The impact of artificial intelligence on our careers is becoming more apparent, even if we are not fully aware of it. Various factors, such as advancements in human capital management systems, the adoption of data-driven practices in human resource and talent management, and a growing focus on addressing bias, are reshaping the way individuals are recruited, trained, promoted, and terminated.
The current market for artificial intelligence and related systems is already substantial, generating a revenue of over US$38 billion in 2021. Undoubtedly, AI-powered software holds significant potential to rapidly progress and revolutionize how organizations approach strategic decision-making concerning their workforce.
Consider a scenario where you apply for a job in the near future. As you submit your well-crafted résumé through the company's website, you can't help but notice the striking resemblance between the platform and others you've used in the past for job applications. After saving your résumé, you are then required to provide demographic information and fill in numerous fields with the same data from your résumé. Finally, you hit the "submit" button, hoping for a follow-up email from a human.
At this point, your data becomes part of the company's human capital management system. Nowadays, only a handful of companies actually examine résumés; instead, they focus on the information you enter into those small boxes to compare you with dozens or even hundreds of other candidates against the job requirements. Even if your résumé clearly demonstrates that you are the most qualified applicant, it's unlikely to catch the attention of the recruiter since their focus lies elsewhere.
Let's say you receive a call, ace the interview, and secure the job. Your information now enters a new stage within the company's database or HCM: active employee. Your performance ratings and other employment-related data will now be linked to your profile, providing more information for the HCM and human resources to monitor and evaluate.
Advancements in AI, technology, and HCMs enable HR to delve deeper into employee data. The insights gained help identify talented employees who could assume key leadership positions when others leave and guide decisions regarding promotions. This data can also reveal favoritism and bias in hiring and promotion processes.
As you continue in your role, your performance is continuously tracked and analyzed. This includes factors such as your performance ratings, feedback from your supervisor, and your participation in professional development activities. Accumulating a substantial amount of data about you and others over time allows HR to consider how employees can better contribute to the organization's growth.
For instance, HR may employ data to determine the likelihood of specific employees leaving and assess the impact of such losses.
Popular platforms used on a daily basis already aggregate productivity data from sign-in to sign-off. Common Microsoft tools like Teams, Outlook, and SharePoint offer managers insights through workplace analytics. The Microsoft productivity score monitors overall platform usage.
Even the metrics and behaviors that define "good" or "bad" performance may undergo changes, relying less on subjective manager assessments. With the expansion of data, even professionals such as consultants, doctors, and marketers will be evaluated quantitatively and objectively. An investigation conducted by The New York Times in 2022 revealed that these systems, intended to enhance productivity and accountability, had the unintended consequence of damaging morale and instilling fear.
It is evident that American employees need to contemplate how their data is utilized, the narrative it portrays, and how it may shape their futures.
Not all companies have a Human Capital Management (HCM) system or possess advanced capabilities in utilizing talent data for decision-making. However, there is a growing number of companies that are becoming more knowledgeable in this area, and some have reached a remarkable level of advancement.
While some researchers argue that AI could enhance fairness by eliminating implicit biases in hiring and promotions, many others see a potential danger in human-built AI merely repackaging existing issues. Amazon learned this lesson the hard way in 2018 when it had to abandon an AI system for sorting résumés, as it exhibited a bias in favor of male candidates for programming roles.
Furthermore, the increased collection and analysis of data can leave employees uncertain about their standing within the organization, while the organization itself may possess a clear view. It is crucial to comprehend how AI is reshaping the workplace and to demand transparency from your employer. These are some key points that employees should consider inquiring about during their next performance review:
- Do you perceive me as a high-potential employee?
- How does my performance compare to that of others?
- Do you see me as a potential successor to your role or the roles of others?
Similar to the need to master traditional aspects of workplace culture, politics, and relationships, it is essential to learn how to navigate these platforms, understand the evaluation criteria being used, and take ownership of your career in a new, more data-driven manner.
