Hiring One AI Expert Won’t Fix Your AI Strategy

Everyone is talking about being locked in a brutal AI hiring war. Headlines reinforce the idea that success depends on winning a narrow race for elite machine learning engineers or data scientists. In reality, many organizations are solving the wrong problem. The real issue isn’t a lack of access to external AI talent; it’s a lack of visibility into the skills they already have.

This misconception is quietly derailing enterprise AI strategies. Leaders assume that hiring a handful of “AI experts” will unlock transformation. But without a wider workforce that understands how to apply, integrate, and scale AI across functions, even the most talented hires struggle to create meaningful impact.

The myth of the AI “silver bullet”

There’s a persistent belief that one or two high-profile AI hires can catalyze change across an organization. But AI transformation (or any transformation, for that matter) doesn’t work that way. It’s not a standalone function. It’s a capability that must be embedded across teams, workflows, and decision-making processes.

Instead, AI success depends on skills readiness and cross-functional integration. When organizations isolate AI expertise within a small team, they create bottlenecks instead of momentum. Those experts become over-relied upon, disconnected from business context, and ultimately limited in their ability to scale impact.

Meanwhile, the rest of the workforce remains underprepared, unsure how to engage with AI tools, or how to apply AI to everyday work.

The issue with poor skills visibility

At the heart of this issue, there is a lack of clear insight into existing workforce capabilities. Many companies simply don’t know what AI-adjacent skills already exist internally among their current workforces.

Employees across functions (whether in operations, marketing, finance, or IT) often possess foundational capabilities that can be extended into AI applications with targeted upskilling. These might include data analysis, workflow automation experience, or business operations. But without structured skills intelligence, these AI-adjacent capabilities go unnoticed.

As a result, organizations default to expensive external hiring or contractors, even when internal employees could be equipped to deliver similar outcomes with the right support. This reactive approach is inefficient, costly, and unsustainable, particularly in a tight economic climate.

Hiring isn’t always the answer

Recent research found that 72% of employers are struggling to fill roles, with AI skills now ranked as the hardest capability to hire globally for the first time.

Plus, pouring resources into recruiting and onboarding new talent doesn’t always make sense. External hiring comes with higher costs, longer ramp-up times (as they learn about the business), and no guarantee of long-term retention. More importantly, it doesn’t solve the systemic issue of workforce readiness.

Organizations that rely too heavily on hiring miss a critical opportunity: the chance to unlock and scale the potential that already exists within their workforce. Sometimes, in order to find talent, you just have to shift your mindset to seeing it.

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The case for building from within

Leading organizations are already moving in a different direction: they are investing in their people, equipping employees with the skills needed to build custom tools, experiment with new technologies, and solve problems that didn’t previously exist.

This approach is foundational to long-term success. Developing internal talent addresses immediate skill gaps and creates a more resilient and adaptable workforce. Employees are already familiar with the organization’s systems, culture, and goals, which makes them uniquely positioned to apply AI in meaningful, context-driven ways.

However, building internal capability requires more than offering generic training programs. It demands a structured, strategic approach.

Organizations need to move beyond one-off courses and instead embed skills intelligence and management into the fabric of the business. This includes aligning upskilling initiatives with strategic priorities, tracking skill development through clear metrics, and creating a culture where curiosity and growth are actively encouraged.  Furthermore, this skills-based model transcends learning and development, and must be embedded across the entire employee experience, from talent acquisition and onboarding to performance and growth.  This enables the business to create a self-sustaining pipeline of talent that adapts to the needs of the market.

With the rapid pace of technological acceleration, the skills required for success are evolving in just months, not years. Businesses must continuously assess workforce capabilities, identify gaps, and invest in targeted development to stay ahead.

Borrowing strategically to accelerate learning

While building internal talent is essential, there are moments when organizations need specialized expertise quickly. Not as a replacement for internal development, but as a complement to it.

Bringing in external consultants or partners can provide short-term support and introduce new perspectives. But the real value lies in knowledge and skills transfer. Organizations must ensure that insights from external experts are captured, shared, and embedded within internal teams for continued implementation after they depart.

This requires intentional collaboration. Internal teams need to be open to learning, capable of integrating new knowledge, and supported by processes that allow that knowledge to scale across the business.

When done effectively, borrowing expertise becomes a catalyst for innovation rather than a temporary fix.

Holistic skills-based strategy

Ultimately, the path forward isn’t about choosing between hiring and upskilling. It’s about shifting to a skills-based strategy overall that’s grounded in visibility and intentionality.

The starting point is understanding what skills exist today and what will be needed tomorrow. A skills gap analysis provides this foundation, enabling organizations to make informed decisions about where to invest in development and where external support is truly necessary.

From there, businesses can operationalize cross-functional upskilling by:

• Mapping skills across teams and identifying hidden capabilities
• Aligning learning programs with real business challenges
• Encouraging collaboration between technical and non-technical roles
• Embedding continuous development into performance and talent processes

This approach transforms AI from a niche capability into an organizational strength.

Stop searching outside and start scaling within

The narrative of an AI talent shortage isn’t entirely wrong, but it is incomplete. The real constraint isn’t access to talent. It’s the ability to see, develop, and deploy the skills already inside the organization.

Companies that move fastest in AI won’t be the ones that hire the most experts. They’ll be the ones that can activate their workforce at scale, turning existing capability into real execution. Because AI transformation doesn’t happen through a few hires. It happens when the entire organization is ready to apply it.

About Skillsoft

Skillsoft (NYSE: SKIL) is a global leader in AI-native skills management for the human + AI era. By unifying learning, real-time skills intelligence, and workforce insights, Skillsoft helps enterprises build their Skillforce — humans and AI working together to drive measurable business outcomes. Through personalized, interactive learning across leadership, technology, and compliance, Skillsoft enables organizations to close critical skill gaps and accelerate transformation. Skillsoft is trusted by thousands of organizations worldwide and supports a global community of more than 105 million learners.

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