AI Is Reshaping Wealth Firms, but Relationships Still Drive Business: Q&A with Logan Henderson of Gridline
As RIAs scale through mergers and acquisitions and AI continues to infiltrate the industry, wealth managers are racing to adopt the technology and improve their data infrastructure, streamline operations, and deepen client relationships.
Logan Henderson, CEO of Gridline, discusses the long-lasting impact of AI in private markets, the challenges RIAs face around data integrity, and why the future of wealth management will remain deeply human-centered.
The following responses have been edited for clarity and conciseness.
CM: As financial advisors are turning to artificial intelligence to provide specialized services to their clients, how is Gridline positioning itself to integrate AI into advisors’ workflows?
[Gridline] sees AI, at its core, as a data problem within private markets, which is the ecosystem where it operates. Many pieces of information are still delivered manually through PDFs or Excel, and it is cumbersome for them to be able to extract, structure, and analyze those key points of data.
For Gridline, AI is an enablement function to extract that data, automate the reconciliation and structure of it, and then make it usable, so that [advisors] have the information available.
CM: As personalization scales, what metrics or KPIs should advisors track to know whether AI is improving client outcomes rather than efficiency alone?
The jury is still out on what the key success driver is. Today, advisors are adopting AI for efficiency gains that they’re going to have, but those efficiency gains are oriented towards delivering a better client experience and customer outcome.
It’ll take several years to see how customer satisfaction and stickiness are increasing, but the more advisors have that information available and the more mundane, day-to-day tasks are automated, they can be client-centric and focus on the “people side” of the business rather than the data, management, and administrative side.
CM: Through your platform, what types of proprietary data advantages is Gridline leveraging to make AI more effective for those who are using your platform?
There are two different elements to it, which all come back to data. The first component is the structuring of investment portfolios — analyzing and structuring the data so that it’s usable and that there is an informed perspective on how the portfolio is performing.
The second component, where we see a significant data advantage, comes down to due diligence. Alternatives do not have an ecosystem or a data repository; it’s a very manual process. [Gridline] has built a suite of solutions that leverage AI-native capabilities in the decision-making process.
CM: Do you expect AI to drive further consolidation in the RIA space by favoring firms with greater scale and data advantages?
As [RIAs] scale, they certainly have a data advantage, but they are also running into data integrity concerns. Many firms have scaled through acquisitions, and the core systems that they operate on are different. It may be a different reporting suite, custodial platform, or internal processes that they have built to help alleviate some of these historical pain points.
CM: As more firms start launching RIA referral programs, how have these programs evolved beyond traditional client-to-client referrals?
There’s going to be an area of partnership, whether it’s different technology or service provider solutions, that has some type of referral program. But firms are looking for a unified technology stack, not just client referrals and accumulating assets.
The key question is, “How do you better serve those clients?” It’s through a unified platform that can deliver value to the firm and deliver value to the client. There’s going to be more technology-driven and system-driven partnerships than the traditional advisor referral model, because inevitably, firms need to not only acquire that customer and bring them as a client, but they also need to be able to keep them for the long term.
CM: Looking ahead, what does a “next-generation” advisory practice look like to you in terms of technology stack, team structure, and client engagement?
The wealth management industry is and always will be a people-oriented business. While certain technological capabilities will make that more efficient, most firms or most clients want to have an individual who knows them, their family, their needs, and their appetites.
AI is really good at data and solving complex problems, but there’s still a psychological element, and maybe over time, it will continue to get better.
The next generation of wealth firms will spend far less time on the systems that they need to do their jobs. AI, especially agentic capabilities, will handle much of the day-to-day management at these firms, giving firms the ability to spend more time with their existing clients and meet prospective clients.
