INTRODUCTION
Foreign Direct Investment (FDI) in the US medical device industry remains strong, with over 122,000 workers employed by foreign-owned firms as of 2022. While venture capital for startups has dipped, the sector sees high-value M&A activity and over $5.5 billion in ongoing investment projects driven by demand for innovation, with major FDI coming from Japan, Germany, Canada, and the UK.
IN DEPTH
In 2026, the US remains one of the largest markets for both medical devices and biopharmaceutical in the world. In 2026, Foreign Direct Investment (FDI) in the US medical device sector is characterized by cautious, strategic expansion, with manufacturing revenue projected to reach $54.2 billion. Investment is focusing on AI-enabled devices and nearshoring, driven by a need to mitigate supply chain risks while facing intense regulatory scrutiny and geopolitical pressures. The volatility of AI investments has led investors to invest in companies with proven technological progress and capabilities rather than just conceptual ideas. The market is “interrogating” AI investments rather than accepting “imagination,” with a premium placed on companies that move beyond pilot projects to deployable, high-ROI AI agents.
The “Show-Me-The-Money” Shift
Early 2026 data shows that while median implementations return roughly $175 million against $187 million of spend, successful, full-scale production deployments average a 540% ROI within 18 months. Finance, operations, and retail are leading in moving beyond pilot projects to production, with some sectors pushing above 20% scale in active deployment. Mid-2026 has seen an important shift in the New York City medical industry, for instance. Investors are prioritizing companies with proven 6+ month production deployments, while firms are stuck in the pilot phase face funding gaps.[1] The market is witnessing a “clinical correction” where interest in “shiny” AI pilots is fading in favor of tools that show direct, peer-reviewed accuracy.[2] Investors recognize that AI adoption in medical workflows is slow, favoring companies with durable business models over “one-hit” tools.[3]
The Lack of a solid FDA regulatory Framework Creates a Risk for Investors
In many cases, investors have found themselves locked into contractual traps with clients that have failed to generate revenues. Between 2022 and 2025, the number of FDA-authorized AI devices nearly doubled, by-passing a rigorous clinical trial process[4]. This has opened doors to AI-enabled medical devices that in most cases do not improve patient outcomes; therefore, do not generate real value. Moreover, due to the lack of a solid FDA regulatory framework, investors face additional risks and costs. Most of the 1,450 authorized AI devices (mostly used in cardiology, radiology and neurology) were cleared through 510(K), which requires a showing that the device is “substantially” equivalent to an already-marketed product. The issue, however, is that differently from a traditional device, AI software can change after deployment, therefore, they should be subjected to constant clearance.[5]
CONCLUSIONS
Political pressure is mounting on the FDA to ease the clearance process for AI-enabled medical devices, including generative AI (GenAI) tools, creating a tension between promoting innovation and ensuring patient safety. While some stakeholders, often aligned with deregulatory, industry-friendly approaches, argue for faster market entry to boost competitiveness, safety advocates and some researchers warn that this could increase the risk of undetected algorithmic errors, potential “hallucinations,” and harmful clinical decisions. Deregulating AI medical devices is not the solution. Deregulation may attract Foreign Direct Investment (FDI) into the US; however, this strategy increases risk for investors due to potential for higher product recalls, liability issues, and regulatory uncertainty.
[1] https://www.digitalapplied.com/blog/ai-agent-adoption-2026-enterprise-data-points
[2] https://www.healthcare.digital/single-post/healthcare-ai-bubble-bursting-2026-risks
[3] https://medcitynews.com/2026/05/the-ai-funding-divide-why-vcs-will-miss-the-next-healthcare-category-kings-and-where-ceos-should-look-instead/
[4] https://www.healthcare.digital/single-post/healthcare-ai-bubble-bursting-2026-risks
[5] https://legis1.com/news/fda-ai-device-regulation-fdas-static-framework
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