How to Use AI for Internal Talent Mobility and Career Pathing

In today’s competitive, oversaturated job market, talent is challenging to find — and keep. Many people understand they have more to gain from job hopping than staying in their current roles and hoping for a promotion.

A strategic career pathing program based on internal talent mobility data is no longer optional, but indispensable. Human resources (HR) professionals must help employees visualize their individual career trajectories within the organization to retain top talent. Emerging research and statistics suggest that the best way to do this may be through the use of artificial intelligence.

Understanding AI’s Role in Talent Mobility

Finding the perfect role, project or department for someone within the same organization can be challenging, especially if their transferable skills are not easily identifiable. AI simplifies this process by analyzing vast amounts of talent and career information.

AI can analyze performance reviews, resumes, job reports, project outcomes and behavioral data to inform career pathing. It can automate the traditional process while improving the size and quality of talent mobility datasets. HR can use natural language to interact with it, eliminating the friction typically associated with learning a new digital tool.

Many companies have already implemented AI internally — approximately 80% of HR departments already utilize it in recruitment — so professionals should be able to easily tap into hiring data. For those who have grown accustomed to its presence and built context-rich datasets, integration will be seamless.

How to Use AI for Internal Career Pathing

There are several ways the department can leverage AI to improve internal talent mobility by creating more opportunities for employees. For one, it can evaluate the subtle trends associated with career progression and match employees to positions, thereby developing an internal talent marketplace.

For example, this technology could track absenteeism, contract length or microexpressions. It could even search the internet, scouring job boards, professional networking platforms and freelance websites to evaluate the likelihood of employee retention. It can go beyond information gathering and analyze actionable data to inform decision-making.

Professionals can use AI-powered predictive analytics to forecast future job fit and performance. For instance, they can assess the likelihood of satisfaction in a new role. Alternatively, they can predict how skill sets will evolve in tandem with the job market.

Once HR understands where individuals’ skills need work, they can initiate algorithm-driven training. According to the 2024 BDO Audit Innovation Survey, 61% of leaders in finance reported turning to AI for upskilling and reskilling purposes. These personalized career paths can help facilitate internal transitions more quickly and smoothly.

HR can even use these insights during hiring. Say a promising candidate doesn’t make the final cut. Instead of losing this individual to the competition, the department can identify similar roles within the organization where they’d be a great fit.

Benefits of Using AI to Identify Skills Gaps

According to MIT Sloan, helping employees identify skills gaps during a digital transformation provides clear business benefits. However, progression looks different for everyone. While many seek the higher pay and additional responsibilities that come with traditional promotions, some prefer lateral moves. They may even be willing to take a step back.

As the name suggests, traffic on the traditional career ladder moves one way — upward. In the real world, however, progression can be vertical, horizontal or diagonal. Mapping all these trajectories on an individual level can be complex, especially within large enterprises, chain stores or multinational companies.

Since linear progression is not always possible, organizations are often bottom-heavy. Top talent migrates when people outgrow their roles, leaving large vacancies that novices fill. HR can mitigate this issue by leveraging AI to inform talent mobility and optimize job satisfaction.

Utilizing AI is beneficial because it can process information much faster than humans or existing software. Regardless of how large an organization is, it can personalize career pathing. For instance, it can factor in the maximum commute length people will accept, preventing HR from offering the role to a top candidate who is too far away and isn’t willing to relocate.

AI could improve engagement, increase job satisfaction and enhance retention. It could even strengthen diversity, equity and inclusion efforts by fairly evaluating all criteria, thereby facilitating merit-based hiring. These improvements could streamline administrative processes and boost productivity, decreasing recruitment and labor costs.

The Importance of Ethical Implementation

Given that AI is so beneficial, it’s unsurprising that so many organizations are implementing it. McKinsey & Co. research reveals that 92% plan to increase AI investments by 2028. However, as of 2025, just 1% believe they have reached maturity. This technology is new, so best practices and integration mistakes are only just emerging.

To secure employee buy-in and ensure AI-powered talent mobility initiatives are effective, the HR department must ensure implementation has an ethical and fair framework. Algorithms generate insights based on datasets, so flawed information can inadvertently perpetuate biases. Balancing AI with human touch is essential for mitigation.

Data privacy and security are also major concerns. Employees may be reluctant to be monitored at the level required for in-depth insights, as it may feel risky or intrusive. Professionals should be mindful that AI complements — not replaces — human interactions. In-person interviews and feedback surveys can help reduce friction.

Still, some people may be averse to using this technology. According to a 2024 YouGov survey on the public’s attitudes toward AI, while 37% of people actively use it, 34% abstain from use and 29% are “AI ignorant.”

People may fundamentally disagree with it due to its environmental impact and history of intellectual property theft. Models should be trained in-house with original content only when workers opt in. Companies should also consider offsetting estimated data center emissions with sustainability efforts.

Enhancing Internal Talent Mobility With AI

Forward-thinking organizations can practice strategic talent sourcing and workforce planning by leveraging AI-powered solutions. A single algorithm can inform hiring, exits and referral programs for a more comprehensive approach to career pathing. It moves beyond individual progression by hyperpersonalizing efforts, making it a valuable tool for HR departments to have.

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Devin Partida is the Editor-in-Chief of ReHack.com, and is especially interested in writing about human resources and BizTech. Devin's work has been featured on Entrepreneur, Forbes and Nasdaq.