Event round-up: AI Leader's Series: Neuro AI
As artificial intelligence continues to evolve at a rapid pace, researchers and practitioners are increasingly turning to neuroscience for inspiration. Neuro AI, an emerging discipline that combines principles from brain science with AI development, promises systems that are more efficient, adaptive, and capable of continuous learning. Yet these opportunities also introduce new challenges for governance, ethics, and organisational oversight.
Our first AI Leader’s Series session of 2026 brought together leading experts to explore what neuro AI actually means in practice, how it differs from conventional AI approaches, and what organisations need to consider as these technologies mature.
Key topics included:
- The definition and significance of neuro AI as a discipline bridging neuroscience and artificial intelligence
- Practical examples of neuro-inspired approaches, from neuromorphic computing to neurosymbolic AI
- Governance challenges posed by systems that continuously adapt and learn without full retraining
- Emerging regulatory and ethical frameworks needed for neuro data and brain-derived information
- Practical priorities for organisations engaging with neuro AI technologies
Summary
Speakers:
- Mishka Nemes — Product Manager, Responsible AI, Trilateral Research
- Professor Bernd Stahl — Professor of Critical Research in Technology, School of Computer Science, University of Nottingham
Key themes and highlights
1. What is neuro AI and why does it matter?
Neuro AI represents a fundamental departure from treating the brain as merely a metaphor. Rather, it involves translating specific principles of biological learning, memory, adaptation, and energy-efficient computation directly into AI system design. This emerging discipline bridges two previously distinct fields—neuroscience and AI—with benefits flowing in both directions: biological principles can advance AI capabilities, while AI techniques can help us understand the brain more deeply.
The significance of this shift cannot be overstated. Current AI systems, while powerful, often require complete retraining to adapt to new tasks or changing environments. Neuro-inspired approaches promise systems that can learn continuously, integrate new information without forgetting earlier knowledge, and operate efficiently even in resource-constrained settings. For AI leaders and organisations, this matters because it will fundamentally change how AI systems are managed, monitored, and governed.
- Neuro AI combines insights from neuroscience with AI development to create systems that mimic principles of biological learning and adaptation
- Examples include neuromorphic computing, which designs hardware and software to replicate neural processing, and neurosymbolic AI, which combines connectionist and symbolic approaches
- Nature-inspired algorithms—such as ant colony optimisation and octopus-inspired robotics—demonstrate practical applications of neuro AI principles in real-world settings
2. Challenges and governance implications
While the promise of neuro AI is compelling, significant challenges lie ahead, particularly for organisations tasked with ensuring these systems operate reliably and responsibly.
One of the core tensions is interpretability. Neuromorphic systems and some neurosymbolic approaches may improve efficiency and resilience, but they do not necessarily make systems more transparent or easier to understand. In fact, systems that learn continuously may become harder to predict and assure. What happens when something goes wrong, and how do we trace responsibility?
- Systems that continuously adapt and learn challenge traditional assurance and monitoring practices based on static model evaluation
- Risk profiles may shift in unexpected ways: while some risks might be reduced through improved efficiency, others may increase or emerge in new forms
- Accountability becomes complex when systems adapt autonomously—organisations must clarify who is responsible when a system's behaviour changes
- Effective governance requires systemic, ecosystem-level thinking rather than focusing narrowly on individual technologies
3. Regulatory and ethical boundaries for neuro data
An emerging but underexplored issue is the treatment of neuro data—information derived from or about the brain and nervous system. As neuro AI systems become more capable, they may increasingly draw on biological data, brain-imaging information, or neural recordings.
Neuro data is uniquely sensitive: it can reveal intimate information about cognition, emotional states, health conditions, and even predispositions. Unlike traditional personal data, neuro information has the potential to be re-identified and poses distinctive risks.
4. What organisations should be doing now
While neuro AI remains an emerging discipline not yet fully mature for widespread deployment, proactive steps taken now will position organisations to adopt these technologies responsibly and competitively as they mature. Proactive steps taken now will position organisations to adopt these technologies responsibly and competitively as they mature.
- Develop a clear understanding of what AI capabilities actually exist versus aspirational claims; avoid over-inflating the current maturity of neuro AI approaches
- Ask critical questions when evaluating vendors or developers: How does this system learn? How does it change over time? How do we know if it's behaving as intended?
- Consider efficiency and resilience benefits in context of governance trade-offs; not all efficiency gains justify governance complexity
- Begin developing governance frameworks that account for adaptive, continuously learning systems, including new approaches to assurance and monitoring
- Establish clear organisational policies around neuro data, even before such systems are widely deployed in your sector
Neuro AI represents a significant frontier for artificial intelligence, with genuine potential to create more efficient and adaptive systems. However, this progress must be accompanied by thoughtful governance, updated regulatory frameworks, and a commitment from organisations to engage responsibly with these emerging technologies. By beginning these conversations and preparations now, organisations can position themselves to harness the opportunities of neuro AI while managing its risks.
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Kir Nuthi
Kir Nuthi
Kir Nuthi is the Head of AI and Data at techUK.
She holds over seven years of Government Affairs and Tech Policy experience in the US and UK. Kir previously headed up the regulatory portfolio at a UK advocacy group for tech startups and held various public affairs in US tech policy. All involved policy research and campaigns on competition, artificial intelligence, access to data, and pro-innovation regulation.
Kir has an MSc in International Public Policy from University College London and a BA in both Political Science (International Relations) and Economics from the University of California San Diego.
Outside of techUK, you are likely to find her attempting studies at art galleries, attempting an elusive headstand at yoga, mending and binding books, or chasing her dog Maya around South London's many parks.
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Usman Ikhlaq
Usman Ikhlaq
Usman joined techUK in January 2024 as Programme Manager for Artificial Intelligence.
He leads techUK’s AI Adoption programme, supporting members of all sizes and sectors in adopting AI at scale. His work involves identifying barriers to adoption, exploring solutions, and helping to unlock AI’s transformative potential, particularly its benefits for people, the economy, society, and the planet. He is also committed to advancing the UK’s AI sector and ensuring the UK remains a global leader in AI by working closely with techUK members, the UK Government, regulators, and devolved and local authorities.
Since joining techUK, Usman has delivered a regular drumbeat of activity to engage members and advance techUK's AI programme. This has included two campaign weeks, the creation of the AI Adoption Hub (now the AI Hub), the AI Leader's Event Series, the Putting AI into Action webinar series and the Industrial AI sprint campaign.
Before joining techUK, Usman worked as a policy, regulatory and government/public affairs professional in the advertising sector. He has also worked in sales, marketing, and FinTech.
Usman holds an MSc from the London School of Economics and Political Science (LSE), a GDL and LLB from BPP Law School, and a BA from Queen Mary University of London.
When he isn’t working, Usman enjoys spending time with his family and friends. He also has a keen interest in running, reading and travelling.
Sue Daley OBE
Sue Daley OBE
Sue leads techUK's Technology and Innovation work. This includes work programmes on AI, Cloud, Data, Quantum, Semiconductors, Digital ID and Digital ethics as well as emerging and transformative technologies and innovation policy. In 2025, Sue was honoured with an Order of the British Empire (OBE) for services to the Technology Industry in the New Year Honours List. She has also been recognised as one of the most influential people in UK tech by Computer Weekly's UKtech50 Longlist and was inducted into the Computer Weekly Most Influential Women in UK Tech Hall of Fame.
A key influencer in driving forward the tech agenda in the UK, in December 2025 Sue was appointed to the UK Government’s Women in Tech Taskforce by the Technology Secretary of State. She also sits on the UK Government’s Smart Data Council, Satellite Applications Catapult Advisory Group, Bank of England’s AI Consortium and BSI’s Digital Strategic Advisory Group. Previously, Sue was a member of the Independent Future of Compute Review and co-chaired the National Data Strategy Forum. As well as being recognised in the UK's Big Data 100 and the Global Top 100 Data Visionaries in 2020, Sue has been shortlisted for the Milton Keynes Women Leaders Awards and has been a judge for the Loebner Prize in AI, the UK Tech 50 and annual UK Cloud Awards. She is a regular industry speaker on issues including AI ethics, data protection and cyber security.
Prior to joining techUK in January 2015, Sue was responsible for Symantec's Government Relations in the UK and Ireland. Before that, Sue was senior policy advisor at the Confederation of British Industry (CBI). Sue has an BA degree on History and American Studies from Leeds University and a Master’s Degree in International Relations and Diplomacy from the University of Birmingham. Sue is a keen sportswoman and in 2016 achieved a lifelong ambition to swim the English Channel.
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