AI is no longer just the subject of hype — it’s a requirement for career growth. A recent survey from Nexford University found that nearly one-third (29%) of hiring managers only hire employees who are proficient in AI or have AI-related skills.

This signifies a notable turning point in hiring and workforce mobility: an employee’s long-term career success now depends on their knowledge of, and confidence using, AI.

Employees and employers alike need to take this shift seriously and focus on AI upskilling. The same survey found that over three in five laid-off employees (62%) believe that improving their AI and digital skills will increase their long-term job security, and 62% also said that they would be more likely to take a job with a company that supports AI upskilling.

AI skills are no longer a “nice-to-have,” but a pre-requisite for career longevity. Organizations that invest now in a strong, replicable AI upskilling infrastructure will benefit from the most innovative workforces and see the greatest returns on their AI investments.

Why AI skills are now a necessity

The rise of AI is dramatically reshaping how we work. AI now touches every area of an organization — from external applications like personalized marketing outreach to the automation of internal operations. Just as companies that embraced digital transformation first surged ahead, the organizations that become proficient in AI first will pull ahead of their peers. With the pace of AI innovation, that gap is only going to widen.

Workera’s recent 2025 State of Skills Intelligence Report underscores how quickly the divide is forming. Half of enterprises already have a fully defined and approved AI-related business objective for 2025, and another 46% are in development. Among these, the ones with a mature AI strategy are significantly more likely to feel their training programs close skill gaps effectively (47% vs. 16%) and to be confident in their workforce’s AI readiness.

Organizations with defined AI business objectives are training 43.8% of new hires in AI skills within the first 90 days, compared to just 34.2% at companies without such objectives. They’re also more confident in supporting talent mobility and retention (53% vs. 17%). Having a clear AI goal doesn’t just future-proof an enterprise — it shapes how quickly employees build transferable AI skills and how well organizations can retain talent.

AI is not simply a productivity tool. It helps organizations acquire and deepen skills faster. If an employee knows how to work with AI tools and systems, then they’ll have better access to learning and development opportunities — both self-guided and organizationally driven — and will be better equipped to adapt to new role requirements.

Three steps to AI upskilling

The good news? It’s not too late to start. AI gives employees and organizations the ability to catch up faster than with traditional skill-building methods. Here’s how to begin:

Step 1: Identify gaps

With AI, no one is truly starting from zero. Most employees already interact with AI in small ways — whether through search, recommendation engines, or simple automation tools. The first step is to understand the baseline levels of your organization and its employees. Skills assessments provide a clear view of what employees know, what they don’t, and where to focus next. With that foundation, organizations can align employees’ growth with strategic priorities.

Step 2: Work on the skills that matter

Every company will have its own needs, and not every AI skill is equally valuable in every context. Employees should focus on the capabilities that drive the most impact for their organization — whether that’s applying AI to the customer experience, automating back-office operations, or fine-tuning models for business-specific data. 

Leadership plays a crucial role in this step. By clearly articulating priorities and training AI tools on company-specific information, leaders ensure skill development is both relevant and transferable. AI proficiency becomes a durable, horizontal skill — useful across roles, industries, and career paths.

Step 3: Embrace AI mentorship

Even if an organization or individual employee feels behind, AI itself offers a way to catch up. With tools like Sage, employees gain access to a personalized mentor — one that generates tailored learning pathways, suggests the right resources, and adapts to each individual’s pace. Sage doesn’t just test for skills; it guides employees toward the next step in their development. The combination of assessment and mentorship accelerates growth in ways traditional training never could.

Learn in the style that works for you

Upskilling isn’t one-size-fits-all. Some employees learn best through structured reading, while others prefer hands-on practice or conversation. Workera’s new Talk capability expands on Sage’s assessments by enabling multimodal learning — from interactive simulations to live conversations with AI. Talk adapts to each learner’s style, so every employee builds confidence in a way that feels natural and sustainable.

This adaptability is what makes AI-powered upskilling different. Instead of forcing people into rigid programs, the system adapts to the learner, ensuring higher engagement and faster mastery.

The urgency of AI upskilling

The race to develop employee skills has never been more intense. Hiring managers already see AI fluency as a baseline requirement, and companies that don’t provide meaningful pathways for employees to build these skills risk losing talent — or worse, falling behind in innovation.

With AI agents like Sage, organizations can compose individual, role-specific skills frameworks and support them with multimodal learning. The result is a workforce that’s not just current, but future-ready.

Interested in learning more? Schedule a demo with our team.