AI accelerated hiring at one of F1's most complex race operations. But it didn't get the final say
The scale of a Formula 1 race weekend is difficult to overstate. Behind the spectacle sits a vast workforce operation that must recruit, train, and coordinate thousands of people under strict deadlines. For Irana Ahmedova, Head of HR and Workforce at Baku City Circuit, that complexity made HR transformation a necessity rather than an option.
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Each season began with a simple but critical question: how could workforce systems perform better under pressure? The answer increasingly pointed to digital platforms, data, and a measured approach to artificial intelligence, but not without caution.
Building a digital workforce engine
For an operation dependent on thousands of marshals, volunteers, and temporary workers, manual processes were no longer sustainable. Instead, Ahmedova described how they used a cloud-based platform that supported the full workforce lifecycle, from candidate pre-screening through to rostering and scheduling.
“The goal is to build a program that acts as our supporter while remaining user-friendly for all engaged groups,” she said.
Usability remained central. The workforce was highly diverse and often international, with strict deadlines for mandatory training. Digital tools helped remove geographic barriers, enabling broader participation and more consistent preparation ahead of the event.
This extended into a mobile application introduced during the most recent season. The app connected directly to the platform, allowing users to receive updates on interview status, training invitations, and operational shifts in real time.
“It is important that this application is user-friendly and accessible,” she said.
The system also needed to balance scale with flexibility. It had to securely manage large volumes of workforce data while adapting quickly to the unpredictable nature of live event operations. Ahmedova said that balance was essential to improving both speed and quality across the organization.
Automation with a human override
AI had begun to reshape specific parts of the HR process, particularly in candidate pre-screening. Candidates responded to structured questions, and algorithms helped identify suitable profiles, reducing manual workload and accelerating early-stage decisions.
However, Ahmedova drew clear boundaries around its use.
“Relying entirely on AI is not effective, as it may miss nuances such as answer integrity or subtle inconsistencies that humans can detect,” she said.
Instead, the organization adopted a blended model. AI supported efficiency in the early stages, while human recruiters remained responsible for interviews and final assessments.
“We use a blended approach – AI supports certain stages, while humans handle the rest,” she said.
That balance was not only about maintaining quality, but also about managing risk. Ahmedova pointed to concerns such as data leakage and the potential for reduced productivity if AI tools were poorly implemented.
“The extent to which we rely on AI must be carefully analyzed,” she said.
She also referenced broader industry concerns around automation replacing entry-level roles, which could have longer-term implications for talent pipelines. Maintaining a realistic view of AI’s capabilities, she said, was critical to avoiding unintended consequences.
Managing change and workforce readiness
Introducing AI-driven processes created both operational and cultural challenges. Employee resistance, often driven by uncertainty, had the potential to impact productivity and performance.
“Adapting to these changes requires time,” Ahmedova said.
HR played a central role in managing that transition. This included assessing workforce readiness, identifying skill gaps, and aligning implementation with employees’ capabilities.
“We must assess what skills are needed and how to support employees who lack them,” she said.
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Ahmedova also cautioned against a common misstep: assuming that purchasing technology alone would solve operational challenges.
"Many AI initiatives fail due to unrealistic expectations,” she said.
Vendor selection and implementation expertise were equally critical. Organizations that prioritized cost over capability risked creating more complex problems during rollout.
"Lower cost does not guarantee successful implementation,” she said.
Clear communication emerged as a key factor in overcoming resistance. When employees understood the purpose behind AI adoption, they were more likely to engage with new systems and processes.
Keeping HR human
Despite the increasing role of technology, Ahmedova emphasized that core elements of HR remained inherently human.
“Empathy and compassion cannot be replicated by technology,” she said.
In areas such as employee well-being and personal support, human interaction continued to play a critical role. Employees facing personal or emotional challenges expected direct engagement, not automated responses. Ahmedova said that while some roles may evolve with the rise of AI, the human-centered aspects of HR would remain essential.
The organization's approach came down to balance. Technology was used to eliminate repetitive tasks and improve efficiency, but not at the expense of human judgment or connection.
“When both elements work in harmony, it leads to better outcomes,” she said.
