The “augmented” relationship manager: Smarter, better, faster

This podcast episode is based on the Deloitte Luxembourg article below and includes content generated, assisted, or edited using artificial intelligence technology. It has been reviewed by a human prior to publication. The voices featured are synthetic. This podcast is provided for general information purposes only and does not constitute any kind of professional advice rendered by Deloitte Luxembourg. Deloitte Luxembourg accepts no liability for any loss or damage whatsoever sustained by any person who uses or relies on the content of this podcast. 

Introduction

Private banks are navigating one of the most rapidly evolving landscapes in decades. Clients now expect hyper-personalized, real-time experiences, while digital transformation continues to redefine the rules of engagement. At the same time, intensifying competitive pressures are forcing traditional institutions to rethink their operating models and accelerate innovation.

As The Guardian recently reported, GBP 100 billion (USD 131 billion) in deposits left UK high street banks in a single year, as savers shifted to digital-first challengers.

Within this context, RMs remain at the forefront of value creation. Yet their day-to-day work is increasingly shaped by compliance checks, reporting obligations, and administrative work. This not only reduces the time available for strategic advice and meaningful client engagement but also inflates cost-to-serve.

Private banks therefore face a dual imperative: improve the accuracy of regulatory processes and free client-facing teams to concentrate on revenue-generating activities.

AI adoption is already accelerating. Deloitte’s 2025 Predictions Report anticipates that by 2027, half of all companies using Generative AI will have deployed AI agents. Wealth management will be no exception.

A new generation of AI, Agentic AI, is emerging in response to these challenges. It is best understood as part of a broader multi-agent network that can collaborate across processes such as know-your-customer (KYC) maintenance or anti-money laundering (AML) investigations, going beyond traditional task automation.

Unlike conventional automation, Agentic AI can pursue objectives autonomously, make decisions, and take actions with limited human intervention. This shifts AI from executing isolated tasks to supporting end-to-end processes. In practice, Agentic AI can manage routine activities such as monitoring portfolios, generating reports, and tracking regulatory updates, allowing RMs to focus on higher-value work.

Agentic AI does not replace human expertise; it enhances it by multiplying productivity, strengthening client relationships, and improving overall service quality.

What is Agentic AI?

Agentic AI refers to autonomous systems capable of executing complex tasks with minimal human intervention. It is both goal-oriented and adaptive: it continuously monitors changing conditions, analyzes data in real time, and takes proactive steps to complete tasks efficiently.

Unlike traditional Generative AI, which responds to prompts, Agentic AI initiates actions, connects multiple processes, triggers workflows, and interacts across systems to achieve defined objectives. Generative AI remains reactive; Agentic AI is proactive.

In wealth management, the implications are tangible. Agentic AI can automatically flag portfolio risks, generate tailored investment proposals, or coordinate compliance checks without constant RM oversight. In turn, RMs can redirect their attention toward higher-value client interactions.

Transforming the RM’s daily workflow

The impact of Agentic AI on RMs is best understood through its effect on their daily activities. RMs constantly balance time-consuming administrative work with revenue-generating advisory responsibilities. Agentic AI reshapes this balance by reducing the burden of non-revenue tasks—while remaining compliant with regulatory requirements and completing administrative activities—and by enhancing efficiency in high-value engagements.

A clear way to frame this transformation is in two dimensions: liberating RMs from non‑revenue tasks, and enhancing efficiency in revenue-generating activities.

Liberating RMs from non‑revenue tasks

• Compliance and reporting: Agentic AI is already reshaping some of the most time-intensive compliance processes, reducing AML review times from 90 minutes to just 12, and enabling KYC onboarding that once took four hours to be completed in seconds. Large universal and custodial banks are already reaping the rewards, with one global institution reporting over 10,000 hours saved annually through AI-driven automation. Early adopters emphasize not only time savings but also fewer false positives and greater compliance scalability, even as challenges around explainability and data quality persist. However, private banks are still catching up, constrained by lower volumes, complex client structures, and legacy IT systems.
• Administrative workflows: Pilot programs in large banks show that Agentic AI can automate up to 90% of meeting administration—from capturing discussion points to updating CRM—while RMs still provide key inputs and final validation.
• Regulatory intelligence: Agentic AI can reduce manual compliance tasks by up to 70% by anticipating the impact of regulatory change on client portfolios and analyzing large volumes of data points in seconds.

Enhancing efficiency in revenue-generating activities

• Personalized investment recommendations: By analyzing client objectives, risk tolerance, and market dynamics in real time, Agentic AI surfaces tailored investment opportunities. It can dynamically detect underexposure to sustainable assets and proactively recommend ESG-compliant instruments as market conditions evolve, resulting in up to 75% of time savings in ESG assessment phases.
• Proactive client engagement: Agentic AI can pinpoint critical engagement moments, such as liquidity events or unusual transactions, often before they even reach the RM’s radar. It sends alerts instantly, enabling timely outreach that strengthens trust and uncovers new business opportunities.
• Scalable, personalized communication: Agentic AI can draft portfolio updates, investment proposals, and follow-ups tailored to individual preferences. By combining scale with personalization, it ensures clients receive timely, relevant, and human-validated communication.

Expected benefits

The true value of Agentic AI in wealth management lies in augmenting human expertise, not replacing it. Its impact is clear across three dimensions:

• For RMs: By automating compliance monitoring, data collection, and administrative follow-ups, Agentic AI reduces routine workload and enables RMs to dedicate more time to building trust and delivering strategic advice. As AI agents become increasingly embedded in enterprise workflows, professionals can focus on the activities that truly drive growth.
• For clients: Clients benefit from more proactive, personalized, and seamless service. Agentic AI analyzes portfolios in real time, uncovers opportunities, and anticipates risks. This empowers RMs to deliver timely, tailored insights at scale, boosting responsiveness, satisfaction, and client loyalty.
• For private banks: Agentic AI delivers operational efficiency, stronger compliance, and a differentiated competitive position. By automating KYC monitoring and remediation, audit documentation, and portfolio monitoring, it cuts costs, improves accuracy, and frees client-facing teams to focus on revenue-generating activities. Research shows that leveraging Agentic AI not only strengthens compliance and manages complexity but also boosts RM productivity, unlocking new avenues for growth.

Challenges and safeguards

Agentic AI requires robust governance and risk oversight. Its successful adoption depends not only on technical performance, but also on building trust, meeting regulatory expectations, and integrating smoothly into existing workflows.

• Human oversight: While Agentic AI can operate autonomously, RMs remain responsible for client advice. AI supports decision-making but never replaces human judgment. Targeted human controls are needed to maintain trust and accountability, even as the effort required is significantly lower than for fully manual processes. This aligns with broader Deloitte insights that, alongside efficiency gains, AI introduces new risks—from model bias to unintended agent behaviors—that must be actively managed.
• Data protection and regulatory compliance: Wealth management operates in a highly regulated environment. Any AI deployment must comply with GDPR and emerging standards like the Digital Operational Resilience Act (DORA). Robust safeguards for data security, explainability, and auditability are essential to satisfy regulators and internal risk functions.
• Integration with existing systems: Agentic AI must seamlessly integrate with core banking systems, CRM platforms, and compliance infrastructure. Poor integration increases the risk of fragmented workflows and shadow IT, while orchestrating AI across multiple systems ensures performance, scalability, and operational coherence.

In private banking, addressing these challenges is as much about reinforcing client confidence and organizational resilience as it is about mitigating risk.

Deloitte Luxembourg leverages advanced AI experience and deep industry insight to help banks turn these challenges into strategic opportunities. It supports institutions in defining AI and automation strategies, implementing Generative and Agentic AI solutions, redesigning processes, establishing governance frameworks, and upskilling teams. Drawing on its global network and proven methodologies, Deloitte Luxembourg helps private banks evolve how they operate, compete, and deliver value in the digital era.

Conclusion

Agentic AI is reshaping private banking and its workforce organization. By taking over operational, data-heavy tasks such as compliance, reporting, portfolio monitoring, and client communications, it enables RMs to focus on what truly matters: delivering personalized advice, engaging clients at the right moments, and building lasting trust.

For private banks, this means stronger compliance, greater efficiency, and a competitive edge. A recent Deloitte study indicates that Agentic AI could free up to 30-50% of the time of RMs and their assistants, depending on the bank’s current organization and level of agility.

With AI augmenting, rather than replacing, human expertise, RMs can work more effectively, clients receive proactive, tailored service, and institutions unlock sustainable growth, proving that the future of wealth management lies in the seamless collaboration between human insight and intelligent automation.