Trust and Technology in Balance

In an industry built on discretion, personal relationships and long-term trust, few technologies have inspired as much excitement and apprehension as AI. The challenge now isn’t whether to adopt AI, but how to do so responsibly, effectively and at scale.

Once viewed as a peripheral tool for back-office analytics, AI has now entered the core of wealth management strategy. Across private banks, family offices and boutique advisers, it is beginning to influence everything from client onboarding to investment research, portfolio optimisation and pricing.

‘AI has become the most talked about and actively explored technology in wealth management,’ says Amit Gujar, principal at L.E.K Consulting. ‘Across the industry we’re seeing excitement, investment and experimentation – some global private banks have run over a hundred proofs of concept in the last two years. The focus is now shifting from experimentation to evidence: assessing which pilots deliver real commercial and client value and are worth scaling.’

That shift, from curiosity to capability – marks the beginning of a new era. Yet, as Gujar points out, the technology’s real impact lies as much in the groundwork it demands as in the automation it delivers. ‘The desire to leverage AI is forcing firms to get the foundations right – building single sources of truth, cleaning and reconciling data, and strengthening governance. In many ways, AI is making organisations rediscover their data and operating-model fundamentals.’

From Proof of Concept to Proven Value

While AI’s full potential in wealth management is still emerging, tangible progress is already visible. The early wins have come in operations and control, where automation is cutting costs and improving compliance.

‘AI is helping automate onboarding, client verification and monitoring activities – reducing regulatory friction while improving efficiency,’ says Gujar.

‘We’re also seeing tangible productivity improvements in middle office roles. One UK financial advice business has already achieved over 30% productivity gains among paraplanners and administrative staff through workflow automation and document summarisation tools.’

In portfolio management, adoption has been more measured. Machine learning has long aided quantitative hedge funds, but traditional private banks are still learning to embed these tools into day-to-day portfolio construction. The change, Gujar notes, is pragmatic rather than revolutionary; AI is starting to support research synthesis, risk analysis and optimisation, though human oversight remains essential.

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Augmenting, Not Replacing, the Adviser

Despite the advances in automation, Gujar is clear that the heart of wealth management remains interpersonal.

‘Wealth management and private banking is fundamentally about people,’ he says. ‘Clients value their advisers not just for technical competence but for empathy, perspective and the ability to act as a trusted sounding board. That human dimension is not replicable by machines.’

In Gujar’s view, AI’s role is to augment, not replace.

‘Over the next five years, advisers could realistically manage up to twice as many clients while maintaining quality of interactions, thanks to AI agents that summarise meetings, suggest next actions and prepare materials.’

The promise is efficiency without erosion of trust – advisers empowered by data rather than replaced by it.

‘The idea of replacing human was the original robo-advice thesis a decade ago – and it has not succeeded. Even in an era of digital abundance, clients are willing to pay materially more for a trusted adviser, including in remote or hybrid formats. AI will make those advisers more complete, not obsolete.’

The Boutique Advantage

If large global banks have the budgets for massive AI experiments, smaller firms have something equally valuable: agility. ‘Smaller and boutique firms face clear scale constraints but can succeed by being fast followers,’ says Gujar.

‘The democratisation of technology - through cloud platforms, open APIs and modular AI tools, now allows boutiques to deploy sophisticated solutions without heavy infrastructure investment.’

Their size can be a strategic asset.

He adds: ‘They can implement use cases that deliver near-term impact, client onboarding automation, lead scoring, or portfolio insight generation, without being distracted by enterprise-wide transformation programmes,’ he says.

Many technology providers now offer white-label AI copilots and analytics tools, configurable to individual brand identities and workflows. ‘Where large banks struggle with complexity and governance inertia, smaller players can move faster, foster innovation and maintain a high-touch culture.’

Pricing, Fairness and Value

Even as technology transforms delivery, pricing models in wealth management have proven remarkably stable. ‘Despite the narrative of digital disruption, wealth management pricing has been resilient,’ Gujar explains. ‘Advice, relationship management and holistic financial planning continue to command a premium.’

Where costs have fallen - particularly in asset management and execution, clients have benefited through more efficient value chains rather than cheaper advice.

‘Wealth managers rarely compete directly with robo-advisers or digital-only platforms on price. They compete on trust, empathy and access to expertise.’

Regulation, however, is accelerating change. The UK’s Consumer Duty has forced firms to confront legacy pricing disparities and align fees with fairness principles.

‘It has put a spotlight on eliminating cross-subsidisation, improving client understanding and ensuring appropriate solutions for each client segment,’ says Gujar. The reforms, he adds, have had an unexpectedly positive outcome: ‘Some wealth managers have experienced over 10% increases in revenue, alongside improvements in margins, satisfaction and retention - a rare alignment of commercial, client and regulatory objectives.’

The lesson, he says, is that transparency pays. ‘The most successful firms view pricing not as a defensive regulatory requirement, but as an opportunity to reassert fairness, transparency and alignment with client outcomes.’

Competing Through Experience, Not Product

From the outside, wealth management can appear commoditised: similar portfolios, familiar brands, predictable performance. But Gujar argues the real differentiation happens in how well firms understand and serve their chosen client segments.

‘The leaders in this space are not competing on product; they’re differentiating through how well they understand, serve and retain specific client segments.’

For mass-affluent clients, hybrid models are flourishing - digital interfaces backed by human expertise when it matters. Among high-net-worth individuals, dual-adviser models are gaining ground, pairing relationship managers with technical portfolio specialists. And at the ultra-high-net-worth level, private banks are expanding into lifestyle and legacy services, from philanthropy advisory to global mobility support.

Firms are also evolving along three broader vectors: ecosystem partnerships, technology-led engagement, and experience design. ‘Leading firms are building ecosystems with adjacent players, from real estate and legal partners to sustainability data providers,’ Gujar says.

‘The best propositions blend behavioural analytics, private communities and curated content to create loyalty loops, particularly for the next generation inheriting wealth.’

The challenge, however, remains constant: scaling personalisation without losing intimacy. ‘AI and automation can enhance insight, but they can’t replicate empathy,’ he cautions. ‘The most successful firms will be those that strike the right balance between algorithmic precision and emotional resonance.’

AI in Private Markets: From Experiment to Execution

In private capital and alternative investments, AI’s influence is real but still forming. ‘Most firms are experimenting rather than transforming,’ Gujar says. ‘The most visible gains are in data aggregation, document analysis and pattern recognition, not yet in making or validating investment decisions.’

Private markets remain data-poor and fragmented, which limits AI’s accuracy. Yet the direction is clear. ‘Automation is bringing genuine productivity benefits in operational areas like portfolio monitoring and reporting. But deal origination and valuation still rely heavily on human judgment and local insight.’

Firms exploring AI in private markets should do so with humility. ‘Access is broadening, but that doesn’t make it easy or risk-free,’ Gujar warns. ‘AI can help manage complexity, but it cannot remove illiquidity, opacity or long duration.’ Its best use is in screening, diagnostics and client education, helping advisers turn complexity into clarity.

Upskilling, he stresses, is crucial.

‘Teams must understand what AI can and cannot do and be able to question its outputs intelligently.’ The smartest adopters start small and scale carefully, embedding governance and compliance from day one. ‘AI will undoubtedly expand the tools available to wealth managers, but it’s not a shortcut. The firms that succeed will treat AI as a decision-support system, not a decision-maker.’

A Sector Under Pressure and Poised for Renewal

The next decade, Gujar believes, will test financial services as never before. ‘Firms now face a lower interest rate environment, sustained cost pressures, and intensifying margin compression,’ he says. ‘The easy tailwinds have gone; growth now has to be earned in a far more competitive and scrutinised environment.’

Amid that compression, AI will act as both disruptor and divider. ‘Firms with the right data foundations and governance frameworks are seeing meaningful productivity gains; others are discovering that AI introduces new risks from model bias and data fragmentation to regulatory exposure.’

Regulation is evolving in step. ‘Expect new standards on explainability, data provenance and human accountability ensuring firms can show why an algorithm made a decision,’ Gujar predicts. The EU AI Act, the FCA’s Consumer Duty, and MAS requirements in Singapore are all shaping global standards. ‘AI can assist decision-making; it cannot replace fiduciary duty.’

The Next Frontier

As AI reshapes everything from compliance to conversation, wealth management’s defining traits - trust, empathy, discipline remain its greatest strengths. The future belongs to firms that can combine the precision of machines with the judgement of humans.

‘The next frontier for private banks,’ says Gujar, ‘is thriving in compression - using AI, data, and disciplined focus to serve more clients, more personally, with fewer resources and greater trust.’

In an era where algorithms can simulate insight but not sincerity, the winning formula for wealth managers may be deceptively simple: master the fundamentals, data, discipline and dialogue and let technology do the rest.

"Trust and Technology in Balance" was originally created and published by Private Banker International, a GlobalData owned brand.

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