Why This Growth Stock Manager Likes Both the AI Trade and Eli Lilly

Key Takeaways

• AI is a major growth driver for stocks, but infrastructure bottlenecks could cut into cash flows for the largest companies, says Jennison’s Blair Boyer.
• Only about 20% of businesses use AI in any business function, so opportunities are still in its early innings, he says.
• Growing concentration in huge stocks has raised the importance of balancing with next-generation names.

It’s been a tricky year for growth stock investors and Big Tech. The group started 2026 on the defensive, as investors rotated out of names that had benefited from the massive AI buildout. But sentiment has again improved, as the wave of AI capex shows no signs of abating.

The rebound in growth stocks lifted the near-term fortunes of growth stalwarts like Silver medalist PGIM Jennison Growth Fund PJFZX, Bronze medalist PGIM Jennison Focused Growth ETF PJFG, and Silver medalist Harbor Long-Term Growers ETF WINN, all of which are run by investment manager Jennison, an investment unit of global asset manager PGIM.

The three funds favor businesses with strong market positions, healthy balance sheets and durable competitive advantages. They’re concentrated portfolios; PGIM Jennison Growth has 53 holdings and a turnover of 34%. Jennison has “shown over longer time periods that it can identify the next generation of growth leaders, and this strategy has enough talent behind it to outperform its peers over time,” writes Morningstar analyst Natalia Arrigoni.

We checked in with Blair Boyer, Jennison’s co-head of growth equity, about what lies ahead for the AI juggernauts and other growth companies. Boyer walked us through his theses on Eli Lilly LLY and Snowflake SNOW, and explained how he views Microsoft MSFT, Apple AAPL, and other key stocks.

Leslie Norton: What do you expect for growth stocks in the second half 2026?

Blair Boyer: Strong underlying corporate profits have been the rock that kept people in the market. Consensus operating earnings growth estimates for the S&P 500 are in the high-teens-to-low-20% range for 2026 and 13%-15% for 2027. These consensus numbers appear reasonable.

Higher market volatility is a fact of life at this point. The first quarter was more around geopolitics. Inflation has proved stickier than expected. Then there are severe physical and operational constraints facing the AI infrastructure buildout. According to reports, over half all global AI data center construction projects are facing cancellations or delays, including high-profile expansion plans of Oracle ORCL and OpenAI. While combined hyperscaler AI capex has surged past $700 billion for 2026, companies still can’t bring on capacity fast enough to meet demand. Amazon revised its 2026 capex guidance higher, but said it still will not meet this year’s demand.

Norton: What are you thinking about the returns on the capex binge?

Boyer: Consensus estimates for capital spending by the five largest hyperscalers—Amazon AMZN, Alphabet GOOG, Microsoft, Meta META, and Oracle—are approximately $1.0 trillion in 2027 and $1.3 trillion in 2028. Free cash flow may turn slightly negative in 2027 as they scale to meet accelerating demand. The substantial cash generation should support a durable, long-duration return opportunity for investors.

We already see early evidence of returns on AI-related capital spending, particularly among the hyperscalers. Our discussions with management teams suggest demand for AI compute could exceed available capacity for multiple years. That demand is appearing in the reacceleration of cloud revenue growth and margin contribution for Amazon, Microsoft, and Alphabet, and in the rapid annual recurring revenue growth of leading private frontier model companies such as OpenAI and Anthropic. Amazon is a good example. In the most recent quarter, AWS revenue growth accelerated to 37%, its fastest pace since 2021.

Despite above-market growth, many hyperscalers and other AI-infrastructure-focused companies are trading at P/E multiples in the 20 range or lower. The market is actively pricing in timing uncertainties, power grid limitations, and construction bottlenecks.

Norton: Are these benefits filtering through to non-tech companies?

Boyer: From the discussions we’ve had across businesses in many industries, broadly, AI is generating significant cost savings and helping businesses grow faster. I can tell you that at Jennison, making and synthesizing our financial modeling work would have taken weeks and months in the past. That now takes hours and days. AI is a transformational computing cycle with an opportunity set well beyond the technology sector.

We are still in the early stages of a multiyear adoption cycle. Commentary across a broad range of earnings conference calls suggests that only a small percentage of companies have identified concrete examples of AI improving current revenue growth. Most surveys indicate that only about 20% of businesses are using AI in any business function today.

Norton: Let’s have some examples.

Boyer: AI is being used in healthcare clinical trials, where the failure rate is nearly 90% and a huge drain on resources. Analyzing historical data allows companies to fail early and cheaply in the lab, rather than late and expensively in Phase III human trials. Pharmaceutical companies can drastically optimize R&D spending by eliminating placebo groups and reviving failed compounds. Eli Lilly has a $1 billion five-year joint venture with Nvidia NVDA to accelerate drug discovery and production through AI and robot-operated laboratory operations.

Walmart WMT is using AI and machine learning to improve purchasing, optimize what it has in stores, and optimize its third-party marketplace (a relatively new business). That flywheel is also creating an advertising stream that didn’t exist a year or two ago.

Norton: How are you navigating this heavily concentrated market, with your own heavily concentrated portfolio?

Boyer: We’ve been through an extraordinary 12-to-15-year period in which companies that were already at scale saw their growth accelerate. Twenty-five years ago, we probably owned 60-70 names. Today, we own 50-60, reflecting these larger companies. We make sure there’s diversification outside the top 10. Companies that are earlier in their growth trajectory make up 15%-25% of the portfolio. They have a high degree of organic growth as a backdrop to the revenue growth.

Norton: What are some next-generation names?

Boyer: Snowflake is an important player in data warehousing and data access. Crowdstrike CRWD sits in the internet security space. The proliferation of data and of AI makes security ever more important to C-suite executives. For infrastructure software, AI deployment increases the need for observability, orchestration, governance, security, and control across increasingly complex systems. The market decline [let us] take advantage of price pressures. We didn’t waver about the longer-term outlook for those businesses.

Norton: Let’s discuss Microsoft and Apple, which have faced different headwinds. They are in your top 10.

Boyer: Microsoft is uniquely positioned at the center of enterprise AI adoption. It can monetize AI through both subscription and consumption-based models. Continued Azure acceleration, increasing Copilot uptake, and ongoing cloud migration and digital transformation trends support our high conviction.

Microsoft is expected to deliver roughly 20% annual revenue growth—remarkable, given its size—while maintaining strong profitability and cash flow generation. The stock trades at approximately 20 times 2027 earnings. That’s compelling for a business with competitive advantages, an expanding AI opportunity, and a long runway for sustained growth.

Apple AAPL has an unmatched installed base, a powerful brand, and the ability to monetize one of the largest and most loyal global customer ecosystems. The slowdown in its growth rate is driven by temporary headwinds including supply constraints, component inflation, and near-term services softness rather than deterioration in competitive position.

Norton: What’s the thesis for Eli Lilly, one of your largest positions?

Boyer: It was founded on diabetes treatment. Blockbuster tirzepatide therapies such as Mounjaro and Zepbound continue to gain share globally and drive exceptional revenue and earnings growth. Large pharmaceutical companies haven’t historically grown at high rates for a maintainable period. A year ago, they were expanding capacity, and much like with hyperscalers, [growth] wasn’t all linear. There were concerns around pricing. Some of that weakness allowed us to increase our position size. Part of what expands the market here is ever lower prices. There’s a really broad opportunity set ahead.

Lilly can deliver sustained above-market earnings growth. That’s supported by durable competitive advantages in obesity and diabetes, continued international expansion, and a robust pipeline. In June, Lilly presented data for its next-gen obesity treatment showing a very clean safety and tolerability profile, making it more suitable for indefinite use than even tirzepatide.