Clinical AI Pathway Stakeholders

This page introduces the key stakeholders in clinical AI development and helps clarify who to engage at each stage. Awareness of potential collaborations helps foster stronger partnerships and supports the seamless integration of AI into clinical practice.

Clinician

Clinicians—also known as Healthcare Professionals or Medical Experts—bring essential medical expertise to the development of AI solutions. They help define clinical needs, validate relevance, and ensure that AI tools support—not disrupt—care delivery. As end users, their feedback is critical throughout the process to ensure the solution is usable, trustworthy, user-friendly, and improves patient outcomes. Involving clinicians early often increases the chances of successful adoption in real-world practice.

Project Manager

Project Managers—also known as Delivery Leads, Implementation Managers, Program Managers, or Project Coordinators—are essential in a hospital setting to ensure that AI initiatives are delivered safely, efficiently, and on time. They coordinate multidisciplinary teams to move AI solutions through the phases of development. Given the dynamic and iterative nature of clinical AI projects, Project Managers help manage shifting priorities, regulatory considerations, and the integration of AI into complex hospital systems. Their leadership supports structured progress and alignment with both clinical needs and strategic goals.

Data Engineer

Data Engineers—also known as Data Scientists, Developers, Machine Learning Specialists, or Clinical Data Analysts—support AI development in hospital settings by designing and implementing robust data workflows that enable the use of health data for machine learning. This includes ensuring secure and efficient data storage, transformation, validation, and curation—essential steps for creating reliable AI models. Working with data from sources such as electronic health records, diagnostic imaging, and monitoring systems, they collaborate with clinicians and IT teams to ensure that data pipelines are technically sound and clinically relevant. As AI systems evolve, Data Engineers play a key role in adapting data infrastructure and workflows to accommodate new data, updated models, and real-world performance feedback—helping maintain trust, safety, and operational stability in AI-supported care.

Company

The company—also known as an AI Solution Provider, Technology Partner, Vendor, External Consultant, Developer, or Manufacturer—plays a pivotal role as an external partner in the development and implementation of AI solutions in healthcare. They provide the technical expertise, resources, and support needed to deploy and integrate AI systems into existing infrastructures. In a hospital context, this external partner collaborates closely with internal stakeholders—such as clinicians, IT teams, and regulatory bodies—to ensure the AI solution is effective, secure, and compliant with healthcare regulations. If resources allow, a company can also be hired to manage key business aspects such as scalability, funding, and ongoing support—ensuring the AI system aligns with the hospital’s needs and long-term objectives while adhering to industry standards.

Legal Department

The Legal Department—also known as Legal Advisors, Compliance Officers, or Lawyers—is essential for ensuring that AI solutions in healthcare comply with laws, regulations, and ethical standards. Different legal departments can provide guidance on data protection, patient consent, intellectual property, procurement contracts, and liability—key considerations throughout the AI development process. Because AI development in clinical settings often involves sensitive data and regulatory oversight, legal experts help navigate complex frameworks like GDPR, HIPAA, MDR, DPIA, the AI Act, and national health laws. Their involvement supports responsible innovation by identifying risks early and ensuring that the solution is legally sound and defensible across all stages of development.

Regulatory Expert

Regulatory Experts — also known as Regulatory Affairs Specialists, Compliance Specialists, or QRA Specialists — ensure AI systems developed for clinical use comply with the Medical Device Regulation (MDR), In Vitro Diagnostic Regulation (IVDR), and, where applicable, the EU AI Act. These regulations mandate safety, effectiveness, and specific processes for medical and diagnostic AI systems. Regulatory Experts guide teams through classification, conformity assessment, documentation, and post-market surveillance. Their early involvement is critical for defining the regulatory pathway based on the AI system’s intended use. By embedding regulatory considerations early, they help minimize delays, reduce risks, and ensure AI tools are safely deployed. Depending on the setup, they may be internal team members or external consultants.

Tech Transfer Office (TTO)

The Tech Transfer Office (TTO) supports the transition of AI innovations from research into real-world use. They help identify Intellectual Property Rights (IPR), manage patents, and negotiate licensing or partnership agreements. In the context of clinical AI, the TTO ensures that research-driven solutions are legally protected and positioned for collaboration with external partners or commercialization—bridging the gap between lab and bedside.

Health Economic Specialist

The Health Economic Specialist evaluates the economic impact of AI solutions in clinical settings. They assess cost-effectiveness, resource use, and long-term value to the healthcare system. By analyzing whether an AI tool improves outcomes relative to its cost, they help inform investment decisions, reimbursement strategies, and overall adoption. Their insights ensure that AI solutions deliver real value—not just technically, but economically. A Health Economic Specialist can also support the development of an health technology assessment (HTA). 

HTA Agency

HTA (Health Technology Assessment) Agencies assess the clinical effectiveness, safety, and cost-benefit of new health technologies, including AI solutions. Their evaluations inform decisions on reimbursement, adoption, and policy. In the AI development process, engaging with HTA bodies early can help align the solution with evidence standards and ensure it meets the requirements for future implementation in clinical practice.

Hospital IT-Department

The Hospital’s IT-Department plays a key role in ensuring that AI solutions can be safely integrated into existing clinical systems. While their primary responsibility is operations, they are particularly crucial after the launch—handling system maintenance, data security, interoperability, and user access. Early involvement is important to ensure technical feasibility and a smooth deployment, but their ongoing support is what ensures the long-term stability and functionality of AI systems within the hospital’s digital environment.