AI & Workforce Readiness: Nicole Helmer on Skills-First Learning with Degreed

1. At a time when AI is reshaping jobs, how do you help organizations move beyond “training programs” to prepare future-ready workforces?

Traditional training programs are built around fixed courses, but today’s work is anything but fixed. AI is accelerating that change, continuously reshaping roles, skills, and performance expectations. What organizations do not need is more courses; they need a system to activate capabilities that connects learning directly to the moments of need.

Sometimes the right answer is real-time guidance to solve an immediate challenge. Other times, the best learning happens when people deliberately step back. When the stakes are lower, they can shift mindsets, reflect, and build deeper skills for the future. Both approaches matter. The key is creating a rhythm of learning that balances immediate enablement with intentional future development.

Leaders should be asking “how do we accelerate time-to-proficiency, mobilize skills across the enterprise, and build the adaptability to meet what’s next?”. Organizations that get this right will be able to use AI as a catalyst for more workforce agility and long-term competitiveness.

2. What unique perspectives do you expect advisors to contribute in guiding enterprise clients through AI-enabled transformation?

Advisors bring a critical outside-in perspective. While organizations are often consumed by immediate operational pressures, advisors connect the dots between workforce data, industry trends, and the broader AI skills landscape. That view helps leaders see not just which roles may be automated, but also what new forms of value creation are possible when AI augments human capability.

The best advisors will act as both translators and challengers – translating technical disruption into workforce strategies, and challenging leaders to think bigger about talent mobility and growth. They help organizations balance speed with trust, ensuring adoption of AI in ways that are ethical, inclusive, and aligned with culture rather than just technologically possible.

3. Where do you see the next wave of innovation in learning platforms? What will separate those that thrive from those that stall?

The next wave will be driven by hyper-personalization and adaptability. Platforms that thrive will move beyond simply offering content libraries to becoming true learning companions: leveraging AI to provide real-time coaching, adaptive pathways, and dynamic recommendations based on evolving skills data.

At Degreed we are using AI to design and deliver learning that’s dynamic, role-specific, and built to evolve alongside your organization. That’s why we built Degreed Maestro. Unlike generic AI assistants, Maestro delivers learning experiences built around the learner’s current skill level, their goals, and the needs of the business. It can offer coaching, help you rehearse a presentation, or recommend your next development move. It remembers where you’ve been and suggests what’s next. Maestro is truly adaptive, which means it doesn’t just make you more efficient, it makes you more capable. That distinction matters.

Those that stall will continue treating learning as content consumption and will be distracted chasing smaller snippets of content and flow-of-work shortcuts when they should be combining the right mix of modalities, interactivity, and context for deeper growth. The real differentiator will be platforms that connect individual growth with organizational outcomes: showing how learning accelerates business performance while giving employees visibility into career mobility. In short, the winners will integrate skills, AI, and outcomes into one seamless experience.

4. From your vantage point, what’s the most common misconception leaders have about workforce readiness in the age of AI?

The biggest misconception is that readiness is about having the right tools. Leaders often assume that by investing in AI-enabled systems, their workforce will automatically be prepared. But technology alone doesn’t equal readiness. Readiness is about mindset and adaptability — the ability of people to continuously learn, reapply skills in new contexts, and embrace evolving roles. Many leaders also underestimate the pace of change: the “future of work” isn’t five years away, it’s happening now, and readiness must be built as a continuous muscle, not a one-time initiative.

5. Beyond the technology, what role does culture play in helping companies embrace large-scale upskilling and reskilling?

Culture is the real differentiator. Technology can enable upskilling, but culture determines whether people will actually embrace it. A culture that encourages experimentation, rewards learning agility, and views career mobility as a strength is far more likely to succeed in workforce transformation. Without this foundation, even the best AI tools will fall flat.

Employees must feel safe to learn and to grow without fear of failure. When organizations are thoughtful about how learning and change management intertwine, reskilling shifts from a mandate into an opportunity. That’s how continuous learning becomes embedded in culture and how companies ultimately drive adaptability at scale.

6. If you had one message for CEOs grappling with workforce transformation, what would it be?

Your workforce strategy is your business strategy. Every business model, every competitive advantage, every innovation ultimately depends on people and skills. My message to CEOs is simple: invest in your people with the same urgency and intentionality that you invest in technology. AI will keep reshaping the playing field, but it’s your workforce that will determine whether you win on it.