Artificial Intelligence

• AI adoption is driving a clear divide between leaders and laggards among small and mid-cap Internet companies, with the market often mispricing where AI creates real operating leverage.
• The most compelling opportunities lie in “undervalued leaders” and “dark horses” (i.e., companies with strong or improving AI integration but low valuations).
• The PICO de Gallo framework helps investors separate signal from noise, identifying where AI is truly transforming products and margins versus where adoption is only surface level.

Summary

In this edition of the Focus On AI: AI Wars series, the report applies the PICO de Gallo framework to map AI-driven dislocations across the Internet SMid-cap sector. It finds that while some companies justify premium valuations due to deep AI integration and growth, others remain undervalued despite visible progress. The analysis suggests investors should look beyond obvious winners and focus on firms where AI adoption is quietly translating into operating leverage and future upside.

• AI’s exponential growth is now constrained by power availability, not hardware. Hyperscalers are racing to secure energy capacity, as grid limitations are the gating factor for scaling AI workloads and monetizing infrastructure.
• Energy procurement strategies are emerging as a key competitive moat. Companies with pre-secured grid access, renewable PPAs, and advanced storage solutions will capture early AI revenue, while others risk stranded investments and slower deployment.
• Efficiency improvements and next-gen baseload (nuclear, fusion, geothermal) are critical for long-term AI growth. While incremental gains help, transformative solutions are needed to sustain the pace of AI expansion and avoid bottlenecks

Summary

• AI’s rapid growth is now constrained by access to power, not hardware, as hyperscalers race to secure energy capacity and grid connections. The ability to procure reliable, affordable energy is emerging as a key competitive advantage, with early movers capturing the highest-value AI workloads and revenue. While incremental efficiency gains help, transformative solutions in energy supply and infrastructure are needed to sustain exponential AI expansion and avoid significant bottlenecks.

• Hyperscalers are positioned to dominate the AI landscape by controlling infrastructure, data, distribution, and monetization, rather than relying on first-mover advantage or model quality alone.
• OpenAI, despite early success and brand recognition, faces structural disadvantages due to its reliance on external infrastructure and limited platform control, making its lead less durable.
• The “5 Ds” framework is presented: Data, Distribution, Data Centers, Dollars, and Domination. This framework reveals that scale, integration, and platform ownership are the key drivers of long-term AI success.

Summary

• In this edition of the Focus On AI series, we analyze the competitive dynamics of the AI sector, emphasizing that the future of AI will be shaped by a handful of hyperscalers who own the full technology stack, from silicon and servers to user platforms and monetization channels. The report introduces the “5 Ds” framework to evaluate which companies are best positioned for AI dominance and have entrenched advantages in proprietary data, infrastructure, and user reach. The report also highlights the rise of Chinese foundation models and niche data platforms, but concludes that platform control and recurring revenue streams are the ultimate differentiators in the ongoing “AI Wars.”

• AI adoption in biotech is poised to dramatically accelerate drug discovery, development, and personalized medicine, with efficiencies and cost savings not yet reflected in company valuations.
• Regulatory bodies, especially the FDA, are increasingly supportive of AI integration throughout the drug lifecycle, providing a favorable backdrop for further innovation.
• Most AI applications are currently focused on drug discovery, but opportunities exist across the entire drug lifecycle, from target identification to commercialization.

Summary

• In this edition of the Focus On AI series, we explore how AI is reshaping the biotech sector. AI is enabling faster, more efficient drug discovery and development, with the potential to reduce timelines and costs significantly. Regulatory agencies, notably the FDA, are embracing AI, streamlining approval processes and encouraging early engagement from sponsors. While most current AI applications are concentrated in drug discovery, the technology’s reach is expanding across clinical trial design, personalized medicine, and commercialization. Substantial growth and cost-saving opportunities presented by AI are likely not yet fully captured in pharmaceutical company valuations, suggesting considerable upside potential as adoption accelerates.

• DeepSeek’s AI advancements are poised to disrupt multiple sectors by making high-performance AI models more accessible and cost-effective, with significant implications for data centers, hyperscalers, software, technology services, and power producers.
• Lower training and deployment costs for AI, driven by innovations like FP8 precision and Mixture of Experts architecture, could accelerate adoption and reshape investment strategies across the technology ecosystem.
• The evolving landscape raises new questions around intellectual property, regulatory oversight, and long-term infrastructure planning, especially as AI models become more specialized and business-focused.

Summary

• In this edition of the Focus On AI series, we examine the disruptive impact of DeepSeek’s R1 model and related AI innovations on the broader technology and infrastructure sectors. The analysis highlights how DeepSeek’s approach (leveraging cost-saving techniques and open-source models) has the potential to lower barriers to AI adoption, benefiting established players in data centers, cloud hyperscalers, and software firms. The report notes that while rapid advancements may temper some near-term growth narratives (such as electricity demand for data centers), the long-term outlook remains positive due to increased consumption and new business opportunities. However, the pace of change introduces complexity around regulatory requirements, intellectual property protection, and strategic investment, underscoring the need for careful planning and risk management as AI continues to evolve and proliferate across industries.

• AI adoption has the potential to be a positive catalyst for growth and profitability across P&C insurance and alternative lending
• A more cautious approach to AI adoption across banks could provide long-term upside opportunities

Summary

• In this edition of our Focus On AI series, we take an in-depth look at the impact of AI on the financial services sector. The banking, financial services, and insurance (BFSI) industry is unique in terms of the significant scale of expected investment in technology, disparate rates of adoption, and potential benefits across the sub-sectors. It has been suggested by some that the risks of underinvesting in AI outweigh any cost concerns tied to overinvestment. That said, we believe the situation for BFSI firms is far more complex given unique risks, regulatory oversight, and the need to protect against significant harm to stakeholders and shareholders alike.

• Generative AI-powered search is driving an explosion of interest in the search market
• Initiated coverage on Elastic NV a likely beneficiary of generative AI-powered search

Summary

• In this edition of our Focus On AI series, we touch on what we view as an emerging early-stage use case of generative AI in the enterprise: search. Our research suggests natural language search is a highly compelling starting point for generative AI adoption and is driving an explosion of interest in this market.

• AI is set to increase data center demand and, in turn, power demand
• Which companies will likely benefit most from AI-driven data center and power demand trends

Summary

• In this edition, we take an in-depth look at the impact of AI on data centers and power demand. At first glance, and despite the AI craze in recent months, the link between AI and the utilities sector may seem unclear. Yet, AI is having a broad effect on the world, and utilities are no exception. We argue that as AI applications evolve and become more sophisticated, the demand for computational power will increase, which will lead to increased demand for data centers worldwide and, in turn, fuel power demand.

• Investment summary
  
• AI adoption is a long-term benefit to database spend

Summary

• In this initiation of coverage report on MongoDB, Inc., we explore a key area of the AI transformation: the importance of data and the growing area of nonrelational databases. AI is set to absolutely rock our world, with data being the lifeblood of AI and database being the technological underlay. We argue that AI adoption will be a long-term benefit to database spend. Enterprises are developing new applications faster than ever, with data becoming increasingly important and scalability no longer limiting database sizes, and these trends will likely be supercharged by AI.

• The role of AI in the customer experience journey
  
• The evolution of industries with the advent of AI

Summary

• This report will explore the impact of AI on industries and businesses from a customer engagement standpoint, as we believe the Customer Experience segment will likely be one of the most disrupted by AI given the scope of automation in the business. We think it will be select customer-facing industries – Restaurants and Retail, Banking and Financial Services, Media and Entertainment, Transportation, Healthcare and Life Sciences, Telecommunications, Automotive, and Education – that will see imminent advancements in AI investments. Our discussions are informed by the AI-led business demand seen by Technology Services companies across our coverage, especially the customer experience and digital experience companies.