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Full Connectivity - Bridging the Digital Divide with Shared Infrastructure

About a third of the global population still does not use the internet, with surveys suggesting that even awareness of the internet is not universal. Yet, the internet now gives access to vital services around the world, including healthcare and education, from which a substantial portion of the world is excluded.Bringing the last third of the population online is therefore a major opportunity to catalyze global development, unlocking opportunities for the most underserved to access basic services. In this Citi GPS report, we highlight Oxford Martin School research, funded by Citi, which shows that when telecoms infrastructure is shared between mobile network operators rather than operated by individual telecommunication companies, network quality improves and costs for consumers fall. At the same time, costs for operators fall and return on investment tends to increase. &nbsp;

<hr>1. Significant Progress, Remaining Gaps: The percentage of people living in areas not connected has dropped significantly, yet a major “usage gap” persists where people have coverage but do not use the internet.&nbsp;<hr>2. Affordability as a Primary Barrier: Affordability is the main obstacle to universal internet access in low- and middle[1]income countries. Handset costs can be as high as 16% of monthly income, and data prices vary widely, making internet use inaccessible for many.1&nbsp;<hr>3. Infrastructure Sharing as a Solution: Sharing telecommunications infrastructure, especially through models like TowerCos, can significantly reduce costs for operators, improve network quality and lower prices for consumers. &nbsp;

Key Takeaways 

1 GSMA, 2025. The State of Mobile Internet Connectivity Report 2024. p. 29

Bridging the Digital Divide with Shared Infrastructure

In this Citi GPS report, we highlight Oxford Martin School research, funded by Citi, which shows that when telecoms infrastructure is shared between mobile network operators rather than operated by individual telecommunication companies, network quality improves and costs for consumers fall. At the same time, costs for operators fall and return on investment tends to increase.

Full Connectivity

<ul><li data-list-item-id="ee02756715ac8e60f1bc6ed3031ad24ac">Strong growth in AI, energy security investments, renewables, batteries and EVs is driving sustained demand for power infrastructure and generation equipment</li><li data-list-item-id="e9b75329df1a7dc6b08e16716e2e388e1">Grid expansion is struggling to keep pace with rising power needs, increasing interest in distributed energy solutions and bring-your-own-generation strategies</li><li data-list-item-id="eb69f45bd62b5587e5ab16f406147efa8">Even if AI-related power demand moderates, long-term electrification and energy security trends should continue to support substantial investment across the power value chain</li></ul>

Must C: Overcoming Gridlock 2.0

A new Citi Research report from a team led by Head of Energy Strategy Anthony Yuen looks at the challenges hampering efforts to expand the world’s power grids, work that appears unable to keep pace with strong demand and supply growth. In this Must C report, we examine the evolving power landscape and explore pathways to ease grid constraints while supporting AI deployment and energy-security goals.Demand for power infrastructure and generation equipment continues to rise, driven largely by the U.S.-focused AI data-center buildout, as well as growing concerns around energy security. At the same time, the expanding adoption of renewables, batteries, and electric vehicles is adding to equipment demand. Yet power grids in many regions are struggling to keep pace, constrained by both supply-chain bottlenecks and lengthy permitting processes.As a result, speed-to-power has become a critical priority. Rather than waiting years for new grid connections, many power users are increasingly pursuing distributed solutions and "bring-your-own-generation" (BYOG) strategies, particularly ones based on U.S. natural gas. While grids will continue to expand, demand growth has been far stronger than expected, extending equipment lead times and increasing pressure on existing infrastructure.We believe AI will remain a significant driver of power investment. And even if AI-related demand growth moderates, the broader trends of energy security, electrification, renewable deployment, and EV adoption will still require substantial investment in power infrastructure and generation equipment.To meet these needs, demand is rising for a range of generation technologies, including combined-cycle gas turbines, reciprocating engines, aeroderivative turbines, fuel cells, renewable power, and energy storage systems. In the U.S., many of these solutions depend on natural gas supply, creating potential opportunities across the midstream sector.<h2>Not just about supplying power</h2>Building new power infrastructure is a lot more complicated than simply constructing a power plant and connecting it to the grid. In our view, three challenges increasingly define the landscape: persistent labor shortages, the unique characteristics of AI-driven power demand, and lengthy regulatory and permitting processes. Together, these factors are making it harder to bring new power supplies and data-center projects online, even as demand continues to accelerate.

Research @ Citi Podcast: Watts the Problem?

Labor remains one of the most important constraints. Across much of the world, the market for skilled trades and technical professionals is tight, particularly for occupations that support both data-center and power-infrastructure development.&nbsp;In the U.S., shortages of electricians, lineworkers, construction managers, mechanics, plumbers and other skilled workers are being compounded by simultaneous investment across data centers, utilities, renewables, EV charging networks, semiconductor manufacturing, transmission projects, housing, and public infrastructure. These industries are often competing for the same labor pool. As a result, securing qualified workers can increase costs, extend timelines, and create bottlenecks even when financing and equipment are available.We don’t expect these labor constraints to disappear quickly. Structural factors such as retirements, insufficient apprenticeship pipelines, and growing demand from grid modernization and renewable-energy deployment suggest labor availability is likely to remain a challenge well into the next decade. While initiatives such as expanded training programs, prefabrication, standardized equipment modules, and greater field-service capacity can help, these solutions require time to scale.&nbsp;Labor shortages are also a global issue, although the severity varies by region. Europe, the UK, Australia, and several fast-growing Asian markets face significant shortages of specialized talent, while China appears better positioned from a construction-capacity perspective but still requires advanced engineering and operational expertise.Beyond labor, AI data centers are introducing a new level of complexity into electricity planning. The challenge isn’t simply about growing demand. Rather, utilities and grid operators increasingly must manage three separate dimensions simultaneously: the sheer volume of demand, the ability to deliver power when needed, and the volatility of that demand once facilities are operational.The growth in volume is substantial. U.S. data-center capacity has expanded rapidly in recent years, and new facilities are requiring increasingly large amounts of electricity as computing hardware becomes more powerful. Yet translating this demand into actual operating projects has become difficult. Many proposed facilities face delays or cancellations before construction begins because developers can’t obtain power quickly enough or can’t secure the necessary equipment and approvals. Long waits for transformers, switch gear, generators, and interconnection studies can delay energization even when a project appears viable on paper.These challenges have increased interest in onsite generation, often referred to as BYOG. In many cases, developers are evaluating natural-gas-based generation technologies as a way to bypass grid bottlenecks and accelerate deployment.&nbsp;But the industry remains mindful of historical lessons. The power sector still remembers earlier periods when expectations for future demand resulted in excess generation capacity that later proved unnecessary. As a result, questions around the durability of long-term AI-driven electricity demand remain important when evaluating new investments.Volatility presents another distinct challenge. Unlike many traditional industrial loads, AI data centers can experience significant swings in electricity consumption over relatively short periods, depending on workload intensity. Those changes affect not only computing equipment but also cooling systems and supporting infrastructure.&nbsp;As renewable generation represents a growing share of the power mix, the interaction between variable electricity supply and increasingly dynamic demand adds complexity to grid operations. Utilities are therefore moving beyond traditional planning methods toward more detailed modeling that captures load behavior across different operating conditions, seasons, and weather scenarios.Concerns about grid reliability are also receiving greater attention. System operators increasingly need to account not only for steady demand growth but also for the possibility of large and rapid increases or decreases in load that can affect voltage, frequency, and overall system stability.The regulatory environment adds yet another layer of complexity. Permitting and interconnection processes exist for important reasons, including protecting reliability and ensuring that costs are allocated fairly. However, these processes weren’t necessarily designed for the scale and speed of current demand growth. In some cases, developers have submitted speculative or duplicate connection requests in an effort to secure future capacity, increasing the burden on utilities and grid operators that must evaluate projects that may never ultimately be built.Regulators are responding. In the U.S., policymakers and grid operators are exploring ways to accelerate interconnection timelines while maintaining reliability and protecting consumers from unnecessary costs. A key theme is that large power users may increasingly be expected to fund the infrastructure upgrades required to serve them and, in some circumstances, provide their own generation during periods of grid stress. Similar debates are taking place internationally as governments balance economic development, reliability, affordability, and energy-transition objectives.Stepping back, we believe the core issue is that both electricity demand and electricity supply are growing rapidly, but the systems required to connect them are struggling to keep pace. This dynamic supports continued demand for power infrastructure and generation equipment, while also creating supply-chain bottlenecks that can extend project timelines. In response, developers and policymakers are exploring a wider range of solutions, including flexible computing workloads, improved forecasting and grid modeling, dynamic grid technologies, and efficiency improvements that effectively function as a source of “virtual power.” Together, these approaches may help ease constraints, but they are unlikely to eliminate the need for substantial investment across the broader power ecosystem.&nbsp;

A redacted public version of our new report, Must C: Overcoming Gridlock 2.0 — Solving Power Bottlenecks to Drive AI &amp; Energy Security, is available <a href="https://ir.citi.com/-ipZbZShv8EfrgEUnbwp9btzkQTJtfRm3KNMVxJHRjV1_WNMJjs9z5iyxyf-5R8Qmg00RwGZbgk73zkqddnZJsyoEZi1UH6NmuXfNK-ly-E-k17SDbM6gg%3D%3D" target="_blank">here</a>. You can listen to the accompanying Research @ Citi podcast episode, Watts the Problem?, <a href="https://www.citigroup.com/global/insights/e82-watts-the-problem" target="_blank">here</a>. &nbsp;

The work to expand global power grids appears unable to keep pace with strong demand and supply growth, constrained by supply-chain challenges and many regions' permitting frameworks. A new Must C report from Citi Research explores solutions that could ease grid constraints and accelerate AI deployment and energy-security transitions.

Must C: Overcoming Gridlock 2.0 — Solving Power Bottlenecks to Drive AI & Energy Security

Transcript

<ul><li data-list-item-id="ed12a2a586d80d53c8075751712c3eea6">AI has reached a critical inflection point, moving from a back-office productivity tool to a core catalyst for business model evolution</li><li data-list-item-id="ea74ee4a4c3e9e5c5ecd3e8ae570d5322">Businesses are approaching AI investments strategically, focusing on areas that deliver the greatest value, whether in productivity, new product development, or customer experience enhancements</li><li data-list-item-id="e1bc797e5bd4203648c77d60df06a5d31">The emergence of "Agentic AI" poses new challenges around identity, authorization, and accountability that the industry is still grappling with, but also presents opportunities to simplify and improve payment processes</li></ul>

In this episode of The Citi Institute Podcast, host Alex Miller is joined by Ranjeet Kapur, Global Head of Fintech at Citi Commercial Bank and James Simcox, Group Chief Product Officer at Equals.They explore how Artificial intelligence has moved from experimental back-office tool to a core driver of business model change in Fintech and corporate banking, focusing on payments, fraud prevention, customer experience, and emerging Agentic AI.Ranjeet Kapur comments that AI and machine learning have existed for decades, but recent advances in hardware and processing power have unlocked their ability to deliver value at scale.James Simcox explains how AI has rapidly shifted from small-scale experiments to pervasive deployment across Equals, with AI now writing around 86% of the firm’s code, up from 5–10% a year earlier, and transforming functions such as reconciliation, finance, fraud detection, and customer service.Together, they examine the rise of Agentic AI and discuss why a strategic approach to AI investment is becoming increasingly important.Citigroup, Citi, and Equals are not affiliated and are independent of each other. Equals maintains a client relationship with Citi Commercial Bank. The speakers' views are their own and may not necessarily reflect the views of Citi or any of its affiliates. All opinions are subject to change without notice. Neither the information provided nor any opinion expressed constitutes a solicitation for the purchase or sale of any security. The expressions of opinion are not intended to be a forecast of future events or a guarantee of future results.

Ranjeet Kapur leads the FinTech segment for Citi Commercial Bank (CCB) within the Digital, Technology &amp; Communications (DT&amp;C) group. In this role Ranjeet supports his team’s efforts in better understanding and growing Commercial Bank’s engagement with this segment. Clients include payment intermediaries, alternative finance platforms, WealthTech and other models in the Fintech ecosystem.Prior to that, and as part of the of DT&amp;C segment, he led the process for launching the Western European digital business. He has also held roles in the Commercial Subsidiaries Group and Business &amp; Planning team at CCB. Before Citi Ranjeet worked in the technology field, first for a Canadian telecom and after that for a publishing house in Guatemala.Ranjeet holds an MBA from IESE Business School in Barcelona and B.Sc. in Computer Engineering from Rochester Institute of Technology in New York.

Ranjeet Kapur, Global Head of Fintech at Citi Commercial Bank

James Simcox is Chief Product Officer at Equals, where he leads product, delivery and strategy across the Group's embedded finance and payments platform. James has held progressively more senior roles throughout the growth of Equals, an embedded money movement platform powering exceptional businesses globally. Before Equals, James held a role as Business Analyst at Procter &amp; Gamble and led digital innovation and central projects at Quintessential Brands Group, reporting to the board. He is a recognised voice on the intersection of AI, security and fintech.

James Simcox, Group Chief Product Officer, at Equals

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From Productivity Tool to Business Transformation

In this episode of The Citi Institute Podcast, host Alex Miller is joined by Ranjeet Kapur, Global Head of Fintech at Citi Commercial Bank and James Simcox, Group Chief Product Officer at Equals. They explore how Artificial intelligence has moved from experimental back-office tool to a core driver of business model change in Fintech and corporate banking, focusing on payments, fraud prevention, customer experience, and emerging Agentic AI.

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AI at the Inflection Point

<ul><li data-list-item-id="ecb3d191ef95dc321b784c64311c3e04c">Citi Research outlines its Q3 positioning, highlighting a shift from broad tech optimism to a more selective view despite AI's continued influence on S&amp;P 500 earnings growth particularly in semiconductors</li><li data-list-item-id="e1489609dd8af6e9ec06878d4466cf95b">The market is experiencing a "broadening dynamic" beyond just tech with potential recoveries in cyclical sectors like consumer discretionary and industrials as easing oil prices may temper inflation concerns and Fed hawkishness</li><li data-list-item-id="ecca814dc7ecfe50d195f294f9b18935a">While AI remains crucial ongoing monitoring of AI capital expenditure and its potential impact on sectors like software will be key to navigating evolving equity market dynamics and identifying diversified investment opportunities</li></ul>

Scott Chronert looks at what may await U.S. equity markets in the third quarter, considering a "game of chicken" within the AI trade as well as the prospects for a broadening dynamic in the rest of the S&amp;P 500. This podcast contains thematic content and is not intended to be investment research. Nor does it constitute financial, economic, legal, tax or accounting advice. This podcast is provided for information purposes only and does not constitute an offer or solicitation to purchase or sell any financial instruments. The contents of this podcast are not based on your individual circumstances and should not be relied upon as an assessment of suitability for you of a particular product, security, or transaction. The information in this podcast is based on generally available information and, although obtained from sources believed by Citi to be reliable, its accuracy and completeness are not guaranteed. Past performance is not a guarantee or indication of future results. This podcast may not be copied or distributed, in whole or in part, without the express written consent of Citi. © 2026 Citigroup Global Markets Inc. Member SIPC. All rights reserved. Citi and Citi and Arc Design are trademarks and service marks of Citigroup Inc. or its affiliates and are used and registered throughout the world.

Scott Chronert is a Managing Director at Citi Research serving several roles, including US Equity Strategist, Global Head of ETF Strategy &amp; Analysis, and US Small/Mid Cap strategy. Scott assumed the US Equity Strategy role at Citi in October 2021. He brings a fundamental approach to assess the US equity landscape. Regarding ETFs, Scott and his team have been at the forefront of sell-side, institutional grade, analysis of the ETF ecosystem since 2012. His product covers all facets of ETFs, including broader industry trends, flow analysis, stock and market impacts, complemented with positioning views covering most asset classes and geographies. His work on US Small/Mid Cap provides a blend of top-down and stock-specific insight. Scott also contributes to Citi’s global equity strategy product. Prior to joining Citi Research in 2010, Scott spent more than 25 years in Institutional Equity Sales and Management roles (mostly at Citi). Citi was named Global ETF Research Provider of the Year 2019 by ETFexpress. Scott is a graduate of Dartmouth College, AB degree 1978 and UCLA Graduate School of Management, MBA degree 1980.

Scott Chronert, Managing Director at Citi Research 

Scott Chronert looks at what may await U.S. equity markets in the third quarter, considering a "game of chicken" within the AI trade as well as the prospects for a broadening dynamic in the rest of the S&amp;P 500.

/rcs/citigpa/storage/public/Research-Citi-Markets-Edition-Transcript-7-6-26.pdf

Markets Edition: Tech Trade at a Crossroad

<ul><li data-list-item-id="e10801c14488c85f5ceec0dba986ef83e">AI innovation is fundamentally reshaping global economics driving accelerated adoption and significant market performance shifts across diverse industries</li><li data-list-item-id="e9b83375de46c0c05046868bb75e2f7e3">Businesses are strategically leveraging AI for revenue growth and market expansion moving beyond mere cost savings to maximize creative application</li><li data-list-item-id="e7a7f87239c9172eaf22493172daa7d73">Critical AI deployment factors include rising output token costs persistent infrastructure constraints and evolving cybersecurity and regulatory challenges</li></ul>

Rob Rowe and Heath Terry offer a mid-year review of AI, ranging from the accelerating pace of adoption and how companies are leveraging AI to regulatory issues and infrastructure challenges such as the much-discussed token bottleneck.&nbsp;&nbsp;This podcast contains thematic content and is not intended to be investment research. Nor does it constitute financial, economic, legal, tax or accounting advice. This podcast is provided for information purposes only and does not constitute an offer or solicitation to purchase or sell any financial instruments. The contents of this podcast are not based on your individual circumstances and should not be relied upon as an assessment of suitability for you of a particular product, security, or transaction. The information in this podcast is based on generally available information and, although obtained from sources believed by Citi to be reliable, its accuracy and completeness are not guaranteed. Past performance is not a guarantee or indication of future results. This podcast may not be copied or distributed, in whole or in part, without the express written consent of Citi. © 2026 Citigroup Global Markets Inc. Member SIPC. All rights reserved. Citi and Citi and Arc Design are trademarks and service marks of Citigroup Inc. or its affiliates and are used and registered throughout the world.

Rob Rowe is the Head of Citi Research’s Global Strategy &amp; Macro Group (GSMG) as well as the Global Head of Citi Research. GSMG unites all of Citi’s Economists with Fixed Income, FX, Equity and Commodities strategists to create a common team providing research on the world’s major economies and asset classes. Rob has been with Citi for 35 years in various capacities. He originally joined Smith Barney, Harris Upham &amp; Company in 1989 working in investment banking, fixed income sales, and research. In addition to his overall responsibilities, he continues to provide portfolio strategy for select clients as part of his previous role overseeing the Global Bond Portfolio Analysis team. Rob is a graduate of Hartwick College with a BA in European History and the Theatre. He is also a graduate of the American Academy of Dramatic Arts.

Robert Rowe, Global Head of Research, Citi

Heath Terry is the Global Sector Head for Technology &amp; Communications Research at Citi Research. Prior to joining Citi in May 2025, Heath led the centralized research effort in TMT for Balyasny Asset Management and was a Managing Director at Third Point Ventures, leading its growth stage venture capital practice. Prior to that Heath worked for more than 20 years in equity research, most recently as the head of Goldman Sachs’ Global Investment Research’s Technology, Media and Telecom Group. While at Goldman Sachs Heath led research's working group on Artificial Intelligence and created the firm’s venture capital research practice. He is a Trustee for the Southern Environmental Law Center and Vice Chairman of The University of Alabama President’s Cabinet.

Heath Terry, Head of Technology & Communications Research

Rob Rowe and Heath Terry offer a mid-year review of AI, ranging from the accelerating pace of adoption and how companies are leveraging AI to regulatory issues and infrastructure challenges such as the much-discussed token bottleneck. &nbsp;

/rcs/citigpa/storage/public/Research-Citi-Ep-83-AIs-Mid-Year-Review-The-Token-Bottleneck-Transcript.pdf

E83: AI's Mid-Year Review: The Token Bottleneck 

<a class="lmn-btn lmn-btn-secondary" style="text-decoration:none;" href="https://www.citivelocity.com/cv-content-web/eppublic/wrap/epfcms/html/1_y6c2vu4b" role="button" target="_blank">Audio Description</a>

<ul><li data-list-item-id="e0e10f6f95656a0b2c6bf37d61a702524">Real-World Complexity: Anand Govind highlights that physical AI introduces exponentially higher complexity than virtual AI, requiring innovators to solve critical real-world challenges in safety, unit economics and industrial change management</li><li data-list-item-id="e9072ddc84b3c392de688914848312934">Commercial Inflection Point: Shenwei Zhu notes that the robotics sector is at a major inflection point, shifting from technological feasibility to commercial feasibility, which demands significant capital to fund the next industrial revolution</li><li data-list-item-id="e9dacf6f9c716a524fde8757f8ce0c1ea">Citi's Legacy of Progress: Drawing on over a century of experience funding historic industrial revolutions, Citi is actively bridging the gap between visionary physical AI companies and global capital to accelerate commercial growth</li></ul>

Citi brings together some of the most promising private companies in Robotics and Physical AI with leading institutional investors to explore the next generation of investment opportunities in this rapidly evolving sector.

Key Takeaways from Citi's Robotics and Physical AI Leadership Conference 2026

<ul><li data-list-item-id="e60373bb5fac055f58656276b6b4ed0e9">Resilience remains the defining macro theme. Global growth is expected to stay positive as inflation continues to moderate.&nbsp;</li><li data-list-item-id="e63408b48a2da0a061b4dc418ef38b42d">AI remains a powerful market driver. Continued investment in AI infrastructure and applications is supporting earnings, capital spending, and risk appetite.</li><li data-list-item-id="efc0da038f77ca5ea489bd17c3c2cc58f">Risks remain elevated but manageable. Geopolitics, monetary policy, and supply-side disruptions will continue to shape market outcomes through year-end. &nbsp;</li></ul>

As the second half of 2026 begins, Citi Research's outlook remains centered on a global economy that continues to expand despite geopolitical uncertainty, moderating inflation, and ongoing supply-side pressures. While growth expectations have softened, our base case remains one of continued expansion rather than recession. At the same time, the AI investment cycle continues to influence corporate spending, earnings expectations, and broader market performance.<h2>Global Economy: Slower Growth, Continued Expansion</h2>While the global outlook remains constructive, we continue to monitor several key risks, including higher energy costs, supply-chain disruptions, and the growing possibility of a significant El Niño event. These factors could affect inflation, agricultural production, energy generation, and labor productivity across a number of regions.Key forecasts include:<ul style="list-style-type:disc;"><li data-list-item-id="ea7fd2f163838818d5a9b0063e2bf407e">Global growth of 2.5% in 2026.&nbsp;</li><li data-list-item-id="e6c78285e64a329136bb0c47aeef0fccb">U.S. real GDP growth of 2.1% in 2026, easing to 1.8% in 2027.&nbsp;</li><li data-list-item-id="e65047bba23fda9b8f2980348ffdf1cab">China GDP growth of 4.7% in 2026.&nbsp;</li><li data-list-item-id="ec4c18a776602568ba0bcb720239a82e4">Euro Area GDP growth of 0.3% in 2026, improving to 1.4% in 2027.&nbsp;</li><li data-list-item-id="ea0e4167c805366acb45bc526429e3a13">Emerging market growth of approximately 4.0% in 2026, down from 4.3% last year.&nbsp;</li><li data-list-item-id="ef21caa271528afad0e0dcfa3ca515174">U.S. headline inflation declining from 3.2% in 2026 to 1.7% in 2027.&nbsp;</li><li data-list-item-id="e6adec7a89f65dee411b1baaafe5a36cf">U.S. unemployment averaging 4.5% in 2026.&nbsp;</li></ul><h2>U.S. Monetary Policy</h2>We continue to expect that the Federal Reserve's next move will be a rate cut rather than a rate hike, with the Fed Funds rate projected to end 2026 at 3.25% and move to 3.00% during 2027.&nbsp;<h2>Equities: Broadening Market Leadership</h2>Equity markets remain supported by resilient earnings growth, with leadership becoming more diversified across regions and market segments as economic data and earnings revisions improve. Our U.S. Equity Strategy team recently increased its year-end 2026 S&amp;P 500 target to 8,100, supported by earnings forecasts of $350 per share in 2026 and $400 in 2027.&nbsp;While the AI investment cycle remains an important structural driver of earnings growth and capital spending, we are seeing increasing evidence of broader participation beyond the initial AI beneficiaries. Improving economic data, more widespread earnings upgrades, and a more constructive backdrop for cyclical areas of the market support a wider range of opportunities across global equities. Citi's global strategists remain constructive on the asset class overall, targeting approximately 6% upside for global equities by year-end 2026.<h2>Rates: Focus Shifts Back to Policy Rates</h2>Across fixed income markets, policy rates are increasingly important drivers of returns.Our forecasts include:<ul style="list-style-type:disc;"><li data-list-item-id="e8c7574eaadfa2cb56c91be9217e72cef">U.S. 10-year Treasury yields at 3.90% by year-end 2026</li><li data-list-item-id="ecb066c06f85678962541b412f1702c6a">German 10-year Bund yields at 3.00%</li><li data-list-item-id="eb2b6b1d9964f4bea28fd6e634f2947b0">U.K. 10-year Gilt yields at 4.85% &nbsp;</li></ul>The U.S. Treasury yield curve is expected to steepen modestly as monetary policy eases.<h2>Credit Markets: Tight Spreads Persist</h2>Credit markets remain supported by relatively stable fundamentals and demand for income.Our forecasts include:<ul style="list-style-type:disc;"><li data-list-item-id="e330b2699e055007456f5086b7dbfdc7b">U.S. Investment Grade spread target: 90 basis points</li><li data-list-item-id="eac360d8d71301582e3bb159477a6317e">U.S. High Yield spread target: 305 basis points</li><li data-list-item-id="e6ebf37ceb3c30cc2d1abc4bf73fd2ab8">U.S. High Yield default rate: 3.4% in 2026 &nbsp;</li></ul>Spreads remain relatively tight by historical standards, leaving base rates as a larger contributor to total yield than spread income. As a result, the outlook for central bank policy and duration positioning are becoming increasingly important considerations across credit markets.Commodities: Structural Themes Remain in FocusCommodity markets continue to reflect a combination of geopolitical developments and longer-term structural demand driversEnergyFollowing easing tensions associated with a U.S.-Iran interim agreement, crude oil prices had retreated from recent highs, but hostilities have flared up again and Strait of Hormuz flows face renewed disruption risk. The base case remains a return to negotiations within 1–2 weeks, but delays have become more likely. We continue to forecast Brent averaging $75/bbl in Q3 2026, $70/bbl in Q4 2026 and $65/bbl in 2027, assuming a deal ultimately materializes and the Strait reopens.Our forecasts include:<ul style="list-style-type:disc;"><li data-list-item-id="e99f0ae0acc2544ee4b20e1312deab236">WTI: $71/bbl in Q3 2026, moving lower during 2027</li><li data-list-item-id="ecc65cb18d8b62bd0a7830b1eab787518">Brent: $75/bbl in Q3 2026, declining toward $65/bbl during 2027 &nbsp;</li></ul>Precious MetalsGold remains supported by ongoing demand for diversification and macroeconomic hedges, but near-term headwinds have us waiting to turn bullish until the end of the summer. We see gold reaching $5,000 in 2027.Industrial MetalsCopper remains closely linked to themes such as electrification, power infrastructure, and digital infrastructure development.Our forecasts include:<ul style="list-style-type:disc;"><li data-list-item-id="ec80119cb0743e480ad1473df87b79726">$14,000/MT in Q3 2026</li><li data-list-item-id="eabd9aff9f6304d3ebfaf20e95e2963c4">$14,500/MT in Q4 2026</li><li data-list-item-id="e786015eea44c419b62c33143d8405666">$14,250/MT average during 2027 &nbsp;</li></ul>Foreign Exchange: Gradual Dollar ModerationOur FX outlook points toward modest U.S. dollar weakness over the medium term.Key forecasts include:<ul style="list-style-type:disc;"><li data-list-item-id="e050223a5d2323f4905a114ddcb9ee239">DXY declining from 101.82 in Q3 2026 to 99.96 by Q3 2027</li><li data-list-item-id="e47ad33a96a77a040d800313878f1ffb0">EUR/USD near 1.14</li><li data-list-item-id="ec0f2671e31a12d54bb129cd1924e8d8f">USD/JPY declining from 159 to 144 by year-end 2027</li><li data-list-item-id="e82c703dc6ea23104f5874c78ec233dc3">GBP/USD remaining around 1.31</li><li data-list-item-id="ee03ed1f0985cd3d3e3730cdb9aa9b3e8">USD/CNY moving toward 6.73 &nbsp;</li></ul>Overall, we expect currency markets to continue reflecting relative growth, inflation, and monetary policy differentials across major economies.Emerging Markets: Differentiation Remains KeyEmerging-market performance remains highly differentiated across countries and regions, with investors balancing growth opportunities against a range of macroeconomic and policy risks. Our economists continue to monitor the potential impact of a severe El Niño event on food prices, energy generation, and labor productivity across a number of markets.&nbsp;Key themes include:<ul style="list-style-type:disc;"><li data-list-item-id="e3bef6a786c044e10db7ac560367b34d7">Potential inflation pressures from weather-related supply shocks, particularly in countries with high food-price sensitivity.&nbsp;</li><li data-list-item-id="eccacc05de2218c7565e1239817289490">A somewhat more hawkish policy backdrop across parts of the emerging-market universe as central banks balance inflation risks against softer growth.&nbsp;</li><li data-list-item-id="e9800ebd1e6f60ca6e1db2ecefb23e806">Emerging-market local-currency bonds continue to outperform U.S. Treasuries on a year-to-date total-return basis, with Latin America leading performance and CEEMEA also delivering solid returns.&nbsp;</li><li data-list-item-id="e146996faec293dcb0613e3fd69a48baf">Selective opportunities remain in EM credit, supported by attractive real yields, resilient fundamentals, and continued investor demand for carry. &nbsp;</li></ul>Digital Assets: Market Maturity and New RisksOur Digital Assets team continues to monitor an evolving market landscape as institutional participation increases.Current observations include:<ul style="list-style-type:disc;"><li data-list-item-id="eede15fa1545c9dfad872bafd66b565ff">Total crypto market capitalization is around $2.35 trillion</li><li data-list-item-id="e069b85466410f29b6715710790d19eb6">Bitcoin ETF flows have disappointed as investor risk-appetite and congressional progress remain scarce</li><li data-list-item-id="e3f605169cd1e568bf7bd7bb2f6a068bd">Stablecoin usage continues to expand and tokenization develop</li><li data-list-item-id="e5fed76b9b8bd989fa500098431e58007">Blockchain ecosystems continue to compete for activity and liquidity &nbsp;</li></ul>Our research also highlights the importance of monitoring emerging technological developments, including quantum computing, which could influence the long-term evolution of blockchain networks and digital asset infrastructure.<h2>Asset Allocation: The AI Cycle Remains the Dominant Force</h2>Our Global Asset Allocation team continues to view the AI investment cycle as a defining driver of market performance, supporting earnings growth, capital expenditure, and broader risk appetite. While geopolitical developments, monetary policy uncertainty, and supply-side shocks have periodically created volatility, our overarching framework remains anchored in the view that the conditions typically associated with the end of major bull markets have yet to emerge. Expressing a view on a relatively strong business cycle favors base metals. At the same time, elevated policy uncertainty, tight credit spreads, and ongoing geopolitical risks argue for having some hedges on as well, and credit screens well as an underweight against our equity overweight, while in rates we are mostly in relative value space.&nbsp;<h2>Timeline: Key Events to Watch</h2><h3>Q3 2026</h3><h4>AI investment remains a key market driver</h4><ul style="list-style-type:disc;"><li data-list-item-id="ee3d67941821f7abd60121cbb11b4c96b">AI infrastructure spending continues to support earnings expectations and capital expenditure</li><li data-list-item-id="e3605ca409c0ced1733eceb49ea7a7737">S&amp;P 500 target: 8,100</li><li data-list-item-id="ebd425c49fee75e7b1087ebee119fbc48">Copper forecast: $14,000/MT</li><li data-list-item-id="e020e6da789b602b3f7ff619c0c7786e1">WTI forecast: $71/bbl &nbsp;</li></ul><h3>Q3–Q4 2026</h3><h4>Monetary policy inflection point</h4><ul style="list-style-type:disc;"><li data-list-item-id="ee966925c1d2a9983904e4c5b21ce3caa">Our economists expect the next Federal Reserve move to be a rate cut rather than a hike</li><li data-list-item-id="efd0e6c2ffbf45f5b33345ce697bea0aa">Inflation is expected to continue moderating</li><li data-list-item-id="ea05f378c35eb218aeb17d55592c13cbb">The Treasury yield curve is expected to steepen modestly as monetary policy eases &nbsp;</li></ul><h3>Year-End 2026</h3><h4>Key forecast milestones</h4><ul style="list-style-type:disc;"><li data-list-item-id="e55b11e5ec198ef0a83838ceeb33b1609">Fed Funds Rate: 3.25%</li><li data-list-item-id="ee5a2aacef1fec6d0f5fbdeac3cfeae21">S&amp;P 500 target: 8,100</li><li data-list-item-id="e654be7d88807c878e9e1dbb7bd97ce99">STOXX 600 target: 640</li><li data-list-item-id="eedaceec7b4b2bbc36265683cf01058da">U.S. 10-year Treasury yield: 3.90%</li><li data-list-item-id="eb854ce4e43574b13432590af6fe34c91">DXY forecast: 100.88 &nbsp;</li></ul><h3>Early 2027</h3><h4>Supply-Side and Climate Developments Remain in Focus</h4><ul style="list-style-type:disc;"><li data-list-item-id="e3a3a9fa6483d494f87deef5b6ded304c">El Niño conditions remain a key factor for agriculture, energy markets, and labor productivity</li><li data-list-item-id="ec3eca2386e555d050ee4ac9304ad2ec1">Commodity and supply-chain impacts remain an important watchpoint for the global outlook</li></ul><h3>Q1 2027</h3>Our recent research indicates normalization may be less linear due to renewed U.S.-Iran conflict escalation and potential additional Strait of Hormuz disruptions, but our base case still assumes eventual negotiations and reopening of flows.<h4>Energy Market Normalization</h4><ul style="list-style-type:disc;"><li data-list-item-id="e990550731964c208d86884209d158cdb">Brent crude forecast to move toward $60–65/bbl as supply disruptions continue to ease</li></ul><h3>Year-End 2027</h3><h4>Key forecast milestones</h4><ul style="list-style-type:disc;"><li data-list-item-id="e5f3b81e05fe9ed86d131160c60a1ac07">U.S. GDP growth: 1.8%</li><li data-list-item-id="eafabfb5d7e383ad808e097b5e65956de">U.S. inflation: 1.7%</li><li data-list-item-id="eb91b4fc0d82ab4aeaee133a0d3cd7da3">Fed Funds Rate: 3.00%</li><li data-list-item-id="e60c3995d65f7bbe89e0468d84bed0d12">Gold: $5,000/oz</li><li data-list-item-id="eac135e5b84923fae26af304cb530e6b2">USD/JPY: 144</li><li data-list-item-id="eb3c17bbb5d19f05dc27b8fdba709c233">China GDP growth: 4.6% &nbsp;</li></ul><h2>Bottom Line</h2>The defining theme for the remainder of 2026 remains resilience. Global growth is expected to remain positive, inflation continues to moderate, and the AI investment cycle remains an important driver of earnings and capital spending. At the same time, investors continue to navigate an environment shaped by geopolitical uncertainty, evolving monetary policy, supply-chain risks, climate-related disruptions, and technological change.

Citi Research's Midyear 2026 Outlook highlights a resilient global economy, moderating inflation, and continued expansion despite geopolitical uncertainty. The AI investment cycle remains a key driver of earnings, capital spending, and market performance, while investors navigate evolving monetary policy, supply-chain risks, and shifting opportunities across asset classes.

Midyear 2026 Outlook: Resilience, AI, and Evolving Market Dynamics

<ul><li data-list-item-id="e33fb66ba7976799a716cf689efe05558">The largest direct beneficiaries of today’s AI boom are the U.S. and a small group of economies with critical positions in semiconductors and software</li><li data-list-item-id="e96b6285df2d441e8a5a772a05e9d1800">The long-term gains from AI may depend less on who builds the technology than on how widely and effectively businesses adopt it</li><li data-list-item-id="e7542bd7e9334c792321d1d4bfc1ca3b5">AI could widen economic gaps between countries unless emerging economies significantly improve digital infrastructure skills and access to the technology</li></ul>

A new Citi Research report from a team led by Head of Emerging Markets Economics Johanna Chua explores the possibility of an emerging-markets growth divide in the scramble for benefits from artificial intelligence (AI). There are only a few potential emerging-markets winners in the U.S.-led AI capex cycle, and if the 1990s information-technology (IT) revolution is any guide, future productivity gains could accrue more to users than producers. Here too, emerging markets look relatively disadvantaged vs. developed ones.As Chua and team note, AI has become one of the most important forces shaping the global economy. Massive investment in AI infrastructure — especially in the U.S. — has helped support global growth even as governments and businesses have faced repeated shocks, from trade disputes to geopolitical tensions. Much of the public discussion has focused on how AI will boost company profits, but a broader question is equally important: How will the benefits of AI be distributed across countries, particularly between developed and emerging economies?The answer remains uncertain. Estimates of AI’s long-term impact on productivity vary widely: Some economists expect relatively modest gains, while others see AI delivering a much larger boost to economic output. What is clear is that many investors assume the U.S. will capture a disproportionate share of the benefits, with only a handful of emerging economies seeing meaningful gains.That view helps explain why U.S. tech stocks have significantly outperformed many other markets in recent years, alongside economies such as Taiwan and Korea that occupy critical positions in the semiconductor supply chain.Three main arguments support the idea that emerging markets may be at a disadvantage.The first is that most of the value created by AI will be captured by the companies developing the leading AI models and the infrastructure that powers them. Today, those firms are concentrated largely in the U.S., while a small number of companies in Taiwan and Korea dominate essential semiconductor technologies.Under this view, businesses around the world will pay for access to AI through software subscriptions, cloud-computing services, and related products. As a result, much of the economic value generated by AI adoption could flow back to the firms providing the technology rather than the firms using it.However, China presents an important challenge to this narrative. Chinese AI models have become increasingly competitive while often remaining substantially cheaper to use. Lower costs appear to reflect a combination of more efficient model designs, lower infrastructure and energy costs, subsidies, and aggressive pricing strategies.At the same time, concerns about access to leading U.S. models have encouraged countries and companies to explore open-source alternatives, many developed in China. Recent releases from Chinese developers have also narrowed the performance gap with leading American models.Even so, greater use of Chinese AI models doesn’t automatically translate into equivalent profits for Chinese firms. Many organizations may still rely on American cloud infrastructure and software tools while using Chinese-developed models, leaving the distribution of economic gains uncertain.The second argument focuses on how quickly AI spreads through an economy.History suggests the greatest benefits of transformative technologies often go not to the companies that create them but to the much larger number of businesses that successfully adopt them. In the IT revolution of the 1990s, for example, much of the productivity gains came from firms that learned how to use new technologies effectively.Current measures of AI adoption suggest richer countries are better positioned to put the same lessons into practice. Indicators of AI use and readiness, digital infrastructure, innovation capacity, education levels, and regulatory frameworks are all strongly correlated with income levels.Many emerging economies face practical barriers. Reliable electricity, data infrastructure, internet connectivity, and digital skills remain unevenly distributed. Language also matters: Because many advanced AI systems have been built around a limited number of major languages, large populations may initially benefit less if their primary languages are underrepresented.As a result, AI adoption is likely to proceed most quickly in higher-income economies, potentially widening existing productivity gaps.The third argument concerns labor markets.AI is generally expected to have its greatest impact on jobs that involve information processing, analysis, communication and other cognitive tasks. These occupations are more common in developed economies than in many emerging markets.Research measuring exposure to AI across occupations finds that countries with higher incomes tend to have a larger share of jobs that could be affected by AI. This may seem counterintuitive, but it also means those economies have more opportunities to generate productivity gains through AI adoption.The impact on jobs remains highly uncertain. AI may replace some tasks while making workers more productive in others. It may also create entirely new tasks and occupations. Predicting these effects is difficult as jobs consist of many individual activities, and AI's influence continues to evolve rapidly.For emerging economies, a key question is whether AI helps workers perform more sophisticated tasks that were previously inaccessible to them. While this could narrow skill gaps between countries, the likely macroeconomic impact may not be large enough to fundamentally alter existing economic hierarchies.We are still in the early phase of an enormous global buildout of AI infrastructure. Investment continues to flow into semiconductors, software, data centers, power networks and the energy systems required to support increasingly intensive computing demands.Among emerging economies, Taiwan and Korea appear to be the largest beneficiaries so far because of their dominant positions in semiconductor production. Strong demand for advanced chips has boosted exports, investment, and industrial activity in both economies.Other participants include Singapore, Malaysia, Vietnam, Thailand, Mexico and China. However, when measured relative to the size of their domestic economies, the growth benefits have generally been more modest than headline export figures might suggest. Singapore stands out as one of the clearest beneficiaries because of its specialized role within the semiconductor ecosystem.On the software side, Israel is perhaps the most significant beneficiary: The country has built strong positions in cybersecurity and enterprise software, areas that are increasingly important as businesses integrate AI into their operations.Meanwhile, data-center investment is expanding across many emerging economies as technology companies seek to bring AI services closer to users. Yet the macro impact of such investment may be smaller than many assume. Data centers require substantial construction activity and supporting infrastructure, but much of the equipment is imported. Once operational, they also employ relatively few workers compared with their scale.The longer-term benefits are therefore likely to come less from construction itself and more from the services that data centers enable, such as cloud computing, data processing and broader AI adoption by local businesses.Countries such as Malaysia and Thailand appear to be attracting economically meaningful investments. By contrast, many African economies continue to receive relatively little AI-related infrastructure investment, risking a widening digital divide.<h2>Another question: What if the AI bubble pops?</h2>Technological revolutions have often been accompanied by periods of excessive optimism. While AI will likely generate genuine economic benefits, markets may still overestimate how quickly those benefits will arrive, or how large they will ultimately be.If AI-related investments were to disappoint, a sharp market correction could follow. Such a selloff would affect emerging markets through several channels.First, global investors would likely become more risk-averse, reducing capital flows to emerging economies and tightening financial conditions.Second, economies closely tied to the AI supply chain — especially Korea and Taiwan — could face direct economic effects through weaker demand.Third, a decline in U.S. equity markets could reduce household wealth and consumer spending, creating knock-on effects for countries dependent on U.S. demand.In such a scenario, investors would probably still seek safety in U.S. government bonds. However, questions about U.S. fiscal sustainability and changing market dynamics could make traditional safe-haven behavior less predictable than in the past.Some higher-quality emerging-market local-currency bonds could potentially benefit as alternative destinations for capital, particularly because many emerging economies have not experienced the large AI-driven investment inflows seen in U.S. markets.

A new Citi Research report considers the possibility of an emerging-markets growth divide in the scramble for benefits from AI. There are only a few potential emerging-markets winners in the U.S.-led AI capex cycle, and if the 1990s IT revolution is any guide, future productivity gains could accrue more to users than producers. Here too, emerging markets look relatively disadvantaged vs. developed ones.

Emerging Markets Economic Outlook & Strategy: Artificial Intelligence and the EM Growth Divide

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<ul><li data-list-item-id="eda1a70075029e545717cf4b5ad482a27">The S&amp;P 500's composition has evolved, with the AI-influenced Growth cluster now comprising 55% of the index—up from under 20% three decades ago—fundamentally altering the equity market's risk profile</li><li data-list-item-id="e6c3b8eda5e0269769c40ce5562bc1337">This shift increases the S&amp;P 500's risk and volatility (beta), making it more sensitive to the AI theme and requiring a new U.S. equity strategy beyond traditional value versus growth analysis</li><li data-list-item-id="ef2d7a7e0c3545a61b1b2283af779bc1e">Investors should look beyond large-cap stocks to small and mid-cap equities for more direct exposure to traditional macroeconomic influences, diversifying away from the concentrated AI influence in the S&amp;P 500</li></ul>

An old investing adage is to just own the S&amp;P 500. But you have to know what you're buying — and as Scott Chronert and Patrick Galvin discuss, the S&amp;P 500 has seen a major evolution over the last 30 years. So how has it changed, and what do these changes mean for broader exposure to U.S. equities and the AI theme?This podcast contains thematic content and is not intended to be investment research. Nor does it constitute financial, economic, legal, tax or accounting advice. This podcast is provided for information purposes only and does not constitute an offer or solicitation to purchase or sell any financial instruments. The contents of this podcast are not based on your individual circumstances and should not be relied upon as an assessment of suitability for you of a particular product, security, or transaction. The information in this podcast is based on generally available information and, although obtained from sources believed by Citi to be reliable, its accuracy and completeness are not guaranteed. Past performance is not a guarantee or indication of future results. This podcast may not be copied or distributed, in whole or in part, without the express written consent of Citi. © 2026 Citigroup Global Markets Inc. Member SIPC. All rights reserved. Citi and Citi and Arc Design are trademarks and service marks of Citigroup Inc. or its affiliates and are used and registered throughout the world.

Scott Chronert is a Managing Director at Citi Research serving several roles, including US Equity Strategist, Global Head of ETF Strategy &amp; Analysis, and US Small/Mid Cap strategy. Scott assumed the US Equity Strategy role at Citi in October 2021. He brings a fundamental approach to assess the US equity landscape. Regarding ETFs, Scott and his team have been at the forefront of sell-side, institutional grade, analysis of the ETF ecosystem since 2012. His product covers all facets of ETFs, including broader industry trends, flow analysis, stock and market impacts, complemented with positioning views covering most asset classes and geographies. His work on US Small/Mid Cap provides a blend of top-down and stock-specific insight. Scott also contributes to Citi’s global equity strategy product. Prior to joining Citi Research in 2010, Scott spent more than 25 years in Institutional Equity Sales and Management roles (mostly at Citi). Citi was named Global ETF Research Provider of the Year 2019 by ETFexpress. Scott is a graduate of Dartmouth College, AB degree 1978 and UCLA Graduate School of Management, MBA degree 1980.

Scott Chronert, U.S Head Equity Strategy, Citi

Patrick Galvin is a Vice President at Citi Research covering US Equity Strategy as well as US ETF Strategy. Prior to joining Citi in 2022, Patrick spent 8 years on the buy-side working for two of the largest global ETF issuers. Most recently, he spent 4 years working as an Institutional ETF Specialist &amp; ETF Capital Markets Strategist within Invesco’s ETF business. Prior to Invesco, Patrick spent 4 years working within Deutsche Bank’s Asset Management division (DWS), where he worked in ETF Capital Markets. Patrick graduated summa cum laude from Gettysburg College in 2014 with a BA in Economics and is a CFA Charterholder.

Patrick Galvin, U.S ETF Strategy, Citi

An old investing adage is to just own the S&amp;P 500. But you have to know what you're buying — and as Scott Chronert and Patrick Galvin discuss, the S&amp;P 500 has seen a major evolution over the last 30 years. So how has it changed, and what do these changes mean for broader exposure to U.S. equities and the AI theme?

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Markets Edition: AI’s Subtle Impact On The Equity Market

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