The wealth management industry will be short 100,000 advisors by 2035. Demand for human advisors is rising. Clients with $500 to manage and clients with $50 million to manage both want human relationships. That is the context in which AI is being deployed right now.

At a recent RIA industry panel, two CEOs spoke plainly about what their firms are actually doing. Here is what stood out.

The results that matter

Wealth Enhancement Group cut first-close time from four months to two months using AI coaching. The process: AI analyzes call transcripts within five minutes of the call ending, produces an eight-area coaching report, and generates service recommendations. Advisors get feedback before the next conversation happens.

That outcome is worth pausing on. Reducing close time by 50% is a business model change.

How HighTower is building for scale

Larry, CEO of HighTower, described a three-part approach he calls 3.0: integrate, consolidate, and accelerate.

Integration means a centralized middle office handling onboarding and investments, taking that operational weight off advisors. Consolidation means launching HighTower Signature Wealth, a direct-to-consumer brand currently at $30 million in assets, targeting $50 million by year-end, with a goal of representing half the firm in three to four years. Acceleration means moving everyone onto a unified platform so the scale benefits compound.

This is a firm deliberately restructuring around where demand is going.

The growth benchmark

Wealth Enhancement Group scaled from $600 million to $160 billion in assets. Thirty percent annual growth, split evenly between organic and acquisitive. The firm's stated purpose: "We care for each other so we can care for our clients."

That is an operating principle, not a tagline. It shapes hiring, culture, and how technology gets adopted.

What change management actually looks like

Both firms described the same rollout sequence for AI tools: experimenters first, then early adopters, then mainstream. Always keep advisors in the decision loop. Prove the business case with rational benefits. Be willing to roll back investments that do not deliver.

The firms that struggle with AI adoption tend to skip this step. They treat change management as something that follows deployment. It does not. It precedes it.

Where the work actually happens

AI coaching, transcript analysis, and real-time recommendation delivery all require a data layer that connects to existing systems cleanly. The AI surface is what advisors see. The infrastructure underneath is what makes it work at scale.

The shortage is coming. The clients are not disappearing. The infrastructure question is worth answering now.