On the Frontlines: AI in Talent Management

This plan places the Federal government on the bleeding edge of technological innovation.

You read that right. The Federal government, commonly thought of as being slow and very resistant to change, is now creating a new paradigm in the areas of employee development and workforce planning.

So, what is the State Department doing and how does it create a new paradigm?

By using GenAI, the State Department can compare the skills its employees currently possess with the skills needed to fill current job openings. This information is then used to identify individual employees who can potentially fill these roles and present them with not just the skills they would need to acquire to fill these roles but also identify to these employees how to acquire the requisite skills.

The way it currently works in many large firms, including at Deloitte where I am a consultant, is that employees are matched to roles and projects based on the skills they currently possess. This system places the burden of identifying both the skills and learning resources needed to move into a new role entirely on employees. The employer is still involved, but only in a passive role of providing learning resources to its employees.

In this new paradigm, the employer takes on a much more active role in terms of both making employees aware of potential career paths within the organization and providing employees with guidance on how to develop the skills necessary to pursue their desired career path.

This new concept in talent management offers numerous benefits to large organizations across different industries and sectors.

First, it gives organizations that embrace it an edge in the war for talent. Despite layoffs and a possible recession, it is still difficult for organizations to attract employees who have the necessary skills, especially in more technical areas. By identifying employees with related skills and resources for closing the skills gap, organizations can upskill and realign their current workforce more quickly and cost-effectively, thus enabling the organization to gain or retain a competitive edge by placing the right people in the right roles at the right time.

Additionally, it provides leaders with a way to make their workplaces both more inclusive and more meritocratic. By using an employee’s ID number as the only identifying information, the algorithm can anonymously process information related to skills, without the biases around race, gender, etc. that human reviewers possess. This means the process for identifying and selecting employees for advancement, be it through promotion, filling a newly created role, or something else, is now done in a way that is significantly more meritocratic and more reliant on an employee’s skills — and less reliant on an employee’s relationships and networks within the organization. In addition to promoting competency within the workforce, this helps make the workforce more inclusive by identifying diverse candidates with the right skills. It opens career paths to individuals who may have limited networks within the organization or may not feel comfortable asking about career advancement opportunities but who otherwise possess the fundamental skills.

So, what can leaders do to embrace this new paradigm?

CAEs can take the lead with AI by creating a culture where failure is embraced, not feared. It is too often the case that large organizations, including internal audit departments, have a culture that rejects risk-taking and failure and prefers instead to stick with the tried and true. Instead of being feared, failure should be embraced as a learning opportunity. Your organization will inevitably have AI projects that fail. The question is, will you lean into that failure and learn from it so you can succeed in future AI projects, ones that help the organization reap the benefits that come from implementing AI at scale? Or will you choose to just move on from the failure and eventually be left behind?

As part of changing the culture, CAEs must engage stakeholders and create safeguards to manage risk. As part of a culture of embracing failure, CAEs must also work with stakeholders and align on expectations. Although the risks involved with the technical aspects of AI and the legal aspects of labor relations are beyond the scope of this blog post, they are important considerations. Engaging with stakeholders in these areas can help CAEs identify and create safeguards against any risk that this new paradigm poses to the organization.

By following these steps, leaders can adopt this new workforce planning paradigm and reap its benefits, while mitigating the risks associated with embracing new technologies and processes.