Mariner Partners With Humanity Labs for AI Workforce
Mariner, the Overland Park, Kan. The US-based national registered investment advisor, which manages more than $630 billion in client assets, has entered into a five-year partnership with technology provider Humanity Labs to grow its artificial intelligence workforce, representing more than 700 full-time equivalents.
Founder and CEO of Humanity Labs Andre Pop He describes his company and technology managed service as an AI-powered service, sitting on top of the consultant’s existing equipment and infrastructure systems.
That workforce will function as an embedded digital team, in this case, within Marine’s existing systems and workflows, handling back-, middle-, and front-office tasks, including customer onboarding, account opening, compliance reviews, customer reporting, invoicing and onboarding, according to the company.
The financial terms of the partnership were not disclosed.
“Every company in our industry has grown the same way: serve more customers, hire more people,” he said. Marty BicknellCEO and President of Mariner. “That model has a ceiling, and we decided to break it.”
The partnership positions Mariner as the first wealth management firm to adopt an AI workforce model at an enterprise scale, marking the shift from AI testing to product use cases embedded in core operations.
In theory, the AI workforce would store every task under a layer of shared memory, which the company calls Marine Organizational General Intelligence, proprietary operational intelligence that learns from every interaction.
“By moving work to an AI workforce, we’re creating more opportunities for our teams to build relationships, solve complex problems and provide the thoughtful guidance our customers expect,” said Cheryl Bicknell, Marine’s chief operating officer and chief strategy officer.
In a previously unpublished February interview, Humanity Lab Pop So far, most of what has been marketed in terms of agency AI can be divided into two tiers: AI-native software run by the consultant, which ultimately remains a bottleneck in terms of productivity, and AI agent builders deploying custom agents in organizations.
“The problem with the latter is that the company still owns the day-to-day operation and management of those agents, and you have a managed digital workforce, the RIA doesn’t buy equipment or hire people to build agents,” Pop said.
“When the company’s business processes don’t change, you get teams that deliver the finished product—the product, not the software,” he said.
