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Stanford Develops Real-World Benchmarks for Healthcare AI Agents

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Beyond the hype and hope surrounding the use of artificial intelligence in medicine lies the real-world need to ensure that, at the very least, AI in a healthcare setting can carry out tasks that a doctor would in electronic health records.

Creating benchmark standards to measure that is what drives the work of a team of Stanford researchers. While the researchers note the enormous potential of this new technology to transform medicine, the tech ethos of moving fast and breaking things doesn’t work in healthcare. Ensuring that these tools are capable of doing these tasks is vital, and then they can be used as tools that augment the care clinicians provide every day.

“Working on this project convinced me that AI won’t replace doctors anytime soon,” said Kameron Black, co-author on the new benchmark paper and a Clinical Informatics Fellow at Stanford Health Care. “It’s more likely to augment our clinical workforce.”

MedAgentBench: Testing AI Agents in Real-World Clinical Systems

Black is one of a multidisciplinary team of physicians, computer scientists, and researchers from across Stanford University who worked on the new study, MedAgentBench: A Virtual EHR Environment to Benchmark Medical LLM Agents, published in the New England Journal of Medicine AI.

Although large language models (LLMs) have performed well on the United States Medical Licensing Examination (USMLE) and at answering medical-related questions in studies, there is currently no benchmark testing how well LLMs can function as agents by performing tasks that a doctor would normally do, such as ordering medications, inside a real-world clinical system where data input can be messy. 

Unlike chatbots or LLMs, AI agents can work autonomously, performing complex, multistep tasks with minimal supervision. AI agents integrate multimodal data inputs, process information, and then utilize external tools to accomplish tasks, Black explained. 

Overall Success Rate (SR) Comparison of State-of-the-Art LLMs on MedAgentBench

Model

Overall SR

Claude 3.5 Sonnet v2

69.67%

GPT-4o

64.00%

DeepSeek-V3 (685B, open)

62.67%

Gemini-1.5 Pro

62.00%

GPT-4o-mini

56.33%

o3-mini

51.67%

Qwen2.5 (72B, open)

51.33%

Llama 3.3 (70B, open)

46.33%

Gemini 2.0 Flash

38.33%

Gemma2 (27B, open)

19.33%

Gemini 2.0 Pro

18.00%

Mistral v0.3 (7B, open)

4.00%

While previous tests only assessed AI’s medical knowledge through curated clinical vignettes, this research evaluates how well AI agents can perform actual clinical tasks such as retrieving patient data, ordering tests, and prescribing medications. 

“Chatbots say things. AI agents can do things,” said Jonathan Chen, associate professor of medicine and biomedical data science and the paper’s senior author. “This means they could theoretically directly retrieve patient information from the electronic medical record, reason about that information, and take action by directly entering in orders for tests and medications. This is a much higher bar for autonomy in the high-stakes world of medical care. We need a benchmark to establish the current state of AI capability on reproducible tasks that we can optimize toward.”

The study tested this by evaluating whether AI agents could utilize FHIR (Fast Healthcare Interoperability Resources) API endpoints to navigate electronic health records.

The team created a virtual electronic health record environment that contained 100 realistic patient profiles (containing 785,000 records, including labs, vitals, medications, diagnoses, procedures) to test about a dozen large language models on 300 clinical tasks developed by physicians. In initial testing, the best model, in this case, Claude 3.5 Sonnet v2, achieved a 70% success rate.

“We hope this benchmark can help model developers track progress and further advance agent capabilities,” said Yixing Jiang, a Stanford PhD student and co-author of the paper.

Many of the models struggled with scenarios that required nuanced reasoning, involved complex workflows, or necessitated interoperability between different healthcare systems, all issues a clinician might face regularly. 

“Before these agents are used, we need to know how often and what type of errors are made so we can account for these things and help prevent them in real-world deployments,” Black said.

What does this mean for clinical care? Co-author James Zou and Dr. Eric Topol claim that AI is shifting from a tool to a teammate in care delivery. With MedAgentBench, the Stanford team has shown this is a much more near-term reality by showcasing several frontier LLMs in their ability to carry out many day-to-day clinical tasks that a physician would perform. 

Already the team has noticed improvements in performance of the newest versions of models. With this in mind, Black believes that AI agents might be ready to handle basic clinical “housekeeping” tasks in a clinical setting sooner than previously expected. 

“In our follow-up studies, we’ve shown a surprising amount of improvement in the success rate of task execution by newer LLMs, especially when accounting for specific error patterns we observed in the initial study,” Black said. “With deliberate design, safety, structure, and consent, it will be feasible to start moving these tools from research prototypes into real-world pilots.”

The Road Ahead

Black says benchmarks like these are necessary as more hospitals and healthcare systems are incorporating AI into tasks including note-writing and chart summarization.

Accurate and trustworthy AI could also help alleviate a looming crisis, he adds. Pressed by patient needs, compliance demands, and staff burnout, healthcare providers are seeing a worsening global staffing shortage, estimated to exceed 10 million by 2030.

Instead of replacing doctors and nurses, Black hopes that AI can be a powerful tool for clinicians, lessening the burden of some of their workload and bringing them back to the patient bedside. 

“I’m passionate about finding solutions to clinician burnout,” Black said. “I hope that by working on agentic AI applications in healthcare that augment our workforce, we can help offload burden from clinicians and divert this impending crisis.”

Paper authors: Yixing Jiang, Kameron C. Black, Gloria Geng, Danny Park, James Zou, Andrew Y. Ng, and Jonathan H. Chen

Read the piece in the New England Journal of Medicine AI.



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How Artificial Intelligence May Trigger Delusions and Paranoia

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September 16, 2025

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Introduction
What is AI psychosis?
Potential causes and triggers
Impacts on mental health
Challenges in recognition and diagnosis
Managing and addressing AI psychosis
Future directions
Conclusions
References
Further reading

AI psychosis describes how interactions with artificial intelligence can trigger or worsen delusional thinking, paranoia, and anxiety in vulnerable individuals. This article explores its causes, mental health impacts, challenges in diagnosis, and strategies for prevention and care.

Image Credit: Drawlab19 / Shutterstock.com

Introduction

‘Artificial intelligence (AI) psychosis’ is an emerging concept at the intersection of technology and mental health that reflects how AI can shape, and sometimes distort, human perception. As society becomes increasingly reliant on AI and digital tools ranging from virtual assistants to large language models (LLMs), the boundaries between fiction and reality become increasingly blurred.1

AI mental health applications promise scalable therapeutic support; however, editorials and observational reports now warn that interactions with generative AI chatbots may precipitate or amplify delusional themes in vulnerable users. In the modern era of rapid technological innovation, the pervasive presence of AI raises pressing questions about its potential role in the onset or worsening of psychotic symptoms.1,2

What is AI psychosis?

AI psychosis is a novel phenomenon within AI mental health that is characterized by delusions, paranoia, or distorted perceptions regarding AI. Unlike traditional psychosis, which may involve persecutory or mystical beliefs about governments, spirits, or other external forces, AI psychosis anchors these experiences in technology.

Reports and editorials describe a broad spectrum of AI psychosis, with minor cases involving individuals dreading surveillance or manipulation by algorithms, voice assistants, or recommender systems. Others attribute human intentions or supernatural powers to chatbots and, as a result, treat them as oracles or divine messengers.1,2

Compulsive interactions with AI can escalate into fantasies of prophecy, mystical knowledge, or messianic identity. Some accounts report the emergence of paranoia and mission-like ideation alongside misinterpretations of chatbot dialogues.2

AI psychosis is distinct from other technology-related disorders. For example, internet addiction involves compulsive online engagement, whereas cyberchondria reflects health-related anxiety triggered by repeated online searches. Both of these conditions involve problematic internet use; however, they lack core psychotic features such as fixed false beliefs or impaired reality testing; by contrast, “AI psychosis” refers to psychotic phenomena anchored in technology.3

What to know about ‘AI psychosis’ and the effect of AI chatbots on mental health

Potential causes and triggers

AI psychosis arises from a complex interaction of technological exposure, cognitive vulnerabilities, and cultural context. Overexposure to AI systems is a key factor, as constant engagement with chatbots, voice assistants, or algorithm-driven platforms can create compulsive use and feedback loops that reinforce delusional themes. Designed to maximize engagement, AI may unintentionally validate distorted beliefs, thereby eroding the user’s ability to distinguish between perception and reality.1

Deepfakes, synthetic text, and AI-generated images also distort the line between authentic and fabricated content. For individuals at a greater risk of epistemic instability, this can exacerbate confusion, paranoia, and self-deception.1,2

Cultural and media narratives also influence the risk of AI psychosis. Dystopian films, science-fiction depictions of sentient machines, and portrayals of AI as controlling or invincible may prime users to interpret ordinary AI interactions as conspiracies and fear, increasing anxiety and mistrust.1,2

Underlying vulnerabilities play a critical role, as individuals with pre-existing psychiatric or anxiety disorders are particularly susceptible to AI psychosis. AI interactions can mirror or intensify existing symptoms to transform intrusive thoughts into validated misconceptions or paranoid panic.1,2

Impacts on mental health

AI psychosis frequently presents as heightened anxiety, paranoia, or delusional thinking linked to digital interactions. Individuals may interpret chatbots as sentient companions, divine authorities, or surveillance agents, with AI responses strengthening spiritual crises, messianic identities, or conspiratorial terror. Within AI mental health, these dynamics exemplify how misinterpreted machine outputs can aggravate psychotic symptoms, particularly in vulnerable users.2,4

A central consequence of AI psychosis is social withdrawal and mistrust of technology. Affected individuals may develop emotional or divine-like attachments to AI systems, perceiving conversational mimicry as genuine love or spiritual guidance, which can replace meaningful human relationships. This bond, coupled with reinforced misinterpretations, often leads to isolation from family, friends, and clinicians.

Parallel to the conspiracy-driven mistrust observed during the coronavirus disease 2019 (COVID-19) pandemic, during which false beliefs spread that 5G towers caused the outbreak, persuasive AI narratives can reduce confidence in technology and reinforce avoidance of platforms perceived as threatening or manipulative.5

While AI holds promise in schizophrenia care, evidence directly linking AI interactions to exacerbation of schizophrenia-spectrum disorders remains limited; hypotheses focus on indirect pathways (e.g., misclassification or misinformation) rather than established causal effects.2,9

AI psychosis has broader implications for healthcare, education, and governance systems reliant on AI. Perceived deception or harm from AI-driven platforms can jeopardize public trust, prevent the adoption of beneficial technologies, and compromise the use of mental health applications.

To mitigate these risks, AI systems must include lucid, ethical safeguards and explainable “glass-box” models. Complementary legal and governance frameworks should prioritize transparency, accountability, fairness, and protections for at-risk populations.1,13

Image Credit: Miha Creative / Shutterstock.com

Challenges in recognition and diagnosis

A major challenge in AI mental health is that AI psychosis currently lacks formal psychiatric categorization. At present, it is not defined in DSM-5 (or DSM-5-TR) or in ICD-11.7

Machine learning behaviors that resemble psychotic symptoms, like misapprehensions or hallucinations, are manifestations of AI programming and data, rather than being signs of a mental illness with biological and neurological underpinnings. The absence of standardized criteria complicates both research and clinical recognition.

Distinguishing between rational concerns about AI ethics and pathological fears is particularly difficult. For example, rational anxieties like privacy breaches, algorithmic bias, or job displacement are grounded in observable risks.

In contrast, pathological fright central to AI psychosis involves exaggerated or existential anxieties, misinterpretations of AI outputs, and misattribution of intent to autonomous systems. Determining whether an individual’s fear reflects legitimate caution or symptomatic fallacy requires careful clinical assessment.8

These factors contribute to a significant risk of underdiagnosis or mislabeling. AI-generated data and predictive models can assist in mental health assessment, yet they may struggle to differentiate overlapping psychiatric symptoms, especially in complex or comorbid presentations.

Variability in patient reporting, cultural influences, and the opaque ‘black box’ nature of many AI algorithms further increase the potential for diagnostic errors. 2,9

Managing and addressing AI psychosis

Clinical management of AI psychosis combines traditional psychiatric care with targeted interventions that address technology-related factors. Psychotic symptoms may be treated with medication, while cognitive behavioral therapy (CBT) can be adapted to help patients challenge their misbeliefs shaped by digital systems. Furthermore, psychoeducation materials can outline the risks and limitations of AI engagement for patients and families to promote safe and informed use.10,11

Preventive strategies include limiting exposure to AI and fostering critical digital literacy. Encouraging users to question AI outputs, cross-check information, and maintain real-world interactions can reduce susceptibility to twisted perceptions.4

Responsible AI design should incorporate protective features, transparent decision-making processes, and controls on engagement with sensitive or misleading content to minimize psychological risks. Setting clear boundaries for AI use and prioritizing human connection further support prevention.

Support systems play a central role in managing AI psychosis. Mental health professionals can oversee AI-driven insights to provide a nuanced understanding, intervene in complex cases where AI may be inadequate, and deliver empathetic care that AI cannot replicate.13

Increasing family awareness through community intervention measures, including early detection programs, may also identify individuals at risk of AI psychosis and promote timely intervention. AI can augment (but not replace) these efforts via mood tracking, crisis prediction, and personalized self-care tools when deployed with human oversight.10

Future directions

Understanding how psychiatric vulnerabilities are associated with technology-driven explanation-seeking behaviors will enable clinicians to recognize risk factors, identify early warning signs, and effectively personalize interventions. Large-scale studies and longitudinal monitoring could clarify prevalence, triggers, and outcomes, particularly in adolescents and other at-risk populations.1,9

AI-assisted psychosis risk screening can provide real-time, non-perceptual assessments to facilitate the early detection of symptoms and enable prompt action. Future efforts should focus on increasing accessibility, reducing costs, and enhancing usability to ensure widespread acceptance in mental health care settings without replacing human clinical judgment.12

Mitigating AI psychosis requires coordinated efforts among policymakers, ethicists, and AI developers. Policymakers should create flexible regulations that prioritize safety, equity, and public trust, while ethicists provide oversight, impact assessments, and ethical frameworks.

AI developers must also ensure transparency, accountability, and fairness by continuously checking for bias, protecting data, and educating individuals about the use of AI. Continued collaboration among these stakeholders is essential for trustworthy AI tools that support mental health and minimize unintended harms.13

Conclusions

Although AI offers significant benefits for enhancing diagnostics, supporting interventions, and increasing access to care, its integration into daily life also introduces novel risks for vulnerable individuals, including delusional thinking and paranoia. Therefore, a balanced perspective that acknowledges both the potential advantages and hazards associated with these novel technologies is essential.

Effectively addressing AI psychosis requires urgent, sustained collaboration between mental health professionals and AI researchers to develop ethical, evidence-based strategies that protect AI mental health while responsibly leveraging technological innovations. 

References

  1. Higgins, O., Short, B. L., Chalup, S. K., & Wilson, R. L. (2023). Interpretations of Innovation: The Role of Technology in Explanation Seeking Related to Psychosis. Perspectives in Psychiatric Care, 1, 4464934. DOI:10.1155/2023/4464934, https://onlinelibrary.wiley.com/doi/10.1155/2023/4464934
  2. Østergaard, S. D. (2023). Will Generative Artificial Intelligence Chatbots Generate Delusions in Individuals Prone to Psychosis? Schizophrenia Bulletin 49(6), 1418. DOI:10.1093/schbul/sbad128, https://academic.oup.com/schizophreniabulletin/article/49/6/1418/7251361
  3. Khait, A. A., Mrayyan, M. T., Al-Rjoub, S., Rababa, M., & Al-Rawashdeh, S. (2022). Cyberchondria, Anxiety Sensitivity, Hypochondria, and Internet Addiction: Implications for Mental Health Professionals. Current Psychology, 1. DOI:10.1007/s12144-022-03815-3, https://link.springer.com/article/10.1007/s12144-022-03815-3
  4. Pierre J. M. (2020). Mistrust and misinformation: a two-component, socio-epistemic model of belief in conspiracy theories, Journal of Social and Political Psychology, 8(2):617-641. DOI:10.5964/jspp.v8i2.1362, https://jspp.psychopen.eu/index.php/jspp/article/view/5273
  5. Bruns A., Harrington S., & Hurcombe E. (2020). ‘Corona? 5G? or both?’: the dynamics of COVID-19/5G conspiracy theories on Facebook, Media International Australia 177(1), 12-29. DOI:10.1177/1329878×20946113, https://journals.sagepub.com/doi/10.1177/1329878X20946113
  6. Szmukler, G. (2015). Compulsion and “coercion” in mental health care. World Psychiatry, 14(3), 259. DOI:10.1002/wps.20264, https://onlinelibrary.wiley.com/doi/10.1002/wps.20264
  7. Gaebel, W., & Reed, G. M. (2012). Status of Psychotic Disorders in ICD-11. Schizophrenia Bulletin 38(5), 895. DOI:10.1093/schbul/sbs104, https://academic.oup.com/schizophreniabulletin/article/38/5/895/1902333
  8. Alkhalifah, J. M., Bedaiwi, A. M., Shaikh, N., et al. (2024). Existential anxiety about artificial intelligence (AI)- is it the end of the human era or a new chapter in the human revolution? Questionnaire-based observational study. Frontiers in Psychiatry 15. DOI:10.3389/fpsyt.2024.1368122, https://www.frontiersin.org/articles/10.3389/fpsyt.2024.1368122/full
  9. Melo, A., Romão, J., & Duarte, T. A. (2024). Artificial Intelligence and Schizophrenia: Crossing the Limits of the Human Brain. Edited by Cicek Hocaoglu, New Approaches to the Management and Diagnosis of Schizophrenia. IntechOpen. DOI:10.5772/intechopen.1004805, https://www.intechopen.com/chapters/1185407
  10. Vignapiano, A., Monaoc, F., Panarello, E., et al. (2024). Digital Interventions for the Rehabilitation of First-Episode Psychosis: An Integrated Perspective. Brain Sciences, 15(1), 80. DOI:10.3390/brainsci15010080, https://www.mdpi.com/2076-3425/15/1/80
  11. Thakkar, A., Gupta, A., & Sousa, A. D. (2024). Artificial intelligence in positive mental health: A narrative review. Frontiers in Digital Health 6. DOI:10.3389/fdgth.2024.1280235, https://www.frontiersin.org/articles/10.3389/fdgth.2024.1280235/full
  12. Cao, J., & Liu, Q. (2022). Artificial intelligence-assisted psychosis risk screening in adolescents: Practices and challenges. World Journal of Psychiatry, 12(10), 1287. DOI:10.5498/wjp.v12.i10.1287, https://www.wjgnet.com/2220-3206/full/v12/i10/1287.htm
  13. Pham, T. (2025). Ethical and legal considerations in healthcare AI: Innovation and policy for safe and fair use. Royal Society Open Science 12(5), 241873. DOI:10.1098/rsos.241873, https://royalsocietypublishing.org/doi/10.1098/rsos.241873

Further Reading

Last Updated: Sep 16, 2025



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Tabs Raises $55 Million for AI Agents for Finance Teams

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September 16, 2025

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Tabs raised $55 million in a Series B funding round to accelerate its development of artificial intelligence agents for finance teams.

The company’s AI-native platform automates the contract-to-cash cycle, enabling faster invoicing, automated collections, real-time revenue recognition and faster month-end close, according to a Tuesday (Sept. 16) press release.

Founded in 2023, Tabs now serves more than 200 customers and automates over $500 million in annual invoice volume, the release said.

The most recent additions to the platform are two AI agents: billing agents that sync with the user’s customer relationship management (CRM) and enterprise resource planning (ERP) systems, read contracts, and create and send invoices; and collections agents that monitor due dates and automatically match and reconcile payments, per the release.

“Revenue in is the hardest and most valuable workflow in the enterprise, yet finance teams are still stuck with legacy ERPs,” Tabs CEO and co-founder Ali Hussain said in the release. “Tabs is bringing modern AI agents to the CFO’s office, starting with billing, complex enterprise contract management and collections, so companies can collect cash faster and reduce time spent on manual work.”

Justin Overdorff, partner at Lightspeed Venture Partners, which led the funding round, said in the release that Tabs is “eliminating manual processes that have plagued revenue workflows for decades.”

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“The team has combined deep finance expertise with purpose-built AI agents for revenue processing and tracking, and the rapid customer adoption we’re seeing validates just how ready the market is for this transformation,” Overdorff said.

Tabs raised $25 million in Series A funding in October 2024 and $7 million in seed funding in April 2024.

In June 2024, the company added a revenue recognition capability to its platform, saying this module helps businesses manage and recognize revenue, ensure compliance with accounting standards, and improve accuracy and efficiency.

The PYMNTS Intelligence report “Window of Opportunity: Gaining AR Transparency Through Automation” found that when companies adopt digital and automated accounts receivable processes, they can close visibility gaps and build stronger relationships with suppliers and customers.

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US-UK pact will boost advances in drug discovery, create tens of thousands of jobs and transform lives

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2 hours ago

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September 16, 2025

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  • Transatlantic pact to speed up world-leading AI research to help develop new drugs, faster life-saving treatments and improved cancer care
  • Alliance ushers in golden age of nuclear technology, delivering clean, homegrown energy and unlocking high-paying jobs for the British people
  • North East set to become new AI Growth Zone – creating potential for more than 5,000 jobs and billions in private investment – as well as major deal struck between British firm Nscale and leading American firms NVIDIA and OpenAI to deliver a Stargate UK
  • Comes as American tech firms back historic agreement pouring more than £31 billion into the UK AI and tech infrastructure, including Microsoft’s largest ever commitment to the UK

As part of the US President’s State Visit, the UK and US have agreed the Tech Prosperity Deal, focused on developing the fastest growing technologies like AI, quantum, and nuclear.

This comes as America’s top technology and AI firms – like Microsoft, NVIDIA, Google, OpenAI and CoreWeave – commit a combined £31 billion to boost the UK’s AI infrastructure and cutting-edge tech, from data centres to computer chips, the processing power behind AI. Today’s commitments build on the £44 billion in investment into the UK’s AI and tech sector under this government.

Under the partnership, the UK and US will put joint resources and expertise into making emerging technologies a shared success for British and American people:

  • millions of patients could receive life-saving treatments faster, as the UK and US partner up to develop revolutionary quantum computers and open new avenues to use AI in targeted treatments which can aid drug discovery. Technologies like AI and quantum – which can also be applied in many ways across healthcare, energy, space and defence – can bring breakthroughs like new medicines and treatments in a fraction of the time and cost it takes today.
  • families could get access to cleaner, more reliable energy, thanks to a civil nuclear deal that will slash red tape and speed up the delivery of nuclear projects. It means British consumers could be more protected from international fossil fuel price hikes and British workers could benefit from high-paying jobs unlocked by these projects.
  • local communities and businesses will see greater opportunities through investment and rollout of AI infrastructure in both countries, creating jobs and driving growth. A new AI Growth Zone in the North East has the potential to see billions of pounds worth of investment and jobs funnelled into the region. With leading US tech companies joining forces with British firm Nscale to build out AI infrastructure, British businesses will have access to the cutting-edge chips they need to adopt AI, innovate and compete.

As part of the pact, the UK and US will unite to forge joint research schemes to further the use of AI to allow for targeted treatments and other shared priorities like fusion energy. This could see both countries working together to build new AI models for life-changing breakthroughs like developing targeted treatments for those suffering with cancer or rare and chronic diseases. 

This landmark deal is already bearing fruit. A raft of investments and partnerships worth a combined £31 billion have been injected into the UK today – focused on building new data centres and growing AI start-ups, cutting-edge tech, as well as developing advanced quantum computers. 

Prime Minister Keir Starmer said:  

This Tech Prosperity Deal marks a generational step change in our relationship with the US, shaping the futures of millions of people on both sides of the Atlantic, and delivering growth, security and opportunity up and down the country.

By teaming-up with world-class companies from both the UK and US, we’re laying the foundations for a future where together we are world leaders in the technology of tomorrow, creating highly skilled jobs, putting more money in people’s pockets and ensuring this partnership benefits every corner of the United Kingdom.

Technology Secretary Liz Kendall said:

This partnership will deliver good jobs, life-saving treatments and faster medical breakthroughs for the British people.

Our world-leading tech companies and scientists will be working together to transform lives across Britain.

This is a vote of confidence in Britain’s booming AI sector – building on British success stories such as Arm, Wayve and Google Deepmind – that will boost growth and deliver tens of thousands of skilled jobs.

Boosting the UK’s status as an AI maker, NVIDIA will join forces with companies across the UK to deploy 120,000 advanced GPUs across the UK, representing its biggest ever rollout in Europe to date. This infrastructure is the building block of AI technology, able to carry out a huge number of calculations in a split second.

This includes the deployment of up to 60,000 NVIDIA Grace Blackwell Ultra GPUs from British firm Nscale who will partner with OpenAI to deliver a Stargate UK project and establish a partnership with Microsoft to deliver the UK’s largest AI supercomputer in Loughton.

One of the areas set to benefit is the North East, where a new AI Growth Zone will be established and is expected to host some of the initial deployment of the Stargate UK project at Cobalt Park.

Semiconductor designs by leading British chip design company Arm form part of Nvidia’s latest Grace Blackwell series of chips, demonstrating further collaboration between UK and US companies.

Further investment in data centres – the factories powering AI – as well as start-ups in AI and beyond is also being set out:

  • Microsoft is announcing a $30 billion (£22 billion) investment in AI infrastructure and ongoing operations across the UK – marking the largest financial commitment it has ever made in the UK. It will enable Microsoft to build out the UK’s cloud and AI infrastructure and build the country’s largest supercomputer, with more than 23,000 advanced GPUs, in partnership with Nscale. Microsoft has invested in the United Kingdom for more than 4 decades and is now home to 6,000 Microsoft employees, multiple data centre regions, and some of its most important AI and Research Labs, and gaming studios.

  • Google is announcing the opening of its data centre in Waltham Cross, Hertfordshire, as part of a 2-year £5 billion investment in the UK. This includes Google’s capital expenditure, research and development, and related engineering over the next 2 years – and encompasses Google DeepMind with its pioneering AI research in science and healthcare. The investments will help the UK develop its AI economy and unlock AI breakthroughs across the UK, fortify cybersecurity, and create future-focused career opportunities for millions of Brits. Google’s investment is projected to create 8,250 jobs annually at UK businesses.

  • AI cloud computing company CoreWeave will be investing £1.5 billion in AI data centre capacity and operations in the UK – bringing total investment in the UK to £2.5 billion over the past year. As part of this investment, CoreWeave is partnering with British firm DataVita in Scotland to build one of Europe’s largest, most efficient AI data centres. It will deliver advanced compute powered by renewable energy, whilst creating local jobs and contributing to the local economy.

  • Salesforce has today announced an additional $2 billion (£1.4 billion) in investment in its UK business through 2030. Salesforce UK will become an AI hub for the UK and Europe with new R&D teams to support business innovation across the region. The investment bolsters Salesforce’s ongoing commitment to the UK, extending a previous 5-year investment of $4 billion made in 2023, bringing the total investment to $6 billion.

  • UK-based company AI Pathfinder has committed to delivering AI compute capacity – essential to developing and deploying AI. This will begin in Northamptonshire, with an initial investment of over £1 billion.

  • NVIDIA will also invest in the UK’s AI start-up scene – providing fresh capital for domestic tech companies to grow, get innovative AI technologies off the ground and to market, and compete on the global stage. 

  • techUK is collaborating with NVIDIA, alongside robotics and automation leader Quanser and training provider QA, to deliver a program that connects its members, robotics researchers, and startups with funding, training, and industry collaboration opportunities to make the most of AI.

  • Scale AI will invest £39 million in the UK over the next 2 years, expanding their European HQ in London and quadrupling its employees by the end of next year.

  • BlackRock is investing £500 million into enterprise data centres across the country, which includes an initial investment of over £100 million in a data centre expansion west of London. The broader programme will enhance UK digital infrastructure.

Founder and CEO of NVIDIA Jensen Huang said:

Today marks a historic chapter in U.S. – United Kingdom technology collaboration.

We are at the Big Bang of the AI era – and the United Kingdom stands in a Goldilocks position, where world-class talent, research and industry converge.

By building state-of-the-art AI infrastructure and investing in British startups, we are unlocking the power of AI for the U.K. – fuelling breakthroughs, creating jobs, and igniting the next industrial revolution.

Sam Altman, CEO of OpenAI, said:

The UK has been a longstanding pioneer of AI, and is now home to world-class researchers, millions of ChatGPT users, and a government that quickly recognized the potential of this technology. Stargate UK builds on this foundation to help accelerate scientific breakthroughs, improve productivity, and drive economic growth. This partnership reflects our shared vision that with the right infrastructure in place, AI can expand opportunity for people and businesses across the UK.

Josh Payne, Nscale CEO said:

We’re delighted to announce Nscale’s commitment to UK AI infrastructure today, including through Stargate UK and building the most powerful supercomputer in the country with Microsoft. As a UK-based company, we’re showing how we can be makers, not takers, of the most important technology of our time.

Rene Haas, CEO of Arm:

The launch of Stargate UK represents a critical step in expanding Britain’s AI computing power and digital infrastructure. As a company founded and headquartered in the UK, Arm is proud to be at the forefront of the nation’s semiconductor plans and to be a technology partner for Stargate UK, delivering the computing platform that makes scalable, energy-efficient AI possible.

Satya Nadella, Chairman and CEO, Microsoft:

We’re committed to creating new opportunity for people and businesses on both sides of the Atlantic, and to ensuring America remains a trusted and reliable tech partner for the United Kingdom.

That is why we are doubling down on our investment in the UK, investing more than $30 billion over 4 years, including building the country’s largest supercomputer.

This follows renewed commitments from US companies Oracle and Amazon Web Services in the UK. Oracle has committed to expanding the AI infrastructure it provides to the UK government reaffirming their $5 billion investment over the next 5 years. Whilst Amazon also earlier this year announced a commitment to build and operate data centres across the UK with an £8 billion investment.

Showcasing how British technological excellence drives prosperity on both sides of the Atlantic, UK-based quantum computing company Oxford Quantum Circuits installed New York City’s first quantum computer, in collaboration with NVIDIA and Digital Realty, and launched a pioneering Quantum-AI Data Centre just outside of the city.

US quantum firm IonQ is setting up its EMEA headquarters and a new R&D and manufacturing hub in Oxford, following a $1 billion merger with UK start-up Oxford Ionics. The investment will create high-skilled jobs, boost UK quantum exports, and is a flagship example of US/UK collaboration in next-generation technologies.

Michael Intrator, Co-Founder, Chairman and Chief Executive Officer of CoreWeave:

Our investment in the UK will establish one of the world’s largest concentrations of state-of-the-art, sustainable compute, unlocking new opportunities for innovation, economic growth, and scientific discovery.

It allows us to deliver unparalleled AI performance with the lowest possible environmental impact, setting a new global standard. We look forward to collaborating with the UK government and the broader ecosystem to drive the next wave of responsible AI leadership around the world.

Marc Benioff, Chair and CEO, Salesforce:

We are doubling down on our long-standing commitment to the UK with this significant investment.

We’re delighted that the UK, already a vital talent and innovation centre, will become our AI hub for Europe, driving product innovation for customers across the region.

James Seppala, Chairman of Blackstone Europe, said:

We are delighted that the government has designated our hyperscale data centre campus in Northumberland as an AI Growth Zone. This should help accelerate the development of one of Europe’s largest data centre facilities, with £10 billion of projected investment by Blackstone funds. We hope that the project will represent a transformational investment for the region, with the potential to deliver substantial benefits to the country and local communities, by driving innovation, creating high-skilled jobs, and solidifying the UK’s position as a global AI leader.

Notes to editors

Artificial intelligence

The UK and US governments will forge a historic research collaboration to advance the use of AI in drug discovery and other shared priorities like fusion energy.

The UK and US will work together to drive AI-powered healthcare solutions in areas such as precision medicine and chronic disease – leveraging cutting-edge technologies and existing trusted and secure datasets, such as UK Biobank. The US and UK will also collaborate to co-create breakthrough research topics with the potential to catalyze investments that will redefine what is possible in medicine and patient care.

The partnership will see AI models developed by NASA and the UK Space Agency (UKSA) to support science and exploration missions, like those on the moon and Mars.

The deal will also create new opportunities for business and investment, as both countries look to scale up their AI infrastructure.

This will be a boost to British businesses behind the infrastructure, like those creating the next generation of semiconductor chips that power AI all the way to those who operate data centres and other compute resources.

The partnership will deepen the collaboration between the UK and US governments on advancing the science of AI security and promoting secure innovation – including by exchanging world-leading talent and expertise. By working together and alongside industry to develop standards we can promote the prosperity of consumers and the safety of our citizens, ensuring that the UK and US lead the world in understanding and harnessing advanced AI.

In support of the US-UK science and technology partnership, Google DeepMind will work with both governments to advise on how scientists can harness the latest AI tools in their work – as well as continuing their partnership with the UK Atomic Energy Authority to advance fusion energy research in the US and UK.

Quantum technologies

The UK and US will partner to develop revolutionary quantum computers and speed up the deployment of this technology across areas like healthcare, defence and finance. This will boost healthcare, protect citizens and create highly skilled jobs.

For example, millions of patients could receive life-saving treatments faster thanks to this groundbreaking deal. Traditional drug discovery takes years and costs millions because it relies on simulating countless molecular interactions. Quantum computers can speed this up dramatically by simulating molecules more accurately and quickly than ever before. 

Quantum tech is already saving lives, including by helping to study and treat epilepsy and dementia or providing clearer insights into our brains for brain scans. This UK–US partnership could unlock even faster breakthroughs, bringing life-changing treatments to patients sooner and transforming the future of healthcare. 

Under the deal, the 2 countries will establish a taskforce of the UK and US’s top researchers to discover and accelerate breakthroughs in quantum technologies. An exchange programme across industry will also be created to spur adoption across defence, health, finance, and energy.

Through the combined strength of national labs, the genius of British and American scientists, and the agility of leading companies, we can deliver unmatched innovation and keep our countries safe, prosperous, and leading the pack.

Nuclear

 
The partnership will turbocharge the build-out of new nuclear power stations to secure jobs and growth in the UK and US.

New deals between UK and US companies announced this week have been enabled by the partnership, which will make it quicker for companies to build new nuclear power stations by speeding up the time it takes for a nuclear project to get a license. The partnership also extends to fusion energy, where British and American expertise will fast-track progress towards commercial fusion power.

This golden age of nuclear is central to the government’s mission to build more clean homegrown power to ensure energy security.



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