As technology fast becomes a commodity, orchestration is emerging as the hidden component of a successful business model

If 52 per cent of banks globally have made AI adoption a strategic priority, according to consultancy McKinsey, why have only 12 per cent deployed any meaningful use case?

Among asset managers controlling more than $15tn, 72 per cent believe AI will be transformative by 2028, yet only 16 per cent have defined strategies, according to consultancy BCG.

Across Europe, according to research from consultancy EY, 90 per cent of financial services firms report AI integration, but only 9 per cent see themselves ahead, while 29 per cent admit to falling behind.

These statistics reveal an industry caught between ambitious rhetoric and modest reality, within a rapidly changing technology environment. For wealth managers who have consistently embraced technology adoption, this can seem like an aberration. Those firms pulling ahead have mastered several key challenges that explain why most private banks fail to deliver.

The maturity gap starts at the top. Leaders treat AI strategically, while incumbents treat it as IT modernisation. JPMorgan Chase discusses AI use cases in earnings calls, UBS has positioned the executive board as transformation sponsors and Morgan Stanley’s board-level initiatives signal that AI recalibrates how wealth managers serve clients.

This CEO commitment matters because AI implementation forces uncomfortable questions about existing processes. Recently, while working with a leading European private bank, we witnessed a senior executive challenge their board about whether onboarding procedures were fit for purpose or maintained out of habit. That willingness to challenge legacy thinking distinguishes transformation from automation.

Each layer of AI adoption requires different governance, ensuring that firms scale responsibly and reshape adviser capabilities.

At the strategic layer, AI drives comprehensive transformation across major institutional processes. Client onboarding has emerged as a critical battleground where AI tools can reduce administrative workloads from 70 to 30 per cent, according to consultancy KPMG, freeing advisers to focus on client engagement.

This benefits the more complex legal structures where advisers have traditionally spent weeks reviewing family trust documentation and multi-jurisdictional arrangements. Firms that approach this sub-optimally find that humans continue to perform those process-heavy tasks which AI was intended to do, while AI is beginning to take on the roles that humans were hoping to do.

Firms that approach this sub-optimally find that humans continue to perform those process-heavy tasks which AI was intended to do, while AI is beginning to take on the roles that humans were hoping to do

The orchestration layer gives wealth managers a competitive edge by enabling multi-agent collaboration across domains. While AI agents handle tasks like documentation, legal and tax requirements, advisers can focus on building relationships and trust. An ‘agent registry’ ensures quality and easy access to proven AI tools without technical hurdles.

The sophistication gap becomes evident, with laggards still equating AI with desktop co-pilot rollouts, while leading wealth managers are building registries to manage agent quality, preventing unauthorised models from operating in regulated environments. This enables ‘drag and drop’ agent deployment across business units.

The tactical layer involves individual advisers creating agents for routine tasks such as statements or presentations. While 42 per cent of European banking clients say they would rely on AI for major financial decisions, according to the World Economic Forum, the hybrid approach remains the preferred model, recognising that wealth management remains about human trust enhanced by machines.

We refer to this as the democratisation of agents, and the guardrails that orchestrate these allow for mass adoption.

Poor data quality damages AI effectiveness, forcing a retreat to manual processes. This explains why some wealth managers appear transformed, while others remain unchanged despite significant investment. Traditional CRM tools in wealth management often struggle to give a single, real-time view of a client’s portfolio across asset classes due to the disparate nature of data. A single source of truth allows agents to produce this with minimum human intervention.

Regulatory scrutiny can help explain uneven transformational outcomes, with document analysis facing minimal external friction, potentially enabling rapid gains, while financial decision-making applications encounter intensive model validation requirements that slow deployment.

AI excels at compliance documentation and risk assessment, but human judgment remains essential for investment recommendations and next best actions. GDPR and FCA Consumer Duty requirements are cited as the biggest constraints by UK firms, according to EY. These barriers ensure adviser expertise becomes more valuable.

Two distinctive cohorts are emerging within wealth management, separated by their approach to governance and orchestration. Leaders building comprehensive frameworks are pulling away from competitors focused on productivity alone, understanding that AI demands organisational transformation, not just technology addition.

Laggards will compete on traditional advisory skills, while leaders offer enhanced human insight amplified by machine intelligence. The gap becomes notable in emerging areas like sustainable investing, where AI enables sophisticated ESG analysis.

For meaningful AI deployment, the answer lies in orchestration depth, not adoption breadth. AI will not replace advisers, but advisers using orchestrated AI will replace those who do not.

Firms succeeding will combine human trust with machine capability, redefining and enhancing wealth advice for the next generation. Those building governance frameworks now will deliver on promises and shape the industry’s future. The rest will join the 52 per cent of strategically committed banks, wondering why their investments failed to transform.

Vikas Krishan, head of UK and Emea and chief digital business officer at Altimetrik, a digital business enabler for global banks