Post-DeepSeek AI Plays In Public Markets
Welcome to the era of AI application
With Claude 3.7 Sonnet and Grok-3 making waves and a steady drumbeat of new technical and open source breakthroughs — from long-term memory in AI agents to new voice assistants and model capabilities in reasoning and video — every day seems to bring a new breakthrough in AI.
Coupled with DeepSeek’s market-moving debut a few weeks ago, all of this momentum is starting to translate into enterprise adoption as state-of-the-art AI is more affordable and easier to deploy at scale. With potential for productivity growth in everything from medical research to voice assistants in customer service, early movers are already seeing results in terms of higher gross profit and growth.
But which companies in the public markets are truly enabling and embracing modern AI systems? Cutting through the hype to identify these organizations is a key part of why we created the 📈 AI Index 📈, which uses a fine-tuned LLM to analyze earnings and regulatory filings as well as data from a variety of sources to determine levels of AI activity, research and hiring.
Until recently, much AI investment has been heavily concentrated in a handful of mega-cap stocks surrounding NVIDIA, major chipmakers and the Magnificent Seven.
But a shift is happening, one that the market may have actually been pointing to for a while. Separating out major chipmakers from AI application stocks (or companies more focused on enabling or applying AI in specific industries, from advertising to commerce to vertical applications and marketplaces), the AI Index points to a growing divergence between these two baskets starting from the latter half of 2024.
Call it the era of the AI application. As the overhead layer — chips, cloud, data centers — and middle layer of foundation models get played out, there are still many opportunities in specific industry applications closer to the consumer. Here are a few industries and companies from the AI Index in a good position to thrive in an era of open, affordable AI.
Ecommerce
AI can improve personalization, pricing, UX, customer service and more in ecommerce — ultimately translating into better customer engagement and loyalty while at the same time reducing operational costs. Two companies in the AI Index deploying AI across a raft of use cases are eBay and Etsy.
eBay inc. (NASDAQ: “EBAY”)
eBay is growing its e-commerce platform and services with advancements through AI integrations. The company is focusing on AI-powered search and personalization tools, specifically image-based searches and customized UX. For sellers, eBay AI powers tools like Magic Listing — which helps automate listing creation — and pricing optimization algorithms. In customer service, AI is being used to improve response times and resolution rates. OpenAI’s recent Operator AI Agent model is also set to integrate with eBay in a joint collaboration effort to broaden the reach of sellers and enhance the shopping experience.
These initiatives are likely contributing to eBay’s strong financial performance, with Q3 2024 revenue growing 3% year-over-year to $2.6 billion and gross profit margins reaching 70% — reflecting robust profitability and operational efficiency.
Etsy, inc. (NASDAQ: “ETSY”)
With a nearly decade-long track record of deploying AI, Etsy seems well-positioned to be a winner in the long run despite its current underperformance. Etsy AI is everywhere, from AI-powered search to personalized recommendations to the generative AI-based Gift Mode, which tailors gift suggestions. AI is also used for operational efficiencies at Etsy like optimizing shipping routes, accurately predicting delivery times and improving trust and safety by flagging policy violations.
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Recent Q4 2024 revenue reached a record $852.2 million, up 1.2% from 2023 Q4. Etsy’s net income surged 56% year-over-year to $129.9 million. Recent underperformance in its stock is partially explained by the lower gross merchandise sales in 2024. However, with a robust AI-driven strategy and continued growth, Etsy may present a rare opportunity to buy an AI innovator amid a dip.
Data Analytics
AI is improving data analytics with quicker and useful insights in industries like healthcare, finance, and manufacturing. Demand for efficient analytics platforms that integrate data and traditional models with agentic workflows and other gen-AI capabilities are mission-critical in certain industries. This positions companies such as Altair and Palantir for continued growth.
Altair Engineering inc. (NASDAQ: “ALTR”)
Within its Data/Analytics and AI segment, Altair recently announced several major initiatives. By enriching its HPCWorks platform with AI-driven job scheduling, high-level monitoring, and cloud scaling, the company improved resource allocation and workflow management. Altair also acquired Cambridge Semantics last year, bringing knowledge graph technology to its RapidMiner platform to reinforce data analytics and generative AI solutions.
These innovations contributed to strong financial performance, with Q4 2024 revenue growing 12% year-over-year to $192.6 million and software revenue growing 15% to $179 million and now accounting for 93% of total revenue.
IQVIA (NYSE: “IQV”)
IQVIA’s use of AI spans the clinical development processes in areas like study design, site identification, patient recruitment, pharma-covigilance and clinical monitoring. The company recently announced that it will combine IQVIA’s unparalleled information assets, analytics, and domain expertise — known as IQVIA Connected Intelligence™ — with the NVIDIA AI Foundry to build custom foundation models and agentic AI workflows to accelerate research and clinical development.
Although the drug development space is ripe for AI-powered disruption in general and IQVIA’s performance over the past several years is mixed, the company’s growth and recent initiatives to harness generative AI might merit a fresh look. In the third quarter of 2024, IQVIA’s revenue grew 4.3% year-over-year to $3,896 million — with the Technology & Analytics Solutions (TAS) segment growing 8.6% to $1,554 million and now accounting for approximately 40% of total revenue.
Financial Services
Financial services firms have long been early adopters of traditional machine learning in areas like risk assessment, fraud detection and personalized banking. Multi-agent systems for research, voice assistants and other bespoke LLM applications are poised to further enhance efficiency and improve customer experiences.
Upstart Holdings, inc. (NASDAQ: “UPST”)
Upstart focuses on its lending platform and services, employing AI to improve efficiency. The company introduced Model 18 (M18) in August, an advanced credit pricing model that integrates APR as a key feature and generates about one million predictions for each applicant, six times more than its previous model. Upstart also launched T-Prime, an AI-powered lending program targeting borrowers with credit scores above 720, enabling lenders to offer competitive rates with instant and automated approvals.
The company’s AI models now analyze over 2,500 variables, up from just 23 in 2014, and are trained on nearly 82 million repayment events. Upstart also introduced AI-powered tools for auto financing, including a redesigned layout and a new credit dashboard offering deeper credit insights. These innovations coincide with strong financial results in Q4 2024, with revenue growing 56% year-over-year to $219 million and origination volume increasing 68% to $2.1 billion.
Intapp, inc. (NASDAQ: “INTA”)
Intapp is making strides in the Data/Analytics and AI space through several key initiatives. The company recently launched Intapp Assist for DealCloud, which incorporates generative AI to help professionals analyze data quickly, make informed decisions and automate workflows. Intapp also introduced Intapp Data, an AI-powered firmographic dataset covering over 85 million companies and 200 million contacts, enhancing market intelligence for clients.
The acquisition of delphai, an AI software company specializing in firmographic data automation, further strengthens Intapp’s AI capabilities and data strategy. Intapp also recently introduced Intapp Walls for Copilot, designed to centralize confidentiality control and secure sensitive information across systems. Based on the recent Q2 fiscal year 2025 financials, total revenue grew 17% year-over-year to $121 million and SaaS and support revenue 27% to $80 million. Cloud ARR grew by 29% year-over-year to $311.1 million, now representing 76% of total ARR.
Takeaways
In a post-DeepSeek environment where open models are performant and inference costs continue to decline, a race to adoption is underway in every industry. By discerning value from the noise, investors can find opportunities where AI integration is driving significant improvements in operational efficiency and profitability outside of traditional chipmakers or hyperscalers.
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👏 Our thanks to Navein Suresh on this piece.
