Citi’s 2026 Global TMT Conference Preview

A new Citi Research report from a team led by Global Head of Technology & Communications Research Heath Terry outlines key themes to be explored at our flagship Global TMT Conference, held Sept. 8-10 in New York City and featuring more than 250 management teams alongside Citi Research analysts.

Broadening Enterprise AI Adoption Drives Infrastructure Demand

The most important question for the artificial intelligence (AI) ecosystem remains straightforward: How quickly will businesses adopt AI at scale? The answer will shape demand for computing infrastructure, data centers, networking equipment, software, and many of the companies participating across the broader technology landscape.

Our conversations with technology leaders, along with corporate earnings commentary and recent surveys, continue to point toward accelerating adoption. One of the clearest signs is the rapid growth in orders placed with hyperscalers. Combined backlog among these companies reached approximately $1.7 trillion at the end of the second quarter, up 151% from a year earlier. That suggests customers are committing to significant future spending as they prepare to deploy AI more broadly.

At the same time, the AI market is evolving. While access to the most advanced chips remains constrained and some next-generation AI models have been slower to reach the market, the growing use of open-weight models has expanded the range of options available to enterprises. Rather than viewing open and proprietary models as direct competitors in a winner-take-all market, we see room for multiple approaches to succeed.

A key reason is improving economics. New chip architectures are increasing the amount of AI work that can be processed in a given period of time, while advances in software allow organizations to route tasks to the most appropriate model. Together, these improvements reduce the cost of completing AI tasks. As costs fall, businesses are likely to expand the number and variety of applications they deploy, increasing overall demand rather than simply shifting it from one provider to another.

This dynamic could support a more diverse AI ecosystem that includes leading frontier-model developers, providers of smaller specialized models, and organizations that customize models for specific business needs. Lower costs can expand the market by making AI practical for a wider set of use cases across industries.

Supporting this growth will require enormous investment in physical infrastructure. We project global AI-related capex to grow to $3.8 trillion by 2030, from $1 trillion this year. Large financing partnerships are increasingly emerging to help fund these projects, reflecting confidence in the long-term demand outlook.

The scale of planned construction is equally notable. New AI-related power capacity is expected to reach 19 gigawatts in 2026, 29 gigawatts in 2027, and 45 gigawatts in 2028. Even with challenges such as limited power availability, shortages of skilled workers, and regulatory hurdles, companies continue to invest aggressively because demand remains strong.

Importantly, these investments are producing attractive economic returns. Hyperscalers are generating cash returns of roughly 30% on invested capital from their infrastructure spending. That profitability helps justify continued expansion and reinforces the connection between AI demand and infrastructure investment.

During the conference, we will be looking for further evidence that enterprise adoption is accelerating. Areas of focus include actual AI spending levels, customer usage rates, measurable business benefits, and signs of how companies are allocating IT budgets for 2027. We will also monitor trends such as growing use of AI agents, adoption of open models, and decisions about whether AI workloads run in public cloud environments, private facilities, or hybrid configurations.

The overall picture continues to suggest that enterprise AI adoption remains in its early stages. Many large organizations are currently allocating only a small portion of technology budgets to AI initiatives, while a smaller group of leading adopters has already committed substantially larger shares. That gap implies significant room for future spending growth if AI projects continue delivering measurable returns.

Across the technology supply chain, this demand is likely to benefit chip makers, networking providers, data-center operators, hardware suppliers, enterprise-software companies and communications-infrastructure providers. It also helps explain why investors remain focused on the durability of AI spending and the pace at which businesses move from experimentation to broad deployment.

Diffusion of AI in the Enterprise

A major focus across software companies is whether AI is moving beyond pilot projects and becoming embedded in everyday business operations. Investors increasingly want proof that AI is driving customer adoption, revenue growth, workflow expansion, and measurable business outcomes. The key debate is no longer whether companies will spend on AI, but which vendors will capture that spending and establish durable competitive advantages. Conference discussions are likely to center on evidence of production deployments, successful monetization, and whether agentic AI strengthens established software platforms or lowers barriers to entry for new competitors.

Edge Computing and Physical AI

Another important debate concerns where AI processing should occur. Supporters of on-device AI argue that on-device processing offers lower latency, better privacy, lower inference costs, and offline functionality. Others maintain that the most advanced AI systems still depend on the scale and computing power of large data centers. Meanwhile, growing AI demand is pressuring supplies of key components and increasing costs for device manufacturers. Beyond personal computers and smartphones, AI is creating opportunities in robotics, autonomous systems, and intelligent machines, which require advanced computing, sensing, connectivity, and power-management technologies.

Online Advertising

Digital advertising performed well during the second quarter, particularly in the U.S., and attention will focus on whether that strength will continue in 2026’s second half. AI is increasingly influencing how consumers discover information online, how marketers measure performance, and how advertising platforms generate revenue. As search experiences evolve from lists of links toward AI-generated answers, companies will be watching closely for changes in web traffic patterns, consumer behavior, and marketing effectiveness.

Internet Usage Trends and the Rise of Agentic Commerce

AI-powered search and digital assistants are beginning to reshape how people find products, travel services, applications, and online content. Traditional search-engine optimization appears to be becoming less influential as users increasingly interact with AI-driven answer engines. Companies with strong brands, large audiences, and personalized user experiences may be particularly well positioned as internet traffic patterns continue to evolve and businesses experiment with new ways of reaching customers.

Communications-Services Concerns

Within communications services, competition in wireless markets has stabilized, but investors are increasingly focused on whether satellite-based connectivity could become a more significant competitive force over time. Discussions will also examine broadband pricing, industry consolidation, fiber-network demand, and the potential impact of AI on communications infrastructure. Growing AI workloads could significantly increase demand for high-capacity fiber connections linking data centers and enterprise networks, while AI tools may also help communications providers improve efficiency across customer service, network operations, and business processes.

The Regulatory Environment’s Impact

Regulation remains an important factor across the technology sector. Conference participants will be watching for developments that could affect data-center construction, software adoption, communications services, satellite networks, and overall technology investment. Changes in policy could influence both demand trends and competitive dynamics across multiple industries.

Mergers and Acquisitions

Mergers and acquisitions are expected to remain a key consideration. Investors will be looking for updates on announced transactions, potential consolidation opportunities, and signs that strategic deals could help companies strengthen competitive positions or unlock additional value.