How to Capture AI Innovation in a Risk-Aware Equity Portfolio

May 20, 2024
5 min read

Technological disruption creates opportunity—and volatility. But there are ways to capture AI innovation while managing risk.

Companies at the heart of the AI revolution are widely seen as expensive, fast-growing businesses that wouldn’t usually be held in a defensive portfolio. Yet we think select firms within the AI ecosystem can fit into a risk-aware equity allocation that has an eye on quality sources of long-term growth and a thoughtful portfolio construction strategy. 

Investors seeking to reduce risk in equity allocations often lean into traditional defensive sectors, such as utilities or consumer staples. However, we think investors should cast a wider net to create an equity portfolio aimed at delivering more consistent return patterns through both down and up markets. Technology stocks can play an important role in that mix, so long as the portfolio manager focuses on companies with profitable, sustainable business models. 

The Market Dynamics of Transformational Technology

AI is perhaps the most transformational technology cycle since the birth of the internet. Yet we’re only in the initial phase of testing and experimenting with commercial applications. And it’s easy to lose sight of the technology sector’s breadth when the spotlight is on a narrow group of mega-cap stocks. 

The potential for AI to unlock efficiency across industries has triggered spectacular gains for the companies enabling the disruption. Since late 2022, when ChatGPT was launched, the Magnificent Seven stocks have dominated market returns because of their prominent role in developing the hardware and building the infrastructure for generative AI (GAI). As a result, some of these stocks now have high valuations and are vulnerable to volatility. The growth opportunities are real, but so are the risks—especially if you’re wary of expensive equity price tags. 

So is there a way to incorporate AI-driven stocks in an equity allocation focused on risk reduction? We think so. The key is to look for companies with high-quality business models, a degree of stability and relatively attractive valuations for the sector, even if they may be somewhat pricier than the broad market average. Like other companies in a defensive allocation, the AI businesses we favor have strong profitability, measured by return on assets (ROA) and return on invested capital, which are robust predictors of future earnings power. Capital discipline is another feature that can help support margins, particularly in a world of higher interest rates.

Guidelines for Sourcing AI-Driven Quality Growth 

With the following guidelines in mind, we believe investors can identify AI stocks with the right balance of features for a risk-focused allocation.

Learn lessons from past technology cycles—In the dot-com boom, innovation was led mostly by unprofitable companies with unproven business models targeting aggressive growth. This time, it’s very different. Many firms building AI infrastructure are profitable, and some top innovators offer quality businesses with a degree of stability—key components of a defensive equity allocation, in our view. That said, as AI progresses, exciting future innovations must be closely scrutinized. The dot-com bubble taught us that investors should not be blinded by promises of unproven new markets and must always make sure a pioneering product is backed by a credible business model. 

Distinguish among technology industries—Much of the AI-driven surge to date has been led by semiconductor manufacturers and cloud infrastructure providers. Software companies haven’t been at the forefront of the AI wave, but we think they’re poised to catch up (Display). As AI infrastructure proliferates, we believe software companies will play a bigger role in enabling efficiencies for consumers and companies. The significant investments we are seeing today in semiconductors and cloud infrastructure will only produce a reasonable return on investment if software companies are able to monetize GAI in the coming years. We believe this would drive an acceleration in revenue growth for the software industry, which could be a catalyst for software stocks to catch up with their semiconductor counterparts. Select software companies offer an appealing combination of defensiveness and growth for investors, and trade at relatively attractive valuations versus the AI hardware and infrastructure powerhouses.

Software Spending Poised to Catch Up in the Next Phase of AI Growth
Line chart shows the growth of generative AI spending on AI servers, infrastructure as a service and software, from 2020 projected through 2027.

Current analysis and forecasts do not guarantee future results.
As of March 31, 2024
Source: International Data Corporation and AllianceBernstein (AB)

Be Selective Within the Magnificent Seven—We believe the mega-caps should be subject to the same fundamental scrutiny as any other stock in a defensive portfolio: investors should focus on high-quality business models that provide the flexibility to navigate short-term market stresses and longer-term challenges. Microsoft’s cloud platform and relationship with GAI pioneer OpenAI underpin a quality business for the AI era. Alphabet’s strong innovation pedigree should help its digital advertising platform exploit advances in AI. That said, given the outsize weight of the Magnificent Seven in key US and global benchmarks, holding large positions in the entire cohort can be risky—especially if sentiment sours toward the group, as it did in 2022. In our view, portfolio positions should be calibrated to help ensure that a defensive strategy won’t be overly exposed to a potential downturn in the Magnificent Seven, while enabling a degree of upside capture when rising markets are driven by the mega-caps. 

How to Balance Quality, Stability and Price

Incorporating these principles into an equity portfolio isn’t easy. Our preferred recipe for risk reduction is to focus on quality companies with stable shares that trade at attractive prices, or what we call QSP. That formula is challenging to apply to technology companies because even outside the Magnificent Seven, valuations tend to be higher than the broad market. 

The solution to this conundrum is to balance QSP features, both when analyzing individual holdings and in portfolio construction. Some AI-focused technology companies offer exceptionally high quality, particularly in the software industry, where business models are built on recurring revenue streams that add stability to cash flows. High exposure to quality and stability characteristics can help offset some valuation risk. We also think investors should target shares of companies with relatively attractive valuations compared to the broader technology industry.

These features can also be balanced across a portfolio. In other words, with the right mix of holdings across sectors, relatively high valuations for some technology firms can be counterbalanced by especially cheap prices in other sectors. The result: an equity portfolio with an attractive blend of QSP features, sourced from diverse sectors and industries. By carefully selecting stocks of high-quality businesses that are participating in the AI revolution, investors can benefit from a once-in-a-generation technological shift without destabilizing the lower-risk profile of a broad equity allocation.

The views expressed herein do not constitute research, investment advice or trade recommendations and do not necessarily represent the views of all AB portfolio-management teams. Views are subject to revision over time.

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