As artificial intelligence becomes integral to wealth management, firms are shifting from retrospective analysis to real-time guidance and automation, driven by advancements in predictive and agentic AI, reshaping client engagement and operational models.
Benito Mable, co-founder and chief executive of Vault22, argues that wealth management is entering a new phase in which artificial intelligence helps people make better day-to-day money decisions, not just review past performance. His case reflects a broader shift across the industry: advisers and firms are increasingly using AI to automate routine work, improve client service and sharpen decision-making, while research from SmartAsset suggests more than 63% of independent registered investment advisers have already adopted AI tools. Fidelity, meanwhile, says more than two-thirds of firms are using AI in some form, with about half of those users deploying it at scale.
That growth matters because much of traditional finance remains backward-looking. Budgeting apps, investment platforms and digital banks have made it easier to see where money went, but they rarely help people act before a small mistake becomes a larger one. SmartAsset says predictive AI, machine learning and large language models are now being used to forecast investment performance and market trends, while Fidelity’s research points to faster efficiency gains, better decision-making and improved customer experiences as firms expand their use of generative AI.
The next step, according to KPMG, is more ambitious: agentic AI, which does not merely assist advisers but can also carry out complex tasks across the wealth-management chain. KPMG says these tools can help firms contend with rising costs and adviser shortages by automating work and continuously optimising operations. Another KPMG analysis said generative AI could also improve forecasting, risk monitoring, personalised advice and client communication. Industry consultants at N-iX say the main challenge is no longer whether the technology works, but whether firms can build the data foundations and regulatory controls needed to scale it safely.
Mable’s point is that the real prize lies in behavioural change. AI, he argues, can combine real-time data with behavioural science to identify patterns, anticipate problems and guide customers towards better choices before damage is done. That is in line with wider industry thinking. Altruist says AI has moved beyond experimentation and is now central to wealth and asset management, while EY research cited in its guide found that most firms already have multiple generative AI use cases in production and plan to expand further. The message from across the sector is clear: the firms most likely to win are those that turn data into timely guidance, rather than simply showing clients what happened yesterday.
Disclaimer: This article is intended to inform and educate, not to recommend or endorse any financial product, investment or strategy. Please consider your own financial circumstances and seek professional advice where appropriate before making financial decisions.
