Artificial Intelligence (AI)

Banking & International

Transcript

Citi GPS Report

In this episode of The Citi Institute podcast, host Alex Miller is joined by Shenwei Zhu, Managing Director, Investment Banking Division, Citi and Felix Zhang, CEO and Founder, Pudu Robotics to discuss the possibilities and challenges that come with the rapid advancements in the field of robotics, the rise of AI-powered robots that can see, learn, move, talk, and take actions, and what that means for the future.Shenwei Zhu, Managing Director, Investment Banking Division, Citi highlights the importance of data availability and techniques like virtual simulation to train physical AI models and the potential impact of robotics on the labour force.Felix Zhang, CEO and Founder, Pudu Robotics offers advice for aspiring robotics entrepreneurs, emphasising the importance of technology, long-term vision, customer collaboration, and global expansion.Our guests share insights on the growth of the robotics industry, emerging policy and regulatory considerations, including implications for the labour force.Citigroup (“Citi”), and Pudu Robotics are not affiliated and are independent from each other, Although Pudu Robotics is a client of the Banking sector. 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.

<ul><li>AI-driven robotics are revolutionizing how machines learn, act, and integrate into industry and daily life.</li><li>Virtual simulation and data-driven training are accelerating robotics innovation.</li><li>The discussion examines workforce impacts, policy shifts, and what drives success in global robotics ventures.</li></ul>

Felix Zhang is the founder and CEO of Pudu Robotics, the world's leading service robotics company. Felix studied mechanical engineering as an undergrad and attended Hong Kong University of Science and Technology's master's program for computer science. At the early age of 20, Felix placed first in a prestigious Asian-Oceanian college robot competition, and second overall in the APAC region. This was the catalyst for Felix to launch a series of startups including the leading tech news outlet in China (leiphone.com) and a home robotics company, as well as his current company, Pudu Robotics, in 2016. Under Felix's stewardship, Pudu grew into a global leader in the service robotics sector, with over 90,000 units deployed globally in 60+ countries and regions, over 800 employees, and over one billion yuan in funding from Tencent, Sequoia Capital China, and other top investors.

Felix Zhang, Founder and CEO of Pudu Robotics

Shenwei Zhu is a Managing Director in Citigroup's Investment Banking Division. Shenwei currently is based in New York covering Industrial Technology (with a focus on automation, robotics, machine vision, Industrial IoT, industrial safety, advanced mobility and hydrogen fuel cell) companies globally. Previously he was based in London, focusing on industrial M&amp;A across the EMEA region. Prior to that, Shenwei was part of Citi’s Global Industrials Investment Banking group in New York. &nbsp;Shenwei earned an MBA with honors from Cornell University, a Master of Mechanical and Aerospace Engineering with honors from Illinois Institute of Technology and graduated cum laude from the University of Notre Dame with a B.S. in Mechanical Engineering.Shenwei is a native Mandarin speaker.Shenwei has advised on over $50bn of M&amp;A, IPO and financing transactions, his transaction experiences include:<ul style="list-style-type:disc;"><li>Advisor to Symbotic on its $550mm acquisition of Walmart Advanced Systems and Robotics</li><li>Advisor to Nordic Capital on its ~$1bn sale of Consilium Safety Group to Antin Infrastructure Partners</li><li>Capital Markets Advisor to Nikola’s $900mm equity capital raise ($200mm private convertible + $600mm At-the-Market (ATM) equity offering +$100mm Follow-on)</li><li>Advisor to Softbank on its $5.5bn De-SPAC merger with Symbotic </li><li>Advisor to Nikola’s acquisition of Romeo Power</li><li>Capital Markets Advisor to FuelCell Energy’s At-the-Market (ATM) equity capital raise</li><li>Joint Bookrunner to AutoStore’s $2.45bn IPO on Oslo Stock Exchange</li><li>Advisor to SK Holdings on its $1.6bn Investment in Plug Power </li><li>Advisor to John Deere on its $250mm acquisition of Bear Flag Robotics</li><li>Lead Left underwriter to Mason Industrial Technology’s $500mm IPO on NYSE</li><li>Lead Left underwriter to Hennessy Capital Investment Crop V’s $345mm IPO on NASDAQ</li><li>Lead Left underwriter to Pivotal Investment Corp III’s $275mm IPO on NYSE</li><li>Advisor to Xerox on its $35bn public hostile takeover of HP (transaction terminated) </li><li>Advisor to Fortna on its $290mm sale to Thomas H. Lee Partners</li><li>Advisor to Xerox on its $7.7bn merger with Fujifilm and defense against shareholder activist Carl Icahn (transaction terminated) </li><li>Advisor to Korber on its acquisition of HighJump Software for an undisclosed amount</li><li>Advisor to Sibanye-Stillwater on its sale of gold and palladium streaming rights to Wheaton Precious Metals for $500mm</li><li>Advisor to Louis Dreyfus Company on its sale of Global Metals business to a consortium led by China Molybdenum for $450mm</li><li>Advisor to Sibanye Gold Limited on its acquisition of Stillwater Mining Company for $2.2bn</li><li>Lead Left underwriter to AquaVenture Holding’s $135mm IPO on NYSE</li><li>Joint lead bookrunner for the $3bn recapitalization of R.R. Donnelley’s spinoff of LSC Communications and DFS</li><li>Advisor to TE Connectivity on its sale of Circuit Protection Devices business to Littelfuse for $350mm </li><li>Advisor to TE Connectivity on its acquisition of Measurement Specialties for $1.7bn</li><li>Advisor to Eaton Plc on its sale of Aerospace Power Distribution and Cockpit Solutions business to Safran for $270mm</li><li>Advisor to R.R. Donnelley on its acquisition of Consolidated Graphics for $700mm</li></ul>

Shenwei Zhu, Managing Director, Investment Banking, Citi 

Our guests share insights on the growth of the robotics industry, emerging policy and regulatory considerations, including implications for the labor force.&nbsp;

/rcs/citigpa/storage/public/CIP_The_Rise_of_AI_Robots_Transcript.pdf

The Rise of AI Robots

<ul><li>Physical AI is at an inflection point for industrial markets, marked by abundant capital, maturing technology and a diversifying ecosystem</li><li>While humanoid robots have attracted ample attention, this form factor may not be ideal for many Physical AI applications, with battery power and manual dexterity among the challenges</li><li>Warehouse automation is seeing a transition from rigid Automated Guided Vehicles to flexible Autonomous Mobile Robots, but the future of this competition is less about robotic hardware than about the software ecosystem orchestrating that hardware</li></ul>

In a new Super-Sector Analysis from Citi Research, Martin Wilkie and a team of analysts explore the rise of Physical AI — defined as any physical process learning from and applying AI — for industrial markets. We see Physical AI as at an inflection point, with abundant capital, maturing technology and a diversifying ecosystem. AI-enabled edge devices (those at the “edge” of a network as opposed to the central data center or cloud) could see growth in double-digit percentages, as could design and simulation software.&nbsp;Overall, we see adoption of Physical AI adding percentage growth in the mid-single digits to annual customer capex growth as capital replaces labor, with additional growth fueled by M&amp;A in software and connected hardware. Similar to how Large Language Models (LLMs) need huge amounts of text, industrial AI needs industrial data, of both real-world and simulated varieties. Industrial companies’ large data-gathering physical installed bases and domain-specific know-how loom as both potential key enablers of adoption and moats against disruption.The growth of networked machines that can connect to the Internet, aka the “Internet of Things,” has already augmented on-device intelligence for industrial products, but we now think the next driver will be AI, as featured in product and process design as well as in edge intelligence. Emerging use cases for industrials include preventative maintenance, product design and operations monitoring.&nbsp;In recent years, AI investment for industrial names has been dominated by the impact of Generative AI (GenAI) and LLMs on data centers and related infrastructure. Physical AI is different in that it’s domain specific, requiring separate adoption by end markets that each have unique requirements. That means spending patterns will be defined not by hyperscalers’ capex plans, but by the pace of adoption in each end market.&nbsp;We see three pillars of success for industrial companies: digital twin models (which are virtual representations of physical processes), real-world data gathering through edge devices, and simulation. We’re at the beginning of this journey, as development of the technology is nascent and the industrial cycle will play a role. But companies are already preparing for what’s coming, and we expect investment to continue to pivot to Physical AI adoption.To illustrate the opportunity, there are some 4 million industrial robots installed globally, with penetration varying enormously by region and industry. If such robots displace 30% of manufacturing tasks over the next decade (running at three shifts a day and doubling human productivity), the installed base will grow to almost 30 million in 10 years, a compound annual growth rate (CAGR) above 20%. That’s almost three times the growth rate predicted by the International Federation of Robotics. We also note that increased adoption of AI arguably tilts spending from labor to capital investment; in the factory P&amp;L, employee cost is replaced by depreciation. We estimate the related capex requirements could augment capex growth by mid-single digits.&nbsp;<h2>Phases of AI adoption</h2>We see several phases of AI adoption. GenAI is most prevalent, used in industry to combine “knowledge” (such as service documentation) and data, and we see GenAI primarily as an efficiency tool. Agentic AI, with AI decision-making in industrial applications, is also emerging for specific tasks, but adoption is very early-stage, including in areas such as purchasing. “Digital twin” technology and software-defined automation (where AI increasingly drives product and process design) are arguably the areas offering the biggest potential for both disruption and benefits.Physical AI is often equated with humanoid robots, but the market is larger than that: NVIDIA, for example, divides AI-capable robots into three categories: agentic AI (knowledge robots), generalist robots (including humanoid forms) and transportation (such as autonomous vehicles). We focus on generalist robots, specifically in factory and warehouse automation. Humanoid robots will be an important category but won’t displace many specialized robotic form factors, which can be faster or more powerful in specific applications.&nbsp;Even for data software, the industrial installed base and related domain experience matter; industrial software platforms benefit enormously from “equipment on the ground” — controllers, sensors, motors and other devices well positioned to collect data in order to optimize equipment and streamline processes. These connected products arguably formed the largest barriers to entry for newcomers to the industrial Internet of Things, and we think this will also be the case for Physical AI.<h2>Use cases</h2>Simulation is a key pillar of the “simulation, training, edge” framework to drive penetration of Physical AI, especially in product and process design. Product design already relies heavily on software to simulate everything from drag coefficients to load-bearing capabilities, and AI design software can iterate toward a design that’s optimized but within the parameters. Simulation already offers efficiency gains over real-world testing, with more such gains expected: For instance, teaching a robot using real-world data is painfully show, but using synthetic data can accelerate this.When discussing industrial robots, humanoid form factors have attracted a lot of attention, but our impression is that intelligent robotic arms with dedicated end-of-arm effectors are optimal in more than 90% of manufacturing cases, pointing to significant adoption potential. Over time humanoids could offer autonomous versatility, but in the near term we see intelligent single-arm robots integrated with dedicated process know-how as the preferred form factor. Integrating intelligence and AI will be the next key technology step, with ABB Group seeing pick-and-place applications becoming more autonomous and versatile first, with potential differentiation in software, high motion accuracy, high-speed performance and integration tools.Simulation, training and edge represent the “three computers” needed in industrial AI, and edge control will need to evolve alongside the assets. At its most basic, industrial automation is sensing (data gathering), intelligence (decision making) and control (instructions). Most industrial processes rely on embedded software in logic controllers or distributed control systems as the intelligence, which has been coded in advance. AI can evolve this to optimize decision-making in real time.<h2>Humanoid robot challenges</h2>Physical AI is simultaneously the key and the main obstacle to developing humanoid robots because integrated advanced AI with complex hardware creates significant hurdles to real-time performance, efficiency and safety. Unlike software-only AI, Physical AI must directly perceive and interact with the unpredictable real world, and without excessive latency.&nbsp;Building Physical AI requires repetitive training and data collections, which can be done through simulated methods, real-world ones or a combination of the two. We see more humanoid-robot companies relying on simulated methods for such training, as simulated methods are far more time-efficient than real-world ones.&nbsp;Many humanoid-robot companies are focusing on industrial applications, as factory jobs are mostly well-defined tasks such as moving, stacking or sorting objects. An issue that’s generated considerable debate is whether a humanoid robot needs to be equipped with two legs. This is considered the optimal form for a variety of workplace setups, but maintaining balance consumes significant battery power. This has led to more humanoid-robot companies in China introducing wheel-based versions of their products.&nbsp;Another issue is the design of dexterous hands. Chinese humanoid-robot makers equip their robots with suckers or three-finger hands, since these are able to handle existing tasks that humanoid robots are trained to carry out.&nbsp;<h2>Vision and sensing</h2>As the Physical AI landscape evolves, we see machine vision playing a critical role in further driving efficiency on factory floors and enhancing product quality through assessments made on the assembly line. We also think machine vision will be increasingly essential in collecting real-time factory data, which can be utilized to optimize overall operational productivity. Machine vision is becoming more mainstream, with such systems used for applications including visual inspection, defect detection, process control and sorting.&nbsp;AI has helped spur a shift from rule-based machine vision to AI-powered inspection, which has allowed machine vision to handle tasks that previously required human inspectors. For instance, cosmetic defects can be challenging for rule-based machine vision to detect, but AI-powered machine-vision systems learn autonomously by analyzing multiple examples of defects, interpreting data, learning from patterns and making decisions. Machine vision also allows companies to better comply with regulations and enhance worker safety on the factory floor.<h2>China, AGVs and AMRs</h2>We think the warehouse-automation market is at a critical inflection point, transitioning from rigid, fixed-path Automated Guided Vehicles (AGVs) to intelligent, flexible Autonomous Mobile Robots (AMRs). This shift has been propelled by the rapid growth of e-commerce, critical labor shortages, and the strategic need for supply-chain resilience.&nbsp;We think the total addressable market for warehouse-automation systems will increase by ~11% CAGR to some $112 billion in 2029, and one IPO prospectus leads us to expect about 20% of this total addressable market to fall into AGVs and AMRs.&nbsp;China’s national strategies have provided a powerful impetus for the development of intelligent logistics and robotics, creating a uniquely favorable environment for domestic companies. Policy support extends beyond production subsidies to the more ambitious goal of creating an entire industrial ecosystem. This state-led industrial strategy provides a significant long-term advantage over competitors in nations lacking a coordinated industrial policy, and its success is already evident: In 2024, Chinese AMR solution providers accounted for about half of the global market share. This has created a virtuous cycle, with state support ultimately driving technological maturity and global expansion.But significant barriers to adoption of AMRs exist. These include high upfront capital costs, complex integration with legacy systems, and a critical labor-skills gap. One major technical challenge is integrating AMR systems with existing Warehouse Management Systems (WMS) and Enterprise Resource Planning software. A critical issue is the speed mismatch: Robots operate at millisecond-level speeds while many legacy WMS platforms lack real-time processing capabilities. Automation also requires a fundamental shift in the workforce from manual labor to technical roles involving robotic systems’ operation and maintenance.We think the global AMR market could surge 33% to some $22 billion in 2029, with the market continuing to bifurcate. AGVs will remain relevant for simple, repetitive, point-to-point transport tasks in stable manufacturing environments, but the high-growth, high-margin opportunities will be concentrated in dynamic, complex environments such as e-commerce fulfillment, with such environments demanding the flexibility and intelligence offered by AMRs.We see the future of competition less about robotic hardware than about the software ecosystem orchestrating that hardware, and we think the long-term winners will be the companies that master the software, AI and integration complexities of modern logistics. AMR pure plays are best positioned to lead the industry into its next phase, thanks to software-native DNA and their proven success in the most demanding fulfillment environments. The key strategic question for incumbents is whether they can make a successful transition from manufacturing hardware to providing integrated software and solutions before the technology gap becomes insurmountable.

Our new report, Embodied Intelligence: The Rise of Physical AI, also discusses stock implications of these trends. It’s available in full to existing Citi Research clients <a href="https://www.citivelocity.com/t/eppublic/4C2ev" target="_blank">here</a>.

We expect Physical AI in industrial markets to accelerate in the coming years, with opportunities in the cloud and at the edge. As data are AI's fuel, we see large data-gathering physical installed bases and domain-specific know-how as key enablers (and moats) for industrial companies.

Embodied Intelligence: The Rise of Physical AI

<ul><li>Physical AI marks a critical evolution beyond traditional automation and robotics, integrating AI into real-world physical processes to enable unprecedented design optimization and autonomy across industries</li><li>The widespread deployment of IoT and digital twins provides the essential data and simulation environments, serving as the foundational building blocks for Physical AI's self-learning and optimization capabilities</li><li>Physical AI adoption is positioned for substantial industrial growth, driven by increasing efficiency demands and labor challenges, leading to a potential re-allocation of capital expenditures and accelerated productivity gains</li></ul>

Elise Badoy, Head of Europe, UK, Middle East and Africa Equity Research, sits down with Martin Wilkie, Head of Capital Goods Research, to discuss physical AI, how it's transforming industrial processes, and why advances in robotics are about more than humanoid designs.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.

Elise Badoy is a Managing Director and Head of Equity Research in EMEA. Elise joined Citi in February 2010 and is a member of the Global Research Executive Committee. Prior to Citi, Elise worked at Goldman Sachs from 1999 to 2009, initially on the buy-side at GSAM and from 2001 in GS's Global Investment Research division covering the Consumer Staples sector. Prior to joining Goldman Sachs, she worked at Daiwa Securities in Equity Capital Markets and at ING Barings in Investment Banking.

Elise Badoy, Head of Europe, UK, Middle East and Africa Equity, Citi Research

Martin Wilkie heads the European Capital Goods Research team and also heads the Global Capital Goods research pod and the Automation Theme Group at Citi Research. He has been an industrials analyst since 2003, having had various other roles in banking since 1994. He is based in London and started with Citi in 2015. Martin previously worked at Deutsche Bank from 2006 to 2015 also covering the Capital Goods sector, having also worked previously at Morgan Stanley and JP Morgan.

 Martin Wilkie, Head of Capital Goods, Citi Research

Elise Badoy, Head of Europe, UK, Middle East and Africa Equity Research, sits down with Martin Wilkie, Head of Capital Goods Research, to discuss physical AI, how it's transforming industrial processes, and why advances in robotics are about more than humanoid designs.

/rcs/citigpa/storage/public/Episode-62-Research-FINAL-TRANSCRIPT.pdf

E62: The Rise of Physical AI and What It Means for Us

<ul><li>Citi Research identifies AI as a primary megatrend driving substantial growth for industrial companies in power thermal and electrical management sectors positioning them as key AI enablers</li><li>Despite potential capacity constraints AI capital expenditure continues to fuel strong double-digit revenue growth and operating margin expansion for industrials with peak investment still years out</li><li>Beyond direct AI investments, a broader industrial rebound is emerging supported by deglobalization "build in America" initiatives and fiscal policies broadening market opportunities</li></ul>

Anne Malone, North America Head of Research, sits down with Andrew Kaplowitz, Head of U.S. Industrials Research, to discuss themes shaping Industrials in 2026. The lead theme is AI, with capex growth permeating everything in the sector. But topics from the broadening thesis to M&amp;A and U.S. federal policy are also attracting investor attention.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. Copyright 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.

Anne Malone was named Head of North America and Latin America Equity Research 2022; promoted from Deputy Director, a role she held since 2018. Anne started at the firm in 1996 as an Analyst covering Medical Technology stocks. She has held several positions since then, in both Equity Research and Citi Asset Management, taking on roles that utilized her analytical, product, and people skills. Prior to joining Citi she was a Medical Device Analyst at Bear Stearns. Anne graduated from the St Leo College with a degree in Finance and a minor in Economics. She is a CFA Charter holder. &nbsp;

Anne Malone, Head of North America and Latin America Equity Research

Andy Kaplowitz is a Managing Director and U.S. Industrial Sector Head covering the Multi-Industry / Conglomerates and Engineering &amp; Construction sectors. Prior to joining Citi Research in 2015, Andy had several roles in equity research for Barclays/Lehman Brothers from 2001 through 2015. Andy most recently was a Managing Director covering Machinery and Engineering Construction at Barclays since 2011. Prior to that, Andy was a Senior Analyst covering Engineering and Construction stocks since 2006 and Mining Equipment since 2008. Andy has been a Top 3-ranked analyst in Engineering and Construction from 2009 through 2016 in Institutional Investor’s annual All America Research Poll and also held a runner-up position in Machinery from 2012 through 2014. &nbsp;Andy holds a Bachelor of Arts degree from Rutgers University and an MBA degree from the Kellogg School of Management. &nbsp;

Andrew Kaplowitz, Head of U.S. Industrials Research

Anne Malone, North America Head of Research, sits down with Andrew Kaplowitz, Head of U.S. Industrials Research, to discuss themes shaping Industrials in 2026. The lead theme is AI, with capex growth permeating everything in the sector. But topics from the broadening thesis to M&amp;A and U.S. federal policy are also attracting investor attention.

/rcs/citigpa/storage/public/Episode-65-TRANSCRIPT.pdf

E65: You Can’t Spell Industrials Without “AI"

Download Report 

Supercharged - AI and the New Age of Disruption

Technology has always had the power to reshape societies. But the current wave of disruption – driven by advances in artificial intelligence – is unfolding at dizzying pace and on an unprecedented scale. Unlike previous technological revolutions, which generally took decades, AI is firing change across industries, institutions and societies in real time. It’s a challenge just to keep up.This Citi Institute report, which accompanies Citi’s DisrupTech conference being hosted in London in March, focuses on a few areas of disruptive technology, taking in innovations themselves, but also the shifts they will drive.&nbsp;

<ul style="list-style-type:disc;"><li>Autonomous driving and humanoids: Two of the biggest technological shifts gaining momentum today are autonomous mobility and the rise of humanoid and physical AI-enabled robots. They represent a structural innovation cycle with far-reaching implications for productivity, demographics, capital allocation, labor markets and competition.</li><li>NextGen AI companies: The new wave of AI software companies are likely to focus on integrated and agentic AI platforms and huge investments in computing infrastructures, networking and data pipelines. The challenge will be to scale responsibly.</li><li>The rise of quantum computing: Three themes dominate long-term strategic positioning: the physical limits of classical computing and the need for new architectures, the infrastructural intensity of AI scale-up and the disruptive trajectory of quantum capability. &nbsp;</li></ul>

Report Highlights 

AI and the New Age of Disruption

Technology has always had the power to reshape societies. But the current wave of disruption – driven by advances in artificial intelligence – is unfolding at dizzying pace and on an unprecedented scale. Unlike previous technological revolutions, which generally took decades, AI is firing change across industries, institutions and societies in real time. &nbsp;&nbsp;

Supercharged

<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 

<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

HIGHLIGHTS

Related Stories

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

E62: The Rise of Physical AI and What It Means for Us

Embodied Intelligence: The Rise of Physical AI

Sign up to receive the latest insights from Citi.