Rob Arnott, founder of Research Affiliates, has long been known for challenging consensus views, and his latest take on artificial intelligence reflects that skepticism. While he admits to being impressed by the raw capabilities of AI tools, particularly large language models such as ChatGPT, Arnott remains cautious about the investing implications. For wealth advisors and RIAs seeking perspective on how to position client portfolios amid the hype, Arnott’s analysis offers a reminder to separate technological excitement from sound investment fundamentals.
Arnott recently described his surprise at ChatGPT’s ability to distill one of his own complex research papers into a concise summary. He admitted that he would have struggled to produce a synopsis of comparable quality and efficiency. That, in his view, highlights the disruptive promise of AI. Yet his admiration for the tool as a research aid does not extend to enthusiasm about AI-driven equity returns. For Arnott, the market narrative has already run far ahead of the earnings reality, leaving today’s AI leaders priced for perfection.
This distinction matters greatly for fiduciary advisors navigating client expectations. Clients are reading headlines about AI breakthroughs, from chatbots to autonomous systems, and many are eager to participate in what appears to be a generational opportunity. Arnott’s message is that the long-term benefits of AI may indeed materialize, but the valuations already assigned to many of the sector’s leaders leave little room for error.
Two main factors underpin his skepticism. First, Arnott questions the durability of margins in the semiconductor space, which has been at the center of the AI boom. Nvidia has become synonymous with AI due to its dominance in high-performance chips. But as Arnott points out, competitors like AMD, Intel, and even custom in-house chips from hyperscale cloud providers are unlikely to sit idly by while Nvidia earns extraordinary profits. For wealth advisors, this suggests a need to temper expectations of sustained dominance and outsized returns from a single hardware vendor.
Second, Arnott raises the issue of monetization. Many companies are investing heavily in AI infrastructure, pouring hundreds of billions into data centers, software integration, and specialized chips. Yet the path to converting that spending into consistent, scalable profits remains murky. While AI may deliver cost efficiencies and novel capabilities, Arnott notes that its ultimate customers — whether businesses or consumers — are still experimenting with how to generate real returns on those investments. For advisors, this gap between capital expenditure and realized profit is a key consideration when evaluating the long-term sustainability of AI valuations.
At the market level, Arnott warns that these dynamics have contributed to historically elevated valuations across U.S. equities. He points to the Buffett Indicator — total U.S. stock market capitalization relative to GDP — which sits at record highs. Similarly, the Shiller CAPE ratio, a widely watched measure of valuation adjusted for inflation and long-term earnings, currently stands around 38, making it the third-highest in history. These measures suggest that today’s equity environment is not only concentrated in a handful of mega-cap technology stocks but also priced well above historical norms.
For fiduciaries, this concentration risk raises important portfolio construction questions. Clients who remain heavily invested in large-cap U.S. growth equities may be vulnerable to a reversal if expectations fail to meet reality. Arnott himself stated he would be uncomfortable being fully allocated to the S&P 500 under current conditions, urging investors to look more broadly for opportunities.
Instead, Arnott highlights two equity segments where he sees more compelling value: small-cap value stocks in the U.S. and emerging-market value equities. These areas, in his view, are trading at significant discounts compared to the richly valued “Magnificent Seven” large-cap leaders. He is quick to push back against the idea that he is permanently bearish. “People have called me a perma bear,” he said, “but I just named two segments of the equity market that are high conviction.” His emphasis is on buying when valuations are cheap and avoiding crowded trades that require flawless execution to justify their price.
For example, he contrasts the valuation gap between mega-cap growth and small-cap value. Investors today must pay roughly 30 times trailing 12-month earnings to own the largest tech stocks. By comparison, small-cap value equities are available at a Shiller PE ratio closer to 12. That divergence, Arnott argues, creates a much stronger case for allocating to the latter, especially for long-term investors seeking favorable entry points.
Emerging-market value equities represent another area of opportunity, particularly for advisors willing to look beyond the U.S. Arnott acknowledges that these markets come with higher risks — political instability, currency volatility, and governance challenges — but he believes the valuation discounts more than compensate for these factors. For RIAs managing globally diversified portfolios, this is a call to re-examine emerging markets not as a speculative add-on but as a source of meaningful long-term return potential.
One practical takeaway for advisors is Arnott’s suggestion of using exchange-traded funds to access these undervalued segments efficiently. He specifically pointed to the Vanguard Small-Cap Value ETF (VBR) and the iShares MSCI Emerging Markets Value Factor ETF (EVLU) as representative vehicles. For wealth managers, ETFs provide diversified exposure while keeping costs low and implementation straightforward. These vehicles also allow advisors to express a value tilt in portfolios without the need to select individual securities in unfamiliar or volatile markets.
For fiduciaries guiding client allocations, Arnott’s analysis underscores the importance of balancing innovation-driven enthusiasm with valuation discipline. While it may be tempting to chase momentum in AI-linked equities, history shows that crowded trades in hot sectors often lead to disappointing returns once reality catches up. Advisors can use this moment to educate clients about the difference between technological progress and investment opportunity. The former can be revolutionary without necessarily translating into outsized equity gains.
Arnott’s perspective also dovetails with a broader theme in portfolio management: the enduring value of diversification. With U.S. large-cap equities at historically expensive levels, expanding into smaller companies, undervalued styles, and international markets can reduce concentration risk while positioning portfolios for future mean reversion. For advisors, that means moving beyond the S&P 500 as the default equity anchor and instead considering more balanced global exposures.
The conversation around AI also provides an opportunity to revisit behavioral finance with clients. Many investors extrapolate recent trends and assume that past winners will continue to dominate indefinitely. Advisors can use Arnott’s observations to illustrate why such assumptions are dangerous, particularly in sectors characterized by rapid innovation and intense competition. Anchoring client expectations to realistic return assumptions, rather than headline narratives, will be critical in managing risk and sustaining trust.
At the same time, Arnott’s recognition of AI’s genuine capabilities reminds advisors not to dismiss the technology entirely. Tools like ChatGPT may indeed transform productivity, research, and even investment workflows. For RIAs, that suggests incorporating AI as a resource for improving practice management, client communication, and portfolio analysis, rather than simply as a theme for equity exposure. In other words, advisors may benefit more from using AI in their business than from overweighting it in client portfolios at current valuations.
Ultimately, Arnott’s framework points back to fundamentals: valuations matter, diversification protects, and hype cycles should be navigated with discipline. For wealth advisors and RIAs charged with stewarding client assets over decades, that means resisting the urge to chase what is popular and instead seeking opportunities where the market has over-discounted risk. Whether through small-cap value, emerging markets, or other undervalued segments, Arnott advocates for a contrarian, valuation-driven approach.
The broader lesson for fiduciaries is clear. AI is real, and it may reshape industries in profound ways, but that does not mean AI stocks will deliver sustained, above-market returns from today’s elevated levels. Advisors must distinguish between the promise of the technology and the price investors are paying for exposure. By grounding portfolio decisions in valuation discipline and thoughtful diversification, wealth managers can help clients avoid the pitfalls of speculation while still participating in the long-term benefits of innovation.
In today’s environment of frothy valuations, concentrated leadership, and uncertain earnings pathways, Arnott’s cautious optimism about select value opportunities offers a roadmap for advisors. It’s a reminder that the best opportunities often lie where few are looking, and that patient, valuation-conscious investing remains as critical as ever in achieving durable outcomes for clients.
