Big Changes Are Coming

Here’s my prediction:

Few advisors are prepared for the massive change coming to the advisory profession. It will not be a slow rollout over decades. In three to five years (if not sooner), how advisors do business will fundamentally change.

I want to be clear. I’m not suggesting AI will replace advisors. All I’m saying is that the industry will fundamentally change.

Here’s why I feel that way.

The automation onslaught

AI's capability to automate and streamline many of the tasks currently performed by human financial advisors is at the core of my prediction. From portfolio management and investment analysis to risk assessments and financial planning, AI algorithms can process vast amounts of data, identify patterns, and generate recommendations quickly and accurately.

One primary area where AI is poised to make significant inroads is investment management. Traditionally, financial advisors have spent countless hours researching markets, analyzing portfolios, and making informed investment decisions on behalf of their clients. However, AI-powered robo-advisors have already demonstrated their ability to handle these tasks incredibly efficiently.

By ingesting and processing massive amounts of financial data, AI systems can generate investment recommendations tailored to individual clients’ risk profiles and goals. These robo-advisors can continuously monitor market conditions, rebalance portfolios, and execute trades automatically, potentially reducing the need for human intervention and oversight.

The personalization paradox

Ironically, one of the strengths often touted by human financial advisors – personalized service and understanding of individual client needs – may also be undermined by AI. As machine learning algorithms become more sophisticated, they can potentially analyze a client’s financial situation, life goals, risk tolerance, and behavioral patterns with unprecedented depth and precision.

AI systems can then use this wealth of data to generate highly personalized financial plans and recommendations tailored to each client’s unique circumstances. This level of customization, combined with the ability to adapt and refine recommendations continuously based on changing conditions, could surpass the capabilities of even the most dedicated human advisors.

IBM asks: “What if cognitive technologies, such as artificial intelligence (AI) and machine learning, could design a personalized investing experience?” It notes, “Disruptive technologies are fundamentally changing the financial services industry.”

These changes are accelerating rapidly.

The human touch at risk

Beyond the technical aspects of financial advisory services, AI also threatens to encroach on the interpersonal domain. Chatbots, virtual assistants powered by natural language processing (NLP), and conversational AI are increasingly adept at engaging in natural, human-like interactions.

As these technologies advance, they may eventually be able to replicate – or even surpass – the warmth, empathy, and rapport that human financial advisors strive to cultivate with their clients. Clients could potentially interact with AI-powered virtual advisors that provide sound financial guidance and offer emotional support, build trust, and foster long-term relationships.

According to some predictions, chatbots are on track to become the primary channel for customer support in 25 percent of businesses by 2027.

Bursting the M&A bubble

In recent years, the financial advisory industry has witnessed a wave of mergers and acquisitions (M&A) as firms seek to consolidate their market positions and leverage economies of scale. However, the advent of AI may ultimately undermine this trend, potentially bursting the M&A bubble.

The primary driver behind the M&A frenzy has been the pursuit of operational efficiencies and cost savings. By combining resources, firms seek to streamline processes, reduce redundancies, and capitalize on shared infrastructure and expertise. However, AI threatens to disrupt this calculus by offering a more cost-effective and scalable solution.

With AI’s ability to automate tasks, analyze data, and provide personalized recommendations, firms may find that they can achieve the same operational efficiencies without costly mergers or acquisitions. AI’s potential to disrupt traditional business models could render some mergers obsolete as clients gravitate towards more cost-effective, technologically advanced offerings.

As a result, firms that invest heavily in M&A may find themselves saddled with redundant resources and outdated models that are ill-suited to the AI landscape. The M&A bubble could burst as AI makes consolidation’s perceived benefits obsolete.

Another issue is uncertainty. According to Anu Aiyengar, global head of M&A at JPMorgan, “Uncertainty is not a good thing for M&A.” She has observed acquirers waiting to see the impact of AI and pausing their acquisition efforts.

The coming AI singularity

While the impact of current AI systems is already proving disruptive, an even more seismic shift may lie on the horizon: the possibility of artificial general intelligence (AGI) reaching or surpassing human-level intelligence. Many experts believe we are rapidly approaching this “singularity” when AI will match or exceed human cognitive capabilities across virtually all domains.

Elon Musk and futurist Ray Kurzweil predict AI will reach human levels of intelligence by 2029. Others are more conservative and believe we will reach singularity in “20 years or less.”

For the financial advisory industry, singularity would represent an existential threat of unprecedented magnitude. Many core advisory roles could become obsolete if AGI reaches fluid intelligence, reasoning, and domain understanding far beyond human capabilities. An advanced AGI system could provide nuanced financial advice and life modeling that outstrips human advisors. It may even develop emotional intelligence to build trust and relationships more adeptly than humans.

Singularity could produce a superintelligent class of AI advisors who master all facets of financial services – technical, analytical, and interpersonal. Like other technological revolutions, human expertise could rapidly become obsolete.

Fees and the AUM model under fire

Beyond just automating core advisory services, the rise of AI also threatens to disrupt the economics and fee structures that have underpinned the financial advisory industry for decades. AI could put immense pressure on the traditional assets under management (AUM) fee model that many advisors rely upon.

The AUM fee has been the predominant pricing mechanism for professional money management services. However, as AI-driven solutions become more capable and affordable, clients may balk at paying high AUM fees.

Sophisticated AI investment management platforms could offer institutional-grade portfolio construction, monitoring, and rebalancing for a fraction of traditional AUM fees. Clients may opt for these low-cost, AI-powered solutions rather than pay substantially higher fees to human advisors, even with the added element of personal advice and guidance.

This could create a spiral, in which declining AUM fee revenue forces advisors to shed staff, reduce service offerings, and cut costs – making their human-guided value proposition even less compelling compared to AI alternatives. Under these margin pressures, many advisory firms may abandon the AUM model entirely in favor of different pricing structures like fixed retainers and hourly fees.

AI threatens to make virtually every aspect of an advisor’s services a commodity – from investment management to financial planning and client interactions. This could precipitate a race to the bottom on pricing as AI solutions turn premium advisory offerings into standardized, low-cost utilities available to anyone.

Some good news

The high-net-worth client segment may prove more resistant to AI-driven fee compression. Ultra-affluent investors with complex financial lives and highly specialized needs may still be willing to pay a premium for credentialed human advisors who blend AI-augmented insights with dedicated personal service.

Naysayers argue aspects like emotional intelligence and navigating ambiguity remain challenging for AI. Some clients will prefer human advisors, especially for sensitive matters. Regulation around data privacy and ethics could also slow widespread AI adoption.

An article in Financial Advisor Magazine doesn’t buy into the hype. The author believes clients will always recognize the value of human interaction, humans are more persuasive than machines, AI can’t manage family dynamics, and high-level planning is complex.

Final thoughts

AI’s rise poses a formidable challenge to financial advisors. It threatens the traditional advisory model as it automates core functions, replicates human interactions, and potentially achieves superintelligent singularity.

There’s already evidence of the ability of robots to connect emotionally with humans.

Chess and other games are complex. Yet, AI has demonstrated an ability to beat humans in Chess, Go, poker, and other games that require strategic thinking.

Disclosure

I used Claude.ai to provide an initial draft of this article, which I do with most articles I write. I’ve noticed it’s getting better at writing, and I have no doubt it will soon surpass my level.

I edited extensively, did extensive research, and hyperlinked to material facts, which is also my practice.

Dan coaches evidence-based financial advisors on how to convert more prospects into clients. His digital marketing firm is a leading provider of SEO, website design, branding, content marketing, and video production services to financial advisors worldwide.

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