“Human in the Loop”: How AI Is Reshaping Power and Accountability at Work
Artificial intelligence has moved well past helping employees draft emails. In conversation with Dominic Bowen, employment lawyer Andrew Adams, Practice Leader of the Labor & Employment Practice Group at DarrowEverett LLP, laid out just how far algorithms have already moved into hiring, management, and termination decisions — and how unprepared most organisations are for what comes next.
Hiring Is Where the Legal Risk Is Clearest
Adams pointed to a discrimination lawsuit against Workday’s AI-powered hiring software as an example of where these risks are already playing out. The allegations, he explained, involve resumes being filtered out on the basis of protected characteristics such as race, age, or disability — without ever being reviewed by a human at the employer’s end. His concern isn’t the technology itself so much as its removal of human judgment from the process entirely: “there is no circumstance,” he said, “in which I, as an employment lawyer, would ever recommend that a full decision be made or a full workflow go through without a human in the loop.”
AI Can Be Pushed Toward the Answer Someone Wants
Adams also raised a Delaware Chancery Court case tied to the video game Subnautica, in which a company executive was found to have repeatedly prompted ChatGPT until it endorsed a course of action that would let him avoid a bonus payout to former owners. The court saw through it, reinstated the bonus, and put the individuals back in place. For Adams, the case illustrates that AI tools aren’t neutral arbiters — they tend to respond in ways that give the user the answer they’re looking for, and that output degrades in reliability the harder someone pushes for a particular result.
Shadow AI: A Leadership Problem, Not Just an Employee One
On the subject of employees quietly using their own AI tools at work, Adams pushed back on the instinct to treat this as simply a compliance failure. Employees are always going to want to use these tools, he argued, “because it’s so integrated into day-to-day life now” — and if a company doesn’t put sanctioned tools and training in place, employees will find a way to use AI externally regardless. His specific concern: a sales team member pulling up an external ChatGPT and feeding it client data or prospect lists, entirely outside company oversight.
Surveillance, Trust, and the Limits of Monitoring
Asked about the monitoring technologies that have proliferated since remote work became normal — keystroke logging, screenshotting, activity tracking — Adams argued the deeper risk is cultural rather than legal. Over-monitoring, he said, builds distrust with employees, “especially remote employees that are your high performers,” and that distrust tends to produce exactly the disengagement it was meant to prevent. His recommendation: train managers to evaluate output and empower employees, and build compliance safeguards into AI systems on the back end rather than watching every keystroke on the front end.
Succession Planning Is Quietly Breaking Down
Adams also flagged a less-discussed risk: as firms — his own industry included — lean on AI instead of hiring the next generation of associates or junior staff, the traditional apprenticeship model that trains future senior talent is eroding. Established partners and “rainmakers” building AI-driven practices, he noted, often have little incentive to worry about succession planning while revenue holds up, leaving a training gap he doesn’t think most organisations are currently planning for.
Who Actually Owns AI Risk?
Asked directly who inside a company should be responsible for AI-related employment risk, Adams answered simply: everyone. He argued it has to be a board-level and senior-leadership conversation, because HR, IT, legal, and marketing are all deploying AI tools independently — and without open communication between departments, gaps open that can expose the company to real risk.
Three Things Every Leader Should Prioritise
Asked what practical steps a CEO should take over the next twelve months, Adams narrowed it to three: learning, training, and implementation. Leaders need a basic understanding of how AI affects their industry; employees need real training on both use and compliance; and organisations need to actually put sanctioned tools in place — “because they’re going to want to use it, and they’re going to use it on the side if they don’t have access to it in one format or another.”
Across the conversation, Adams’ throughline is consistent: the danger isn’t AI itself, but the absence of human oversight, cross-department communication, and leadership that treats AI governance as someone else’s responsibility. As algorithms take on a larger role in hiring, management, and monitoring, that gap — more than the technology — is what’s most likely to end up in front of a judge.
