UK AI Competitiveness: Talent, Ethics & Growth Strategies with Dr. Andrea Isoni

Dr. Andrea Isoni on UK AI competitiveness: talent visas, national tech funds, ethical ROI, and defence/pharma growth. Solutions for policymakers and businesses

The UK's AI competitiveness hinges not on funding alone, but on dismantling talent barriers and strategically emulating global pioneers. Dr. Andrea Isoni, a Chief AI Officer and AI speaker, contends that while the UK’s R&D tax incentives provide a foundation, the critical bottleneck is restrictive immigration policies stifling skilled labor mobility. His solution? Fast-track visas for essential foreign talent and an Israeli-inspired national tech fund to propel innovation beyond incremental gains.

Isoni further diagnoses systemic challenges: global regulatory friction in AI adoption, ROI-driven ethical balancing acts, and urgent upskilling needs. He advocates for nationwide AI literacy programs, targeted child safety guardrails, and doubling down on defense/pharma sectors, where geopolitical and scientific tailwinds promise explosive growth.

Below, he unpacks pragmatic steps to transform ambition into advantage.

How can the UK ensure its AI industry remains competitive on a global scale, especially with rising competition from tech giants in the US and China?

A: In the UK we have already tax incentives to companies that invest in R&D. The issue now is talent movement which is restricted. This needs to be addressed: at least for certain categories of foreigners should be easy to move in the UK regardless of their nationality.

Also they can copy Israel and have a national fund to invest in tech.

What are the key challenges the UK faces in integrating AI across traditional industries (such as manufacturing, healthcare, and finance), and how can these barriers be overcome?

A: I believe this issue is global not only applicable to the UK.

Simply, it takes time especially in regulated industries as you mentioned (healthcare etc.). To apply AI in a scalable way you need investment in IT infrastructure and skills which take years. On top of that, additional regulations like the EU AI Act are coming into effect, Which will require further compliance costs.

Overall I can see there is an interest to move forward, yes we can move a but faster but the intention is there.

With rapid advancements in AI, how can UK businesses balance innovation with ethical considerations, especially in terms of data privacy and algorithmic bias?

A: At the end, what matters for companies is return of investment, ROI. If they don't know how to start, an external assessment can be beneficial to understand where AI can add value.

Then, if the AI application to be deployed is complex and multi faceted (ethics, compliance ,data from third parties etc.), an external provider can speed up the learning curve and transfer knowledge to the company (even if they plan a handover in 1 year from engagement, they can accelerate the learning curve and spare least 1 or 2 years).

The UK government has made significant strides in AI policy and investment. What further initiatives or regulations would you recommend to foster AI innovation while maintaining public trust?

A: A national educational program to use AI will be beneficial. There are already some authorities that move in that sense but a nationwide program would be better.

At the same time, somehow AI usage should be limited for children as it can affect the development of cognitive abilities (I know it is difficult to implement but some limitations should be in place).

How is the shortage of skilled workers in AI and data science affecting the growth of the tech sector in the UK, and what steps should be taken to address this skills gap?

A: As I said before, visa for foreigners should become relatively easy to get to incentivise skilled labour to work in the UK.

Looking at the next five to ten years, which sectors do you believe will see the most significant growth due to AI technologies in the UK, and how can businesses prepare for these changes?

A: Defence sector and pharma. The first is also due to geopolitical reasons the second is due to new potential applications of AI in drugs or materials discovery.