Commentary: Large Cap Growth ESG Strategy

• The Strategy outperformed due to a combination of active management of our mega cap exposure as well as strong stock selection across industrials and similar early-cycle companies.
• ClearBridge is closely watching sustainability-related opportunities presented by artificial intelligence as well as its energy intensity and social dimensions as the phenomenon plays out in our companies across sectors.
• Preparing for a range of outcomes is our rationale for diversifying across the growth buckets. As the economy straddles a potential recession or uptick in inflation, we want to own companies with different drivers that are able to perform through varying market conditions.

The positive momentum of 2023 extended into the first quarter as a likely economic soft landing and being past the peak of monetary tightening sent stocks broadly higher. The S&P 500 Index advanced 10.56% for its best start since 2019, boosted by solid corporate earnings and continued enthusiasm for generative artificial intelligence (AI). While the market showed some signs of broadening, mega cap growth stocks maintained their leadership with the Russell Top 200 Growth Index (11.70%) being the best performing segment for the quarter.

The likelihood of slowing economic growth and a more palatable rate environment going forward enabled growth stocks to maintain a premium over value stocks, with the benchmark Russell 1000 Growth Index rising 11.41% and outperforming the Russell 1000 Value Index by 242 basis points. Communication services (+17.34%) and information technology (IT, +12.68%) continued to outperform the benchmark, but more encouraging was greater participation in the quarter among utilities (+24.11%), materials (+13.56%), health care (+11.68%) and financials (+11.28%) stocks. While market performance remained top heavy, divergence began to emerge among the Magnificent Seven (Alphabet, Amazon.com, Apple, Meta Platforms, Microsoft, Nvidia and Tesla), a basket of mega cap growth stocks that led the concentrated equity rally in 2023. The group constitutes 48% of the Russell 1000 Growth Index while the ClearBridge Large Cap Growth ESG Strategy maintains exposure in the mid 30 percent range. This underweight enables us to own good businesses outside the group, like electrical components maker Eaton, and maintain a portfolio diversified across the select, stable and cyclical growth companies we target.

The Strategy outperformed its benchmark in the quarter due to a combination of active management of our mega cap exposure as well as strong stock selection across the rest of our growth universe. We tactically trimmed our overweight positions in all three to manage position sizing and fund opportunities in more attractively priced areas of the portfolio. We maintain exposure to six of the Magnificent Seven, with overweights in Nvidia, Meta and Amazon.com, which outperformed for the quarter. The Strategy is underweight Microsoft, Apple and Tesla, with the latter two suffering losses for the first three months of the year.

Exhibit 1: Actively Managing for Greater Market Participation

Complementing those stocks, the Strategy delivered solid results across our industrials holdings as well as cyclical names in the consumer staples and semiconductor areas. We are encouraged that outperformance has continued in step with increased participation across the market from the October lows. The likelihood of a soft landing, rather than a recession, has supported several early-cycle names, including mass market retailer Target and semiconductor equipment maker ASML.

Given our view that the overall market looks expensive, mostly due to mega cap valuations, the low likelihood that technology can continue to deliver well above market returns and an expected slowdown in economic growth, risk management has guided our recent positioning activity. We have been consistently trimming from the select bucket and redeploying into undervalued stable and cyclical names, while also being cognizant of position sizing to maintain the latitude to add to names when prices become attractive.

During the first quarter, we sold our remaining position in data monitoring software maker Splunk ahead of its acquisition by Cisco Systems. We continued to trim other IT stocks into strength to manage risk while also adding to high-conviction positions. For example, we trimmed our active weight in Palo Alto Networks after the information security software maker lowered its guidance in part due to a new emphasis on providing short-term discounts on product bundles to pursue its consolidation opportunity more aggressively. While this strategy should position the company more strongly in the future, it potentially increases volatility in operating results in the near-to-medium term. Part of the proceeds were redeployed into enterprise resource planning and finance software maker Workday, as we believe its products are well-positioned for consistent, robust subscription growth with potentially further upside as new investment initiatives scale.

We were also active in adding to stable bucket investments PayPal and UnitedHealth Group where negative near-term sentiment led to more attractive risk/reward profiles. We added to electronic payments provider PayPal as we have growing confidence that new CEO Alex Chriss’s strategic focus areas can improve the company’s performance, particularly in the key branded business. We added to our UnitedHealth position after shares were pressured due to fears over competition among managed care providers and rising medical loss ratios in the industry. We believe the company will be able to “re-price” for higher medical costs, making this pressure transitory and we see competitive concerns as overblown.

Stocks have been discounting a slowing economy with no recession but inclusive of rate cuts. We believe this has been the driver of momentum over the last year and that the market has downplayed fundamentals in the hopes of easier financial conditions in the future. If the economy dampens but avoids a recession, we should start to see early cyclicals work. Typically that would include industrials, semiconductors and consumer discretionary. The Philadelphia Semiconductor Index has already seen a nice move (up 64.9% in 2023), so we do not expect to see the same early cyclical recovery in that area. However, we would expect to see improvement in industrials and retailers. This was part of the motivation for our purchases of Target and Union Pacific last year, which should benefit as investors start looking toward the end of a slowdown.

If the economy is in a higher-for-longer rates scenario, we believe there may be more risk in the most expensive names in the market. While we do own some of those companies in the portfolio, we have been trimming them in favor of more reasonably priced growth businesses with good cash flow support for more restrictive conditions. In a higher-rate environment, companies with lower free cash flow yields are likely to see less multiple compression.

One of our larger macro concerns is the cadence of rate cuts the market is pricing in. The Fed doesn’t want to be wrong and have to reverse course with rate cuts if one (or both) of the pillars of its dual mandate of price stability and unemployment remain stubborn. Many components of input costs are now reversing higher after a prior decline, including crude oil, materials, industrial metals and agriculture. In addition, unemployment remains very low and labor costs elevated. The questions we now face are whether the neutral rate is higher than 2% and inflation structurally higher than in decades past, but we are certain it will take some time to settle this debate.

Preparing for a range of outcomes is our rationale for diversifying across the growth buckets. Beyond broader sector exposure, we want to own companies with different drivers that are able to perform in different kinds of markets. Areas we have been populating on our whiteboard include consumer discretionary and health care, as well as financials names with good free cash flow support.

The ClearBridge Large Cap Growth Strategy outperformed its benchmark in the first quarter. On an absolute basis, the Strategy posted gains across all 10 sectors in which it was invested (out of 11 sectors total). The primary contributors to performance were the IT and communication services sectors.

Relative to the benchmark, overall stock selection contributed to performance. In particular, positive stock selection in the communication services, IT, industrials and consumer discretionary sectors and an underweight to consumer discretionary drove results. Conversely, stock selection in the health care and financials sectors detracted from performance.

On an individual stock basis, the leading absolute contributors were positions in Nvidia, Meta Platforms, Amazon.com, Microsoft and Netflix. The primary detractors were Apple, Adobe, Tesla, Atlassian and Zoetis.

Artificial intelligence (AI) is transforming the investment landscape, and while its rapid development sparks some valid social and environmental caution, it also brings with it enormous potential for helping sustainability goals, with better data to improve energy efficiency, optimize renewable energy, make agriculture more sustainable and improve human health. ClearBridge is closely watching these opportunities even while we observe AI’s energy intensity and social dimensions as the phenomenon plays out in our portfolio companies across sectors.

On the regulatory front, the world’s first comprehensive AI law, the EU’s AI Act (AIA), will come into force later in 2024. The AIA classifies AI systems according to the risk they pose to users: there is unacceptable risk (such as emotion recognition in schools and workplaces), high risk (such as critical infrastructure and medical devices), limited risk (such as chatbots, which carry the risk of manipulation or deceit) and minimal risk (such as spam filters). Each level of risk is subject to different requirements, and there are heavy fines at the company level for noncompliance. President Biden also issued an executive order on safe, secure and trustworthy AI in October 2023, aimed at establishing standards for AI safety and security, protecting privacy, equity and civil rights, and supporting consumers and workers.

On the labor front, AI can boost productivity, but automation has always threatened labor disruption, potentially deepening global inequalities as AI growth may favor advanced economies with sufficient infrastructure and skilled workforces (Exhibit 2). Hiring algorithms may also rely on and perpetuate race and gender biases. Almost 40% of global employment is exposed to AI.¹

Exhibit 2: Employment Shares by AI Exposure and Complementarity

With looming questions of misinformation and digital safety, cybersecurity, and even human capital management, as hiring for AI ethics jobs is picking up,² it is clear that as AI develops and hits multiple inflection points over the next few years, companies across ClearBridge portfolios will need to negotiate a variety of sustainability-related AI opportunities and risks.

AI and Power Demand Implications

AI is energy intensive, with data centers running the large language models requiring significant electricity and complicating the already complex power supply and demand picture of the energy transition. Overall estimates for data-center-driven U.S. power demand growth vary, but they generally forecast the electric load to roughly double by the end of this decade (from the current 3%–4% to ~8% by 2030).

On the surface, this kind of demand growth should cause generation shortages on the grid, especially in places where the data centers have been expanding rapidly such as Virginia and California.

Factors that could mitigate projected power shortages in the future would be:

• Continued improvement in technologies/efficiency of the data centers
• Expansion of the data center locations toward less congested grids
• An increase in utilization of the existent gas generation capacity and even delays in the scheduled coal plant retirements, which would increase the emissions intensity from AI

Another important mitigating factor over the next five years will be faster development of renewable power sources, as many data center hyperscalers have public commitments to carbon free energy. The renewable projects’ shorter development/construction timeline and locational flexibility to satisfy the data center demand should push demand for renewables higher and improve the renewable projects’ returns. Renewable developers such as NextEra Energy and AES should be beneficiaries of these trends. As highlighted at NextEra’s recent renewable-focused investor day, current forecasts call for renewable capacity to reach between 375 GW and 450 GW over the next seven years (2024-2030). This implies a 13% compound annual growth rate through the end of this decade and suggests a rapid acceleration in renewable development (235 GW of renewables were added over the last 30 years). According to the company, this anticipated power demand acceleration is expected to be driven by consumption growth from data centers (+108%), oil and gas industry (+56%) and chemicals (+14%) between 2025 and 2030.

"Faster development of renewable power sources will be a key mitigating factor in power demand shortages as AI data centers consume more power." 

Over the long term, data center power consumption growth and companies’ green targets should advance the development and utilization of more effective power storage and carbon capture and storage technologies as well as green baseload power solutions, such as green hydrogen and small modular nuclear reactors.

From the regulated utilities’ perspective, the ultimate impact of the data center demand growth will vary by region, but the overall implications for the sector should be positive. Data center additions to regional grids will not only drive incremental investments into the local transmission and distribution systems, but in some cases result in incremental generation needs. In the near-term, utilities located in the territories with planned data center expansions, such as Dominion Energy, Southern Company, Sempra and CenterPoint Energy, should benefit from higher required investments into the grid to accommodate additional demand.

AI Impact on Labor Conditions

Prior waves of technology dating back to the 19th century have changed the fabric of the global workforce. AI is similar but potentially more impactful in that it might affect white collar jobs just as much as it does blue collar labor. The power of generative AI (Gen AI) over prior AI advances is its ability to generate creative output. However, most companies are using Gen AI to augment their employees’ capabilities, rather than seeking to replace them. In ClearBridge engagements with technology companies using newly released code generation tools, we find they generally use them to speed up the first draft of a software engineer’s code output. This frees up the engineer to focus on larger problems such as user experience and system design. The risk of AI causing mass unemployment is therefore overstated, while the need to upskill and reskill today's workforce is likely understated. By 2030, management consulting firm McKinsey estimates that as many as 375 million workers or roughly 14% of the global workforce might need to switch occupational categories and acquire new skills.³ Just as prior waves of innovation did, the AI wave promises to create demand for new skills around model training, prompt engineering and data science.

While AI can often outperform human counterparts on a growing range of tasks, it lacks human intuition, context awareness and ethical judgment. Recognizing these limitations will help companies use AI more effectively and responsibly. When deploying AI to generate content, the primary ethical considerations are around protection of intellectual property rights and avoidance of unintended bias. Google’s missteps with Gemini are a recent lesson on how difficult it is to tune an AI system to account for biases and ambiguity. However, Alphabet, Meta and Amazon are also taking the challenge seriously and stepping up their investment in AI ethics and safety. Meta currently has around 40,000 people working on safety and security, with more than $20 billion invested in teams and technology in this area since 2016. Google’s Vertex AI platform provides a suite of tools that cater to the entire AI lifecycle, from data preparation to model deployment and monitoring. By integrating robust security measures, promoting transparency through explainable AI and adhering to stringent ethical guidelines, Vertex AI empowers businesses of all sizes to develop and deploy AI solutions with confidence.

Misinformation and Social Manipulation

AI and Gen AI in particular make it much easier for bad actors to spread misinformation. We have already seen AI being used to impersonate individuals, including the two leading candidates for the U.S. presidential election in 2024. Meta and Google are working to thwart the misuse of AI-generated content on their respective platforms. In August 2023, Google debuted a watermark software for AI content, letting the user know that the content is AI generated. Meta meanwhile ensures its AI-generated content is labeled “imagined with AI” and is expanding this feature to include content created by third-party tools. The company is also focused on election transparency, namely serving over 500 million notifications on its apps since 2020 informing users how and when to vote, and building an industry-leading library of political ads that is publicly available and elucidates the entity funding each ad and who they are targeting. Given how quickly the tools are evolving, including high-quality AI-generated video in the near future, this remains an open area of both risk and opportunity for the world’s leading digital media platforms.

AI’s Potential in Health Care

The growth and increasing complexity of data in health care also makes AI potentially transformative in the sector. In drug discovery and development, for example, some companies are successfully using AI to create and optimize molecules to go into development, largely with applications in chemistry and protein engineering. Some companies are hoping to use AI to pick better targets for dugs, although we are skeptical about the near-term prospects, as the complexity of biology may pose a challenge for current AI models. Other companies are hoping to use AI and advanced computer models to better design clinical trials, although these attempts are in the very early stages.

"Most companies are using Gen AI to augment their employees’ capabilities, rather than seeking to replace them." 

There is also significant potential for AI in the field of diagnostics, both traditional testing and advanced genetic tests. For traditional methods of diagnosis, like blood/serum based tests and images such as X-rays, CTs and MRIs, AI should be useful for prescreening, enhancing or even replacing human reading of test results. AI models have already been used to develop tests looking for patterns of genes that indicate cancers or the prognosis for cancer.

Along these lines, Hologic, a medical technology company focused on women’s health and the leading manufacturer of mammography machines, is incorporating AI in its breast imaging business to assist radiologists in locating possible breast cancer lesions. Siemens Healthineers, one of the leading manufacturers of CT and MRI machines, is also incorporating AI into its imaging platforms, which provide automatic post-processing of imaging datasets through AI-powered algorithms in order to reduce basic repetitive tasks and increase diagnostic precision when interpreting medical images. The company is the global leader in AI patent applications in health care.

Conclusion

The rapid ascension of large-language model AI in 2023 has made the technology relevant to companies’ futures in nearly every sector. It will be important for AI to be firmly tied to sustainable futures, and we will continue to monitor how ClearBridge portfolio companies and the market at large are navigating AI’s sustainability-related opportunities and risks.