A day in the life of a wealth manager, with and without AI

Wealth managers are some of the busiest professionals in finance. Advisors are constantly stretched thin between focusing on portfolio analytics, industry research, client communications, and proof of compliance. The day is made longer with tedious, manual work that can eat up their most productive hours. It’s a model that doesn’t scale well with today’s fast-paced, capital market demands.

So, how does that impact the individual experience?

Meet Dave — a Senior Wealth Manager at a fictional financial services firm. In this hypothetical scenario, his team has just integrated North, Cohere’s agentic AI platform for enterprise, into their systems. Using North’s Automations feature, Dave can build complex, multi-step workflows that eliminate friction and bottlenecks, leaving him more time in his day to do his best work, all using natural language to build the automation.

North seamlessly integrates with data across fragmented systems and internal/external services, providing a comprehensive understanding of an organization’s unique business context. With privacy and security at its core, North is designed to meet the needs of highly regulated industries like financial services. Learn more about Cohere solutions for the financial services industry.

So, let’s take a look at how Dave and his colleagues are using AI for a range of daily tasks like portfolio insights, research synthesis, and governed compliance. We’ll see how AI has transformed their day-to-day, replacing manual, siloed tasks with auditable, client-ready workflows.

The daily grind of traditional wealth management workflows

Every day, wealth managers like Dave must balance giving personalized advice to their clients with handling regulatory obligations that continue to escalate. This adds to the operational burden for Dave and his team as they navigate through a myriad of daily tasks.

Without AI tools at hand, Dave must use a range of disconnected software and research that drastically reduces his productivity and daily capacity. Traditional tools include:

• Client portfolio management: CRM, spreadsheets, and limited real-time analytics
• Market research: Emails, PDFs, text-based documents, and third-party investment terminals, such as Morningstar Direct, FactSet, and LSEG
• Compliance: Siloed compliance tools and manual attestations
• Communications: Text-based documents, PDFs, and emails
• Post-trade operations: Reactive queues and tribal knowledge

To add even more complexity, Dave must tackle all of these tasks in a high-pressure environment where clients and the firm demand nonstop excellence from their wealth management teams.

The work day, reshaped by AI

Dave arrives at work faced with a tsunami of tasks that need to be done by the end of the day. His top priority is a meeting with a new high-net-worth client, where he needs to propose a comprehensive investment strategy. However, yesterday was just as busy, and he hasn’t had time to sufficiently prepare.

Luckily, he’s built an automation in North that enables Dave to run through the workflow in minutes, giving him more time to review the output and think through his approach before the meeting.

Client proposal workflow using North Automations

This automation uses three different agents in succession. The workflow includes gaining insight into his new client’s investment position, compiling market research to help him formulate recommendations, and drafting communications materials. Dave’s expert approval is needed for any decisions.

Agent 1: Client intelligence

The workflow begins with a client intelligence agent that gives Dave a consistent, analytics-grounded view of his client portfolios across holdings and benchmarks. It then provides a risk profile of his new client, aligned to his firm’s policy and regulatory expectations, as well as a suitability assessment with explicit assumptions and limitations.

The day without AI:

• Previously, Dave’s client intelligence workflow was entirely manual and limited. To better understand his clients, he had to spend time compiling client activity data by hand, such as transactions, deposits, and withdrawals, analyzing it, and updating client records in Salesforce.

The day with AI:

• Using the agent, Dave has a more comprehensive view of his new client and their level of risk, and greater confidence in how he defends his positions, both externally and internally. With a deeper understanding of the client, he can now focus more attention on building a strong relationship.

Once the client intelligence agent has completed its task, it triggers the next agent in the workflow.

Agent 2: Research synthesis

Next, a research agent aggregates and synthesizes market data from multiple third parties and internal libraries. It generates concise, investment thesis drafts with clear assumptions and gaps flagged for Dave’s review. The agent also generates competitor and peer analysis structured for investment committees and client materials.

The day without AI:

• Dave typically sources market commentary, issuer research, and competitor intelligence from many different sources. However, synthesizing these insights used to be a manual, time-consuming, and inconsistent process.

The day with AI:

• With the agent, Dave’s research is more comprehensive and accurate, giving him a stronger, data-driven context to draw conclusions and make recommendations. And it all happens in minutes rather than hours.

Finally, the third agent in the workflow pulls client-facing materials together for Dave’s meeting.

Agent 3: Client communication

The communications agent automatically produces a first draft of investment commentary that is aligned with the firm’s voice and disclosure standards. It also generates quarterly review drafts that are grounded in portfolio and market context, and proposals that include modular sections for compliance and Dave’s own edits.

The day without AI:

• While developing communication documents, Dave used to spend significant time reviewing source materials, pulling in the appropriate data, and writing lengthy drafts.

The day with AI:

• Now, the agent helps Dave complete documents faster and more efficiently, preserving brand and compliance review gates while accelerating client touchpoints.

Helpful stand-alone agents for daily operations

North’s AI agents also help Dave and team with a range of compliance and operational tasks when needed. These agents are always available to assist with regulatory reporting and post-trade settlement processes.

Regulatory compliance agent

Dave uses a regulatory compliance agent to accelerate MiFID II-, Dodd-Frank-, and other regulations globally, as well as firm-policy-aligned reporting workflows, with structured data extraction from OMS/PMS and compliance platforms. The agent’s trade surveillance support gives him pattern summarization, alert triage, and case narratives. Its best execution documentation includes traceable inputs and reviewer checkpoints.

The day without AI:

• The financial services industry has seen regulatory reporting volume grow and rule complexity increase over time. With traditional, manual tools, Dave needed more and more hours for surveillance, attestations, and audit-ready records.

The day with AI:

• The AI agent enables Dave to scale his ability to handle compliance in the ever-changing regulatory environment — in less time, and with fewer steps. He is better informed on regulatory provisions that could impact specific clients or positions.

Operations intelligence agent

The operations intelligence agent reduces settlement and NAV reconciliation friction by summarizing exceptions, surfacing root-cause hypotheses, and suggesting operational next steps. It provides Dave with trade settlement status, break summarization across systems of record, and priority signals.

The day without AI:

• The mechanics of post-trade operations consumed a large portion of Dave’s time and extended risk windows. He had to carefully monitor the settlement and reconciliation processes so that trades closed quickly and smoothly.

The day with AI:

• For Dave, the settlement and reconciliation process has become easier, faster, and more efficient. He can now spend less time tracking mundane details and more time on tasks that require his judgment.

Explore more common uses of AI in finance.

At the end of the day: Greater speed, less risk

For Dave and team, integrating North’s AI agents into their daily workflows has been a game-changer.

Dave is now better supported by synthesized research and draft communications, so he can focus on judgment calls and client relationships. AI’s structured, queryable documentation with clear lineage makes it easier for Dave to provide compliance evidence for audits and regulators. Surveillance and related documentation are co-produced by Dave and AI together, including human review where required. And Dave’s perpetual backlog of exception handling is reduced with prioritized exception intelligence, including context and suggested next steps.

As a result, Dave and his wealth management team are now better able to:

• Connect meaningfully with more clients per day
• Maintain a more complete view of clients and their level of risk
• Work with more accurate research to formulate stronger recommendations
• Have more confidence in how they defend their positions internally and externally
• Stay informed on regulatory provisions that could impact specific clients or positions

For Dave’s firm, the AI tools offer additional strategic value, including:

• Improved client experience: Communications are faster and more consistent without sacrificing compliance review.
• Scalable regulatory compliance: Evidence-rich workflows scale with rule complexity.
• Greater operational resilience: There is less dependency on ad hoc heroics in ops and break management.

Implementing AI in wealth management

Cohere experts recommend starting with a pilot of the Regulatory Compliance Agent as it typically addresses the biggest pain points, the most manual hours, and the strongest regulatory urgency, making impact and measurement concrete early.

In our hypothetical scenario, Dave and team created this agent on North, connected it to their internal systems of record, added clear human-in-the-loop gates for material decisions, and determined a narrow initial scope (such as a best execution document or a single surveillance narrative workflow).

Once data access patterns and review models were proven, the team then implemented the Client Intelligence Agent, Research Synthesis Agent, and others.

Three critical success factors guided the team:

• Defined approval boundaries: The team automates drafts and analysis, and reserves human sign-off for regulatory submissions and client recommendations.
• Grounded connectors: They use production-grade MCP connectivity that scopes to OMS/PMS/CRM and compliance tools instead of generic file dumps.
• Time and quality metrics: The team tracks specialist hours saved, cycle times, and rework rates — not vanity adoption metrics.

North for agentic AI in wealth management

North is Cohere’s enterprise AI platform for agentic AI, combining our state-of-the-art generative and search models, customizable agents, and built-in workflow automations to enable wealth managers like Dave to accomplish tasks more quickly and with higher quality.

To learn how North can empower your wealth management team, contact us for a demo or explore our range of AI solutions for financial services.