Dr. Jeff Bergin
Chief Learning Officer, General Assembly
As AI adoption accelerates, AI skills gaps are widening. Closing them demands more than awareness — it requires action at scale.
AI has moved from experimentation to expectation seemingly overnight. Tools that not long ago felt optional are now embedded into everyday workflows, reshaping how decisions are made, work is delivered and value is created. Yet while technology adoption has surged, workforce readiness hasn’t kept pace.
Many organisations have invested heavily in AI platforms, pilots and proofs of concept. Few, however, are seeing sustained impact. According to PwC, 95% of AI pilots show no measurable ROI when evaluated beyond the pilot phase.
Organisations need to build workforce capability alongside technology deployment. Skills decay quickly when learning is disconnected from real roles, outputs and accountability. And that’s becoming one of the most pressing risks facing businesses today.
Skills are the constraint
The future of work isn’t facing a shortage of AI tools. It’s facing a shortage of people who know how — and when — to use them effectively. As roles evolve, workers are being asked to collaborate with AI systems, interpret outputs, manage risk and apply judgment in new ways.
Generic “AI 101” programmes don’t meet this challenge. They overwhelm beginners, disengage advanced users and leave leaders without the clarity needed to guide adoption responsibly.
Meanwhile, isolated experimentation rarely translates into scaled capability, creating pockets of progress without meaningful workforce transformation. The result: enthusiasm at the top, confusion in the middle and anxiety on the ground. Employees worry about relevance and job security, while leaders lack visibility into who’s ready for what.
Inclusion isn’t optional
If access to AI skills is limited to small groups of specialists, the gap widens further. Inclusive upskilling isn’t just a social imperative — it’s a business survival tool. Organisations that build broad-based capability reduce reliance on shadow AI, retain talent and unlock innovation across functions.
This means AI upskilling requires meeting people where they are, recognising different starting points, learning styles and confidence levels. It also means designing pathways that allow individuals to progress from foundational literacy to applied capability over time, rather than forcing everyone through the same experience.
When learning is relevant, supported and embedded into daily work, adoption accelerates and confidence grows. Everyone wins.
The result: enthusiasm at the top, confusion in the middle and anxiety on the ground.
From learning to leverage
Organisations treating AI as a capability to be managed rather than software to be deployed are seeing real results. They start by assessing readiness, aligning leadership on risk and intent and segmenting learning by role and maturity.
They focus on role-based application — how AI improves performance in HR, finance, marketing, operations and leadership — rather than abstract theory. They reinforce learning through practice, ownership and communities of champions who drive adoption locally.
This shift from check-the-box training to continuous capability building is where momentum is sustained. It’s also where measurable impact begins to emerge.
At General Assembly, this approach underpins how organisations are supported as long-term capability partners. Our AI Academy focuses on practical application and behaviour change, not participation metrics, and on translating AI investment into productivity, efficiency and resilience.
AI is powerful, but it’s not autonomous from human judgment, ethics or context. The organisations that will survive and thrive in the AI era are those that invest equally in human capability.
Preparing the next generation of talent requires collaboration across education, industry and government. It also requires urgency because AI skills development is no longer optional, and catching up is far more costly than building readiness now. AI isn’t simply another technology shift. It’s a workforce transformation. And the current wave of change isn’t the last one. Organisations building capability systems for continuous evolution will win the future of work. Those focused on a one-time adjustment are already falling behind what comes next.
For more information, visit https://generalassemb.ly/employers/what-we-teach/ai?utm_medium=mediaplanet&utm_source=content&utm_campaign=2026_Q1_enterprise_ai_academy_wraparound&utm_content=marketing
