As AI becomes table stakes in investment management, firms looking to keep pace, grow and scale need to know how to best implement it. Some firms are already succeeding and, as a result, winning and retaining clients faster than others. But what’s setting those firms apart?

The answer is simple enough: AI is helping them elevate the client experience, strengthen existing relationships and better demonstrate value to prospects. The real differentiator lies in where they’re implementing AI.

Four moments where AI quietly makes the difference

Across firms that consistently win and retain clients, AI tends to show up in the same four places. Miss these, and no amount of “AI strategy” makes a difference.

1. Before the meeting

Some teams walk into client meetings reacting to the latest reports. Others walk in already knowing what questions their clients will ask.

AI built on trusted data reduces the time spent reconciling numbers, validating reports and pulling context from multiple systems. That reclaimed time can be channeled into better preparation, clearer narratives and the ability to proactively surface insights, opportunities and issues.

What this may look like in practice:

  • An advisor asks AI to summarize key portfolio changes since the last meeting, including performance drivers across public and private assets

  • A CIO reviews an AI-generated briefing that highlights emerging risks, liquidity considerations and talking points tailored to that specific client

  • Teams enter meetings with likely client questions already surfaced and prepared for, rather than reacting to them in real time

Clients don’t walk away thinking “great use of AI.” Rather, “they really understand my situation.”

2. During the meeting

Every client meeting has unforeseen questions:

  • “How much liquidity do I really have?”

  • “Why did performance change last quarter?”

  • “What happens if markets move this way?”’

In many firms, these questions still trigger a pause before a follow-up. But when AI is embedded into workflows, teams can respond quickly, confidently and consistently because insights are grounded in governed, unified data.

What this may look like in practice:

  • An advisor uses AI to instantly explain performance attribution without disrupting the flow of the conversation

  • A portfolio manager asks AI to model the impact of a market shift or allocation change during the discussion

  • Teams answer complex questions without caveats like “we’ll confirm offline,” reducing uncertainty in the room

In key moments, AI can help teams instill confidence. Confidence is one of the strongest trust signals a firm can send.

3. Between meetings

Clients rarely leave because of one bad interaction. They leave because, over time, they feel unseen. AI enables firms to spot changes, risks or opportunities before clients ask, prompting proactive outreach rather than reactive explanations.

What this may look like in practice:

  • AI flags when portfolio drift, cash levels or risk exposure crosses thresholds that warrant outreach

  • Advisors receive prompts to check in based on relevant portfolio or market changes, as opposed to generic cadences

  • Client communications are triggered by insight instead of schedules

With AI, firms are better equipped to pursue proactive communication and deliver information and insights without being prompted right when clients need it most.

4. During prospecting

Prospects may be intrigued by the promise of more data. But what matters more than breadth of data is data clarity — and most importantly, the ability to show them the “right” data.

Firms that use AI well can articulate how they manage complexity, anticipate risk, and think ahead without overwhelming prospects with reports or jargon. Further, they can more easily deliver a personalized, holistic portfolio view, encompassing all the data and information prospects care about most.

What this may look like in practice:

  • AI synthesizes relevant portfolio data, assumptions and historical context, reducing the effort required to tailor prospect conversations to specific goals, asset mixes or concerns

  • AI helps teams explain complex situations clearly and consistently by surfacing key considerations and implications from existing data

  • With context assembled upfront, conversations center on interpretation and decisions rather than how the data was gathered or reconciled

AI itself may not close a deal, but it can help teams remove friction, uncertainty and doubt, which is often what stalls decisions.

The pattern behind firms that grow

Across all four junctures, the same pattern appears:

  • Less time spent deciphering data

  • Faster, more confident responses

  • More proactive engagement

This results in clearer conversations and stronger client relationships, and becomes possible when AI is built on data teams trust and embedded into how they actually work.

The only question that matters

If you’re evaluating AI or already using it, here’s a test. Ask yourself: Does this meaningfully change how clients experience working with us? 

If the answer is no, it’s just another initiative. But if the answer is yes, AI becomes a powerful lever for growth.