria, but those who can synthesize information from AI systems, exercise judgment in complex situations, communicate effectively with other humans, and bring ethical reasoning to bear on difficult decisions. Whether that requires a traditional seven-year medical training program or a three-year law degree is a question that institutions, regulators, and students will be grappling with for years to come. What seems certain is that the status quo — expensive, lengthy professional education programs designed for a pre-AI world — will face mounting pressure to justify their cost and duration as artificial intelligence continues its rapid advance.