Artificial intelligence (AI) could prove to be a huge long-term growth tailwind for Eli Lilly (LLY), as it’s transforming the company’s multi-decade trajectory. AI is changing how the company discovers, develops, and brings new drugs to market. Rather than simply accelerating existing research, AI is helping transform Lilly from a traditional drugmaker into a more scalable, AI-powered engineering platform.
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High conviction NVDA bears now have this Tradr ETFWhile the stock’s spectacular run over the past 12 months could raise the question of whether it is now overvalued, looking only at trailing multiples overlooks the massive AI-driven shift underway. For this reason, I am bullish on the stock even if it seems somewhat expensive on the surface.
The $1B Nvidia “Physical AI” Lab and 24/7 Agentic Workflows
The $1 billion Nvidia (NVDA) “Physical AI” lab and 24/7 agentic workflows reflect one of the most significant catalysts in the ongoing shift in Eli Lilly’s infrastructure, in my view. There are still investors who think that AI in pharma is just a software tool for scanning legacy databases. That totally overlooks Lilly’s core capital allocation strategy. The company is co-locating internal drug hunters with world-class Nvidia engineers inside their newly launched South San Francisco co-innovation lab. So it is essentially treating high-performance compute as a core physical asset, directly bridging silicon and wet biology.
This project runs on Nvidia’s next-gen Vera Rubin architecture and utilizes the specialized BioNeMo platform. Thus, it establishes a 24/7 continuous learning loop between Lilly’s automated, “agentic” wet labs and computational dry labs. I find it interesting that Lilly is deploying “Physical AI” and digital twins via Nvidia Omniverse to virtually stress-test manufacturing lines and to fully automate the synthesis of physical molecules. This closed-loop automated architecture turns physical laboratory trial data directly into real-time computational models.
Now, I think it’s healthy to question whether this is just an abstract experiment to generate headlines. I genuinely believe it is a real attempt to convert drug-making from an artisanal, trial-and-error process into a predictable engineering workflow. Also, note that this strategy targets a strong reduction in early-stage capital expenditure and pipeline cycle times. Eliminating multi-million-dollar clinical dead ends before physical compounds are ever mixed structurally shifts standard R&D cost assumptions, creating a massive long-term operating cushion.
De-Risking the Pipeline via Insilico’s $2.75B Generative AI Engine
In the meantime, Eli Lilly is de-risking the pipeline via Insilico’s $2.75 billion generative AI engine. I believe this shows how Lilly is aggressively acquiring externally validated, machine-developed clinical assets alongside its internal infrastructure upgrades. The Nvidia joint venture drives internal data processing capabilities. However, this massive external licensing agreement brings immediate, high-probability programmatic upside. The deal grants Lilly exclusive global rights to develop and commercialize preclinical oral therapeutics discovered via Insilico’s automated chemistry engine, known as Pharma.AI.
The thesis here centers on clinical success rates. If you follow the industry, you know these have historically been the industry’s largest cash sink. Typically, only about 52% of traditional molecules survive standard Phase I safety trials due to unforeseen toxicities. However, early data on AI-generated compounds show a staggering 80%–90% Phase I pass rate because predictive machine learning models excel at identifying cellular toxicity in silico before a compound ever enters a human subject.
Lilly is onboarding molecules that can compress the standard six-year preclinical timeline down to just 30 months. As a result, Lilly is building a solid pipeline of oral small molecules. I feel this strategy protects its long-term terminal value long before its current injectable glucagon-like peptide-1 (GLP-1) cash cows face their first structural patent cliffs. So if you are willing to be patient with the stock and have a long-term view, this external platform pipeline directly hedges terminal value risks.
The Valuation Reality and Strong Upside Potential
Considering the stock’s prolonged rally over the past year, it’s fair to question whether LLY stock has more upside ahead. I believe it does, as the company’s real earnings growth potential remains incredibly strong. Driven by insatiable global consumer demand for Mounjaro and Zepbound and aggressive manufacturing scale-ups and footprint expansion, LLY is expected to end the year with $36.21 in earnings per share (EPS). This implies a year-over-year growth of almost 50%.
Looking forward to FY2027, consensus EPS estimates already price in 23% EPS growth, as international rollouts expand and persistent supply constraints ease. A P/E of 33x on the 2026 EPS estimate and 27x on the 2027 EPS estimate feels entirely fair, given that this is an undisputed market leader set to sustain excellent growth for years to come, with a strong AI tailwind at its back. The premium valuation multiple is completely justified when execution is this visible and structural.
Is LLY a Buy, Sell, or Hold?
Eli Lilly features a Strong Buy consensus rating on Wall Street, based on 20 Buy and two Hold ratings. No analyst rates the stock a Sell. Moreover, LLY’s average price target of $1,290.79 implies about 8.31% upside over the next 12 months.
Conclusion
I believe Eli Lilly is moving away from the unpredictability of traditional pharma and toward a more scalable biotech platform. By using advanced physical and generative AI tools, the company is reducing risk in its clinical pipeline. Over time, this could make the long-term investment case much stronger for patient investors.