Fast Company<\/em>. \u201cIn fact, we often say that the \u2018portal-to-ticket’ era is dead. Agents can help resolve routine queries autonomously, freeing people leaders to focus on what only humans can do: high-value culture building and strategic talent development.\u201d<\/p>\nChetan says the long-term vision centers on humans and agents working together. Not everyone is convinced the shift is heading in the right direction.<\/p>\n
An Inevitable Yet Unsettled Future<\/h2>\n
Experts argue that the move from automation to autonomy introduces new risks, especially in a domain where decisions have direct human consequences. Regulation is one factor. New laws in the U.S. and Europe are beginning to govern how companies use AI in hiring, particularly around bias, transparency, and candidate rights. In 2025, both Workday and Amazon faced high-profile claims of AI-driven employment bias, intensifying scrutiny and political pressure for clearer rules.<\/p>\n
But regulation is only part of the challenge.<\/p>\n
\u201cIn HR, where decisions directly impact people, the biggest concerns are hidden bias and over-reliance on AI as decision-makers rather than signal generators,\u201d says Dr. Helen Gu, founder and CEO of InsightFinder AI.<\/p>\n
Gu notes that AI still struggles with less tangible factors like context, collaboration, and culture. \u201cThere is a real risk of overfitting models to what can be measured while ignoring what actually matters,\u201d she says. \u201cWhen systems influence hiring or workforce planning, you need continuous visibility into how those models behave and where they may be drifting.\u201d<\/p>\n
Others point to strategic risks.<\/p>\n
\u201cOrganizations may end up using AI to execute broken strategies more efficiently,\u201d says Hemant Kapadia, CFO at Anaplan. \u201cDeploying agentic AI in that environment is not progress. It is just automating chaos at a speed no human can control.\u201d He says companies focused only on automation and cost reduction risk creating systems that are difficult to understand and govern. \u201cThe real opportunity is to use AI as a decision intelligence layer that drives growth.\u201d<\/p>\n
Vendors building these systems push back on the idea that AI replaces human judgment. They say most AI outputs are probabilistic and still require interpretation, especially in high-stakes decisions. \u201cOur systems are designed so that the final decision, whether it is hiring or internal promotion, remains with humans. That balance is critical,\u201d says Mahe.<\/p>\n
Chetan adds that agentic AI \u201cis an amplifier of human judgment, not a substitute,\u201d noting that modern HR demands already exceed what teams can handle manually. Expecting leaders to respond to every query and oversee every outcome risks burnout in a function that is already stretched thin.<\/p>\n
If Phenom\u2019s vision holds, enterprise leaders will face growing pressure to manage more complex workforces while adapting to rapid technological change. Integrating AI into HR will require reworking organizational systems and underlying data structures, alongside new roles focused on oversight.<\/p>\n
\u201cEntirely new job categories are already emerging, where someone is constantly observing how agents behave, identifying where systems break, and deciding when to intervene, whether that means inserting a human into the loop or recalibrating the orchestration itself. As organizations deploy agents more broadly, I expect the nature of HR roles to evolve, helping enterprises make better decisions with clear and traceable accountability,\u201d says Mahe.<\/p>\n
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