What safeguards should companies put in place before using AI for workforce decisions?

Artificial intelligence (AI) is rapidly making a wider and significant transformation for companies in terms of its use at the workstation for different roles. Alongside technical use, the AI is also being highly utilised in several academic and administrative workforces, while solving business problems using human skills along with other tech.

In terms of use, the first approach focuses on using it to automate tasks carried out by employees, while the second involves applying AI-driven analytics and algorithms to automate managerial responsibilities, a practice commonly known as "algorithmic management." Automating specific tasks with AI does not automatically result in job losses, as the technology can also enhance human work by supporting employees in areas where certain functions have been automated.

Whether the adoption of AI leads to workforce reduction or strengthens human roles depends on several factors, including how essential the automated task is to a particular occupation, the way the technology is incorporated into workplace processes, and whether management chooses to retain employees to perform or supervise certain tasks even when automation is technically feasible.

Safeguards to put before using AI

In terms of legality and safeguards while using AI in the workforce, an expert indicated that companies should establish strong governance frameworks before deploying artificial intelligence (AI) for workforce-related decisions.

Prasad Rai, CEO of DAAS LABS, emphasised that organisations should not rely solely on technology when using AI for functions such as hiring, promotions, performance reviews and workforce planning. Instead, he stressed the need for safeguards to ensure fairness, accountability and transparency.

"Before AI is entrusted with workforce decisions, companies need to establish strong governance rather than relying solely on technology. The first safeguard is ensuring that the data used to train AI models is accurate, representative, and regularly audited for bias, because AI will inevitably replicate flaws in historical decisions. Equally important is explainability; every AI-driven recommendation should be transparent, auditable, and easy for leaders to justify. Human oversight must remain central, with AI serving as a decision-support tool rather than the final decision-maker for hiring, promotions, performance reviews, or workforce planning," he said.

According to Rai, companies that earn long-term employee trust will not necessarily be those that adopt AI the fastest, but those that implement it responsibly by placing fairness, accountability and transparency at the centre of their AI strategy.

"Organisations should also implement regular model reviews, clear accountability frameworks, and transparent communication with employees about how AI is being used. The companies that will build lasting employee trust are not those adopting AI the fastest, but those deploying it responsibly, with fairness, accountability, and transparency at the core," he added.