New Pearson and AWS Research: Only 14% of UK Learners Consider Themselves Highly AI-Ready
New UK report points to practical application of AI and critical human skills as the bridge between higher education and AI-enabled work
Pearson and Amazon Web Services (AWS) today released new UK research revealing the disconnect between AI knowledge and real-world application of those skills as a key challenge in preparing graduates for an AI-enabled future.
What does the data tell us?
- Only 14% of UK learners consider themselves highly AI-ready (combining AI knowledge with critical human skills).
- 43% of UK employers cite the disconnect between knowledge and real-world application of AI as a key difficulty when hiring graduates.
- 47% of UK learners say the best preparation for an AI-enabled career is a combination of university education and practical work experience.
The findings reveal a clear execution gap: learners, higher education leaders, and employers recognise the continued importance of university education, but graduates need more opportunities to apply AI in ways that reflect real workplace expectations. This not only means more workplace experience such as apprenticeships, but also using AI tools that are directly integrated into courseware so students can use it ‘in the flow’ of work.
Skills that employers are looking for include the ability to apply human judgement to AI capabilities, communication and collaboration skills, and adaptability.
Sharon Hague, UK CEO, Pearson said:
“AI is changing the expectations graduates face as they move from education into the world of work. The UK benefits from world-class institutions and strong graduate adaptability, but without the right skills this potential will not translate into the workplace. High youth unemployment and an impetus among businesses to drive enterprise value highlights the need help students build, practice, and prove AI-ready capability that prepares them for work.”
Valerie Singer, General Manager of Global Education, AWS said:
“Students are using AI, but usage alone isn’t what employers are looking for. They want evidence that graduates can apply AI to solve real problems. The gap isn’t access, it’s the distance between exposure and proof. Programmes like the AWS Skills to Jobs Tech Alliance give students hands-on experience so they leave with skills they can show, not just tools they’ve tried. That’s how we make sure what students learn actually prepares them for the workforce.”
What is the solution?
To support action, the report introduces the AI Readiness Friction Framework, identifying where progress is slow across the learning-to-work continuum. Recommended actions include:
- Pace: Accelerate the cadence of curriculum and institutional decision-making through modular design, stackable credentials, and faster review cycles.
- Connection: Build ongoing feedback loops with employers and industry bodies.
- Capability: Invest in faculty and instructor AI capability as core system infrastructure.
- Governance: Replace ungoverned access with clear, practical guidance that embeds AI use into everyday learning and assessment.
- Experience: Move beyond access to tools by embedding structured opportunities to practice and apply AI capabilities in authentic workplace contexts.
- Skills: Prioritise the development of compound capabilities such as strategic intelligence, ethical stewardship, and critical human skills.
Responses