The healthtech industry is experiencing intense competition as companies race to develop software and artificial intelligence (AI) tools for clinical decision support, medical telemetry,  robotic surgery, surgical navigation, medical imaging analysis, drug discovery, clinical trial management, and countless other medical applications. This competitive landscape is driving substantial investment and rapid innovation, with established medtech providers, disruptive startups, and well-funded tech giants all striving to integrate AI into the medical industry and patient experience. 

Last year was an important one for healthtech, marked by significant investments in AI-powered medical solutions. In 2024, the annual venture capital funding for U.S. digital health startups totaled $10.1 billion, slightly less than the $10.8 billion invested the previous year. Both 2023 and 2024 averaged about 500 total venture deals, with $1.8 billion coming from 118 deals in Q4 of 2024. While overall M&A activity remained steady, the initial public offering (IPO) market showed potential signs of resurgence, with several companies filing for IPOs in early 2025. 

Amid this fierce competition, companies must protect their innovations through intellectual property (IP). Companies that do not obtain enforceable IP rights for their investments in AI innovations may find themselves without important resources to attract investors, substantiate assertions of freedom-to-operate during due diligence, define the scope of strategic licensing deals, prevent potential competitors from entering the market, or leverage responses to IP infringement claims from competitors. Obtaining strategic IP rights in AI developments, including AI data, models, and processes, is key to thriving in times of fast innovation and stiff competition. 

Protecting AI Innovation in Healthtech 

While protecting traditional medical devices may be relatively straightforward, protecting AI innovations can be complex. For companies that leverage IP to advance business interests—rather than getting patents as trophies—a detailed discussion with a patent attorney of the ideas, competitive market, business goals, and product design is key to determining the types of IP (patents, trade secrets, etc.) will provide the most defensible and valued protection for an AI-based product. 

When establishing IP strategy, healthtech companies should consider AI and software alongside other technologies and products. Software and AI-based products are protectable. Despite uncertainty about patentability of software in both Europe and the United States, leading judicial decisions and administrative guidance have affirmed that healthtech software and AI are patent-eligible. In addition, trade secrets are an effective option for protecting AI-based innovations. 

Patentability of AI and Software in Healthtech

Healthtech IP has grown increasingly valuable. In October 2023, after prevailing at trial on validity and infringement of its AI-related patents, a healthtech company obtained an order from the U.S. International Trade Commission to stop a major computer company from importing smart watches into the U.S. The competitor ultimately redesigned its watches to remove the health monitoring technology. Recently, trade secrets in medical data, AI software, and healthtech software have been successfully enforced, including a case in which a multi-billion-dollar medical records provider was awarded $280 million in damages arising from a competitor’s theft of healthcare IT trade secrets. Nowhere is the phrase “data is the new currency” truer than with high-quality, anonymized data sets that healthtech companies gather and leverage in product development. Particularly when a product uses conventional hardware or runs on someone else’s hardware, obtaining IP for the AI, software, and data can be crucial for success. 

Detecting Infringement and Avoiding Pitfalls

Against this backdrop of high value and complex IP protection, companies face challenges. Some AI systems risk being labeled as unpatentable automations of pre-existing manual processes. Given that many AI techniques leveraged today (including “deep” learning) are decades old, there may be related prior work that may make obtaining patent protection difficult. For back-end functionality, detecting infringement can be tricky. Also, specific AI techniques are short-lived and soon replaced by improved versions.

These hurdles should not discourage medtech companies from protecting AI, but instead serve as helpful guides toward value and away from waste. Experienced IP counsel with expertise in healthtech and AI can analyze these factors together with product details and business objectives, trigger in-depth discussions necessary to align patents with value or supplement patents with other IP, and build a tailored IP strategy that helps the organization achieve its goals. 

Protecting AI Workflows, Data, and Outputs

Often, the focus may not be on the AI itself. A company’s first thought is often geared toward protecting a specific AI model it trained, but the exact model may be relatively short-lived. Retraining and structural improvements are almost certain to follow. While a chosen model performs well, alternatives may be available, and it can be difficult for companies to detect whether a competitor is using its model or a different one. For certain high-value models, trade secret protection may be appropriate, but the IP conversation may focus more on other aspects of the product workflow that interact with the AI. 

AI outputs typically drive downstream processing, leading to diagnostic output, control system change, or a recommendation to a user. That workflow is fruitful ground for AI IP. Though models evolve, AI-driven workflows may persist across product iterations. AI-driven workflows may be more visible to customers and drive sales, and it may be possible to detect usage by competitors—both of which can drive patent value. Data rights and licensing for AI outputs also present high value, particularly in context with corresponding inputs. The input processes may be ripe for IP, such as data curation and pre-processing raw data into informative features. These input-output contexts may provide important support for patent protection. While diagnostic methods can be difficult to protect, improved analyses that rely on different features or generate different outputs are patentable. It also may be possible to consider trade secret protection where features or processing are not visible. Data rights for access to the input data can be priceless, particularly for training data obtained from partners. Such non-patent IP may be important where the AI is exactly mimicking a pre-existing manual process. 

With the growth and importance of AI and software in medtech, savvy companies are using IP to protect their AI investment and gain an edge in this competitive market. Given the technical and legal complexities, obtaining valuable IP protection requires strategic patent attorneys tailoring the IP strategy through an understanding of the product and business.

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Andrew (A.J.) Tibbetts is a shareholder in the Intellectual Property & Technology practice group in Greenberg Traurig’s Boston office. He leverages prior experience as a software engineer to provide practical IP strategy counseling on matters related to computer- and electronics-implemented technology across a range of industries, including in healthtech, life sciences AI, computational biology, medical records analysis/coding, medical devices, and more. He can be reached at andrew.tibbetts@gtlaw.com. 

David J. Dykeman, who serves as co-chair of Greenberg Traurig’s global Life Sciences & Medical Technology Group and as co-managing shareholder of the firm’s Boston office, is a registered patent attorney with nearly 30 years of experience in patent and IP law. He focuses on securing worldwide IP protection and related business strategy for medtech clients, with particular experience in medical devices, robotics, life sciences, and digital health. He can be reached at dykemand@gtlaw.com. 

Samuel S. Stone is an associate in Greenberg Traurig’s Boston office. He is an intellectual property attorney, a member of the firm’s Venture Capital and Emerging Technology Practice, and Innovation & Artificial Intelligence Group. He can be reached at samuel.stone@gtlaw.com.