July 8, 2025
By Mike Davies
We are constantly being told about AI and Gen AI opportunities that will transform current operating models almost unrecognisably, and commercially change the landscape completely. This may be the future, but what of the challenges to get there?
I spoke to our clients in the Financial Services & Banking Technology space, focussing particularly on the Private Banking and Wealth Management sectors. We asked what their views were on the difficulties in monetising Artificial Intelligence. What areas are they prioritising? Have they already tried to implement relevant solutions, and what were the lessons learnt?
The key five themes that came out of my client conversations were:
Data Privacy, Sovereignty, and Disparate Locations
Private Banking and Wealth Management prioritise safeguarding sensitive client information, highlighting the critical importance of data privacy. AI technologies, integral to operations, rely on extensive data sets, necessitating meticulous adherence to regulations such as GDPR. Establishing on-site AI frameworks provides hands-on security management, contrasting with cloud services that demand rigorous protective measures.
Managing diverse data sovereignty laws globally, especially post-Brexit, presents intricate challenges for cross-border firms. Neglecting robust security measures may result in substantial breaches and reputational harm, underscoring the paramount significance of customer data protection in the financial sector.
Evolving Regulatory Landscape
The evolving landscape of AI regulation presents a complex challenge for UK firms. With the EU's AI Act implemented in March 2024 and the UK pursuing its unique regulatory framework for AI, navigating divergent regulations across jurisdictions remains a pressing concern. Staying compliant amidst these dynamic changes poses a continuous and substantial hurdle for businesses in the UK.
Workforce Challenges
A key challenge facing AI adoption in UK Wealth Management and Private Banking lies in the recruitment and retention of proficient AI specialists, data scientists and Technology leaders. The absence of a seasoned workforce hampers organisations in implementing AI projects effectively and offering continuous support to staff. Moreover, it is vital to address employee reluctance towards embracing new technologies that demand substantial upskilling and flexible adjustment to swiftly evolving systems and procedures.
Data Challenges for Model Training and Accuracy
The quality of training data is paramount for the success of AI applications. Inadequate data volume can lead to models underfitting or overfitting, hampering their ability to generalise effectively. Strong governance to maintain data consistency is crucial in preventing discrepancies and biases that may skew results.
Ensuring accuracy is essential, as using data from one industry to train models for another can yield misleading conclusions. Incorrectly labelled data poses a significant risk to the precision and reliability of AI models.
Legacy Systems and Infrastructure
Many established Private Banks in the UK are still dependent on outdated core banking systems, some of which have been in place for decades. The modernisation of this legacy infrastructure is crucial for the successful integration of new AI technologies and represents a substantial endeavour. The maintenance comes at a high cost, redirecting resources that could otherwise fuel innovation in AI. The process of integrating new AI infrastructure with the existing legacy systems is intricate, expensive, time-intensive, and necessitates a proficient technical workforce.
The opportunities presented by AI in banking and wealth management are immense, but the road to realising them is far from simple. From regulatory complexities and data governance to legacy systems and talent shortages, leaders face a web of challenges that demand strategic clarity, technical expertise, and cultural readiness.
At Norman Broadbent, we partner with organisations navigating these transformational shifts, helping them identify and secure the leadership and specialist talent required to embed AI meaningfully and sustainably. Whether building out AI capabilities, transforming legacy systems, or preparing your workforce for change, we bring deep sector insight and a consultative approach that ensures you’re not just reacting to disruption, but staying ahead of it.