Journal of Financial Planning: March 2026
Chris Heye, Ph.D., is founder and CEO of Whealthcare Planning and Whealthcare Solutions.
The rise of large language models (LLMs) like ChatGPT and related AI-powered technologies has triggered considerable debate over the future of financial planning and advice. Few doubt that the spread of AI will have meaningful consequences for financial professionals and their clients. But there remains a broad range of opinions about exactly how these innovations will impact the industry, especially how they will affect the demand for financial advice and the professionals who deliver it.
What, Me Worry?
Perhaps the most common view, especially within the financial planning profession, is that AI will enhance the productivity of advisers, but not significantly impact overall employment levels. The phrase one often hears is that LLMs and other AI-powered algorithms will act as “copilots” and enable advisers to deliver higher quality services to a larger client base. Moreover, most financial professionals believe that even as AI helps to make investment portfolio management, back-office operations, and marketing activities more productive, it cannot replace a client’s desire to have a human being to talk to when making important financial decisions.
Part of the justification for this more optimistic view of the effects of AI lies in historical precedents. The thinking among many financial professionals goes something like this: We survived the growth of the internet, the introduction of robo-advisers, the aftermath of multiple major financial crises, and a once-in-a-century global pandemic. This time—meaning AI—is no different. We will endure this as well.
With apologies to Alfred E. Neuman, I refer to this view as the “What, Me Worry?” argument. It’s not quite business as usual, but close. As long as financial professionals continue to make AI-enabled productivity improvements, they will survive, and maybe even thrive. Sure, there will be some losers, but they will be confined largely to firms that fail to successfully adapt.
The Boiling Frog
The main counter argument, which I will refer to as the “Boiling Frog” view, goes something like this: Yes, you have survived other threats, and yes you may be able to hang on for a while longer, but this time it is different. AI is coming straight at you, and many financial services jobs will be lost. AI will get exponentially more capable at portfolio management, marketing, sales, and operations, and even at mimicking human connections. And consumers will grow to trust AI, just like they grew to trust entering credit card information, buying and selling financial products, or seeking medical advice online.
Adherents of the Boiling Frog view can point to recent studies, like the report recently published by Microsoft,1 that suggest that financial advisers are highly vulnerable to AI-driven technological change. Using 200,000 anonymized conversations between users and Microsoft Bing in 2024 to capture representative trends in AI usage, Microsoft sought to identify the occupations most likely to be replaced by AI. Microsoft then rated each occupation on a 6-point scale based on how much of the work activity AI appears capable of handling based on these online conversations.
The result is an “AI applicability score,” where higher values indicate occupations more exposed to AI. At the top of the “likely to be replaced” list are occupations like interpreters and translators (0.49), sales representatives of services (0.46), and writers and authors (0.45). By contrast, jobs such as dredge operators (0.00), pile driver operators (0.00), and maids and housekeeping cleaners (0.01) appear largely insulated.
Supporting the Boiling Frog argument, Microsoft generated a score of 0.35 for personal financial advisers, about the same as web developers, advertising sales agents, and switchboard operators. These findings do not bode well for the financial planning profession. They suggest the likelihood of increased service automation, major industry consolidation, and significant job losses.
So, who is right?
This Time It Might Be Different
I believe that neither of these arguments fully captures the complexity of AI-driven innovation.
Let’s start with the thesis, implied by the “What, Me Worry?” view, that this time is not all that different. I have generally been skeptical of “this time it’s different” arguments, largely because historically, it has never been different. In the long run, most major technological innovations, like the railroads or electricity or the internet, have created more jobs than they have destroyed.
But there are some historians of technological change, like Erik Brynjolfsson, who believe it is possible that this time is different. Brynjolfsson argues that because AI will replace not just physical work, but cognitive activities as well, and because the pace of AI innovation is exponentially faster than earlier technological revolutions, it could exceed the impacts of earlier innovations like electricity or the steam engine.2
The unique ability for AI to replace cognitive activities distinguishes it from previous major innovations. But there are all types of work activities that require cognitive, and not manual labor, skills. So how do we know exactly which of those activities will be replaced by AI? And how does the potential replacement of (specific) cognitive activities affect the supply and demand for financial professionals and the services they deliver?
The Boiling Frog view does not help us answer these questions. It simply says jobs will be lost, but not much more than that. It is a rather blunt instrument that does not shed much light on the nature of the changes that might occur in the industry. Importantly, it does not include the possibility that AI will lead to the creation of new jobs within the financial services industry, albeit those requiring a different set of skills.
A More Holistic Approach
To better understand the effects of AI on the financial services industry, we need a more holistic and nuanced theoretical framework. MIT economists David Autor and Neil Thompson recently published an article on the effects of automation on employment and wages.3 To better understand how technological change affects industries and occupations, they focus not on workers per se, but on the tasks they perform and the expertise level needed to complete those tasks.
Applying this “expertise” framework to predict how AI will impact the financial services industry, the key question becomes not whether AI will replace advisers. Rather, the question is which adviser tasks firms will choose to automate, and how those choices reshape the expertise, compensation, and activities of the workers who remain.
Autor and Thompson argue that technology-driven automation affects occupations in two fundamentally different ways:
- Expertise-augmenting automation. AI removes routine, low-skill work and raises the expertise bar for the remaining humans.
- Expertise-replacing automation. AI performs core expert tasks and shifts the remaining work toward lower-skill service roles.
Both paths are technologically feasible. The difference lies in how financial services firms choose to deploy AI within their service models.
Let’s start with the expertise-augmenting path, which I will refer to as the “Concierge Advisory” model. In this model, AI is used to strip away administrative and relatively low-expertise work like:
- Account creation and onboarding
- Data gathering and document preparation
- Asset allocation recommendations
- Trade execution and routing
- Meeting reminders and summaries
- Workflow routing and suitability checks
What remains for human advisers is identifying and managing more judgment-intensive, emotionally complex, and high-stakes client situations and concerns, including:
- Anxiety around money and market volatility
- Health events, caregiving, and long-term care decisions
- Cognitive decline and diminished capacity planning
- Retirement income tradeoffs under uncertainty
- Multigenerational and estate-planning conversations
- Family dynamics, conflict, and behavior change over time
Autor’s framework predicts that when low-expertise tasks are removed and high-expertise tasks remain, the occupation becomes more skilled, wages rise for those who stay, and headcount declines as each adviser can handle more complex relationships with the support of technology.
In the second model, which I refer to as the “AI-Guided Advisory” model, AI is not just a support tool. Rather, it becomes the expert engine that absorbs tasks, many of which once required advanced credentials, including:
- Portfolio design and construction
- Risk assessment and modeling
- Basic financial planning
- Retirement income projections and scenario analysis
- Tax withdrawal and optimization strategies
- Basic estate and wealth transfer planning
- AI-powered behavioral coaching
The human roles, in this case, shift toward service, programming, and distribution tasks such as:
- Onboarding and customer support
- Software design and programming
- Database management
- Business partnership development (e.g., employer-plan communication)
- Exception handling and escalation
When automation replaces expert tasks as in this AI-Guided Advisory model, more workers are qualified to do the work that remains. Wages tend to fall because less expertise is required, but overall headcount within the industry can increase as firms scale these lower-cost service models.
The Coming Industry Bifurcation
Importantly, these two paths lead to opposite employment and wage outcomes:
- Concierge advisory. Fewer, but more expert advisers; higher wages; deeper, more complex client relationships; a more personalized and holistic client experience.
- AI-guided advisory. More workers, but with lower average skill and compensation levels; highly scalable, low-cost delivery; more commoditized positioning.
I believe that to be successful in the age of AI, firms will need to choose one of these two paths. Many firms will become increasingly concierge-like and offer a comprehensive set of services delivered with large doses of empathy. The required skill set will shift from technical prowess to expertise in interpersonal communication, managing emotions and family conflict, and reducing anxiety and complexity.
Other firms will automate extensively and use AI agents to manage investment portfolios, guide financial planning activities, educate consumers, improve decision-making, and provide coaching tips. These firms will continually adopt the latest AI technologies while offering an increasingly human-like experience for their clients, whom they will be able to serve at scale.
It is conceivable that some firms decide to implement both models, but as two very separate business units. The AI-Guided Advisory service could be used as a feeder system for Concierge Advisory services, especially for clients with more complicated financial situations.
On the other hand, advisory firms that do not offer concierge-like services, communicate poorly, and fail to implement AI technologies extensively in their practice will be caught in the middle. They are the ones most likely to fail.
To summarize, the real question is not how AI will impact financial sector jobs, but whether and how it will be used to augment or replace expertise levels within firms. Importantly, financial planning and advice firms have agency. They are not inevitably doomed to be run over by the AI bus. It is each firm’s decision about which tasks to automate and which to augment that determines whether it adopts a smaller, expert-driven advice model or a larger, service-driven model anchored around technology.
Because there are millions of individuals and families in the United States who want and need help managing their financial lives, huge opportunities remain for financial services professionals.
Endnotes
- Microsoft Corporation. 2025, July. “Working with AI: Measuring the Applicability of Generative AI to Occupations.” www.microsoft.com/en-us/research/publication/working-with-ai-measuring-the-occupational-implications-of-generative-ai/.
- Brynjolfsson, E., B. Chandar, and R. Chen. 2025, November 13. “Canaries in the Coal Mine? Six Facts About the Recent Employment Effects of Artificial Intelligence.” Stanford Digital Economy Lab. https://digitaleconomy.stanford.edu/publications/canaries-in-the-coal-mine/.
- Autor, D., and N. Thompson, N. 2025. “Expertise.” Journal of the European Economic Association 23 (4): 1,203–1,271. https://doi.org/10.1093/jeea/jvaf023.