Technology is home to endless avenues of career opportunity, making it one of the most dynamic and rapidly evolving sectors in the world. The UK technology sector boasted a market valuation of $1.1 trillion in 2024 and Manchester was named the UK’s most AI-ready city in the same year. It’s clear that this momentum shows no sign of slowing down and that the UK’s innovation landscape will only continue to evolve and grow.
But it is limiting to view technology simply as a ‘sector’. Rather, it is an enabler, a powerful vehicle that can unlock a wide array of other opportunities, a catalyst for connecting different industries and creating new roles within every field.
In this context, technology becomes a framework through which we can consider our approach to skills development. It is sector agnostic, the bridge rather than the barrier, and its potential applications reach far and wide across the boundaries of traditional sectors.
Now, to harness its full potential, drive real innovation and shape the future of work in ways we have yet to imagine, we need to shift our mindset. There isn’t a sector that technology won’t impact in the future and to embrace its full potential, rethinking our approach to AI skills development will be critical.
Bringing AI into the equation
The rise of AI has introduced a range of powerful tools that are reshaping how many businesses deliver their core products and services. When it comes to technology, encouraging people to recognise, trust and maximise their existing knowledge within their respective industries is the key to furthering innovation.
By trusting our expertise and proactively considering how AI can be applied to our own job roles, we can improve processes, increase efficiencies, and achieve operational success, as well as learn to enhance the speed, quality or value of our work.
It’s about using AI to build upon existing strengths to access new opportunities that can positively benefit businesses, rather than using AI for AI’s sake.
Enabling a collective mindset shift
To change the perception of the value and application of AI skills, we need to revisit how we learn. Historically, our focus has been influenced by the pedagogical principles of our education system, which has, for some time, been focused on testing knowledge acquisition rather than applied learning. Instead of asking young people about the exams they’re taking or the job they hope to have, we should be asking them about their aspirations, what problems they see in the world, and how they’d like to solve them.
This shift in perspective will require us to view education as a journey of growth and curiosity – one in which learning is not confined to a classroom or doing our required annual CPD modules but integrated into our everyday lives.
Instead of encouraging people to sign up for courses, we need to drive experimentation with new tools in the delivery of our everyday work. We’ll need to accept the speed at which technology evolves, but at the same time concede that skills development can be a slow process. We’ll need to work hard to let go of these attitudes and embrace the discomfort of ‘getting it wrong,’ the fear of looking foolish or dips in productivity.
This is a systemic challenge that we need to overcome to develop the AI skills that the workforce of the future will need. Only then will we create a culture of continuous learning, driven by passion and aimed at solving real-world problems.
Expanding the concept of AI skills
The government’s new AI Opportunities Action Plan marks a crucial first step towards this vision by emphasising the need to address the skills deficit. The plan not only acknowledges this gap but also recognises the uncertainty surrounding the full extent of the deficit and pledges to provide a range of opportunities for reskilling, rather than just one entry point, and ‘destination focussed’ training.
Section 1.3 of the Action Plan emphasises the importance of training, attracting and retaining the next generation of talent in AI ecosystems. It highlights the need for developing long-term talent pipelines, expanding educational pathways into AI, and fostering a more diverse talent pool to address the skills deficit.
While this is encouraging to see, it only begins to scratch the surface, focusing primarily on AI as a sector, rather than recognising its potential as a cross-sector tool. To reach a full narrative shift, we must go further. 80% of the 2030 workforce is here and already in employment; simply addressing the skills gap at the front end isn’t sufficient.
Going forward, AI and technology will be integral to all industries, and we need to be empowering professionals in any field to view these tools as essential to solving problems and equip them with the skills to harness them effectively.
What's next?
The technology sector, and AI in particular, holds the potential to reshape not just industries, but entire career landscapes. As we continue to nurture the next generation of talent, it is essential that we reframe the conversation around AI skills. By encouraging a mindset that drives individuals to leverage technology in their own fields, we can unlock a wealth of new opportunities and drive innovation across every discipline.
This shift requires a transformation in how we approach education, focusing on purpose-driven learning and real-world problem solving. If we are to fully realise the potential of AI and other technologies, we must ensure that they are seen as essential enablers of progress in every career, empowering individuals to make a meaningful impact on the world around them.
We now have the potential to create a significant change in the way people learn and work – educating them on how to combine new technologies with their existing skills and strengths to tackle real-world challenges, leading to groundbreaking solutions and unlocking limitless possibilities.
Lauren Birch
Lauren Birch is Talent and Skills Lead at Turing Innovation Catalyst Manchester.
