narayan
Artificial intelligence is rapidly evolving from a productivity enhancer into an enabler of strategic growth for DC advisory practices, particularly in accelerating the convergence of retirement and wealth management. As advisors navigate margin pressure, rising client expectations, and increasing operational complexity, AI is emerging not just as a tool for efficiency, but as a catalyst for scalability—enabling firms to expand into higher-value client relationships and adjacent services without a proportional increase in cost. This scalability is especially critical for practices seeking higher margins, making AI a key driver of both operational efficiency and revenue growth.
However, AI itself is not the solution. The real value lies in how technology is applied to drive scalability. The role AI is beginning to play follows a familiar pattern seen in prior waves of technological change. Spreadsheets transformed financial analysis, CRM systems enabled scalable client management and cloud-based platforms and automation streamlined operations. Each step was not about the technology alone, but about how it allowed firms to serve more clients, more efficiently, and at higher levels of sophistication. AI represents the next phase in that evolution, with seemingly far greater impact on both scale and scope.
According to NMG Consulting’s 2025 DC Advisor Insights Study of approximately 600 advisors, AI adoption today is largely concentrated in foundational use cases. Advisors are widely leveraging tools such as Microsoft Copilot and ChatGPT. Use cases often revolve around using ‘filenoting’ services where AI transcribes client conversations and intelligently populates the advisor’s core tech systems. Early adopters are using AI to communicate with clients—creating content, sending letters, providing nudges, etc. Moreover, there is a great opportunity for advisors to do more with AI, such as advanced modeling, product comparisons, etc. However, adoption of these tools is in its early days but is certain to accelerate.
As evidence, nearly half of DC advisors reported investing in technology to improve efficiency, with adoption particularly high among DC specialists (68%) and hybrid advisors (55%), and these applications directly address one of the industry’s most pressing challenges: scaling operations in a margin-constrained environment.
Importantly, efficiency gains are not an end state. They are foundational to future growth. By reducing the time and cost required to service plans and participants, AI-enabled technologies will expand advisor capacity, creating the bandwidth needed to pursue new revenue opportunities. In this sense, operational efficiency and growth are not separate outcomes but mutually reinforcing.
This is particularly salient to advisors pursuing both retirement and wealth businesses. NMG’s analysis shows that practices that pursue both achieve higher gross margins, approximately 52%, compared to retirement-only models at approximately 45%. AI-enabled technologies help make this convergence operationally viable by enabling advisors to scale into adjacent services without a proportional increase in resources.
Increasingly, AI-driven analytics will allow advisors to identify key participant moments such as retirement readiness, job changes and rollover events, enabling proactive and targeted engagement. Segmentation and next-best-action tools support personalized advice at scale, increasing conversion into IRAs, managed accounts and broader planning relationships. These capabilities expand wallet share and unlock new revenue streams.
At the same time, AI can improve efficiency by automating workflows such as investment monitoring, benchmarking, proposal generation and compliance documentation at scale. It also enables scalable delivery of personalized communications and financial wellness programs. The result is lower cost-to-serve and higher advisor productivity.
This dual impact is what distinguishes AI from prior technological investments. It simultaneously expands top-line opportunities and improves bottom-line efficiencies. Advisors can engage more clients, deliver more comprehensive services and deepen relationships, all without linear increases in staffing.
As a result, advisory models are shifting from reactive service delivery to proactive, insight-driven engagement. AI-powered CRM systems and predictive analytics enable advisors to anticipate client needs, identify life-stage triggers and act earlier in the client lifecycle. This is increasingly important as competition centers on share of wallet, with clients seeking fewer, more integrated advisory partners.
Ultimately, the firms that will pull ahead are those that apply AI-enabled technologies to fundamentally reshape their economics. The opportunity is twofold and interconnected: capturing new revenue pools, including wealth management, rollovers and holistic financial planning, while simultaneously compressing delivery costs through automation, scale and reduced reliance on manual workflows. The firms that succeed will be those that recognize these are not separate strategies, but two sides of the same scalability equation.
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