AI Agents in Clinical Trials: Why Language and Compliance Are the Missing Pieces

AI agents are rapidly emerging as a transformative force in clinical operations. By automating routine workflows, managing trial data, and assisting site staff, these intelligent systems promise greater efficiency and faster decision-making. Yet clinical trials are global by design, and success depends on accurate multilingual communication and strict adherence to regulatory requirements. Without addressing the language and compliance layer, even the most advanced AI agents will face adoption barriers.

The Promise and the Gap in AI-Driven Clinical Operations

AI agents are beginning to reshape clinical operations through platforms such as Medable’s Agent Studio and other agentic AI solutions. These systems are designed to automate repetitive tasks, accelerate trial management, and provide real-time support to sponsors, sites, and patients. By reducing administrative workload, they allow clinical teams to focus on higher value activities and shorten the path from study design to data readout.

However, clinical research is global in scope and depends on precise communication across diverse languages and regions. Every document, from informed consent forms to patient diaries, must meet stringent regulatory requirements and cultural expectations. While AI agents can optimize workflows, they cannot succeed without integrating multilingual accuracy and compliance. Language remains a critical barrier that determines both operational efficiency and regulatory acceptance.

The Rise of AI Agents in Clinical Operations

AI agents are autonomous, goal-driven systems designed to act within predefined boundaries. Unlike traditional automation tools, they can interpret context, adapt to evolving workflows, and carry out tasks with minimal human intervention. In clinical operations, this capability opens new opportunities to reduce manual workload and improve trial efficiency.

Key applications include automating site communications, coordinating trial activities across multiple locations, managing patient data during recruitment and retention, and assisting with real-time query resolution and documentation. These functions help streamline processes that are often resource intensive and prone to delays.

Recent advancements in agentic AI platforms, including customizable and no-code solutions built specifically for life sciences, are accelerating adoption. The shift toward decentralized trials after COVID, combined with broader digitization and the growing maturity of large language models, has created a favorable environment for integrating AI agents into daily clinical workflows. As sponsors and CROs look for ways to reduce complexity and speed up trial execution, AI agents are becoming a strategic enabler.

The Multilingual Reality of Clinical Trials

More than 70 percent of clinical trials now include sites across multiple countries, which makes multilingual communication a central requirement for success. Patient enrollment, data collection, and regulatory submissions all depend on content that is accurate, culturally adapted, and fully compliant with local standards. Even small errors in translation can compromise patient safety, regulatory acceptance, and study outcomes.

Critical materials that require multilingual accuracy include informed consent forms, electronic patient-reported outcomes, patient diaries, investigator brochures, and labeling. These documents must not only be translated but also localized to reflect cultural nuances and health literacy levels in each region.

AI agents designed for clinical operations cannot succeed in global trials without robust multilingual support. To function effectively, they must integrate validated translation workflows, terminology management, and compliance checks. Without this capability, the benefits of automation will be limited, and the risks of miscommunication or regulatory rejection will remain high.

Compliance and Regulatory Challenges

Compliance is a defining requirement in clinical research, and any use of AI agents must align with strict regulatory standards. Frameworks such as FDA 21 CFR Part 11, EU MDR and IVDR, GDPR, ICH-GCP, and ISO 17100 set expectations for data integrity, patient safety, and validated translation processes. Failure to meet these requirements can delay approvals or invalidate trial results.

Several risk factors emerge when AI agents handle multilingual or compliance-sensitive content. AI-driven translations may not be traceable to qualified linguists, which creates gaps in accountability. Mistranslation of safety information, such as adverse events or contraindications, can place patients at risk and compromise regulatory submissions. In addition, many AI systems do not provide audit-ready trails for language-related decisions, which limits transparency and prevents regulatory validation.

Consider a plausible scenario where an AI agent automates patient onboarding but delivers unvalidated translations of informed consent documents. Patients may sign forms that do not fully reflect the intended meaning, leading to invalid consent and potential rejection by regulatory authorities. This example highlights why compliance must be integrated into every AI-enabled workflow, with validated translation and quality review processes built into the system design.

Why Language Is the Missing Piece in AI for Clinical Operations

AI agents are highly effective at executing structured tasks, yet language remains one of the most complex and unresolved challenges in clinical research. Clinical trial content is not only highly technical but also tightly regulated. It requires the combination of domain expertise, linguistic precision, and validated compliance frameworks to ensure both accuracy and regulatory acceptance.

Language represents a dual challenge in clinical operations. From a technical perspective, multilingual natural language processing and machine translation often struggle with specialized medical terminology, cultural adaptation, and health literacy considerations. From a compliance perspective, regulators require validated processes that include auditability, quality assurance, and certification under standards such as ISO 17100.

Without addressing the language dimension, AI agents cannot operate effectively in global trials. Errors in translation can compromise patient safety, undermine data integrity, and delay regulatory approval. By embedding robust multilingual and compliance-ready workflows, AI-driven clinical operations can deliver on their promise while protecting the quality and reliability of trial outcomes.

Integrating Language into AI Agent Workflows

For AI agents to function effectively in clinical operations, multilingual compliance must be embedded directly into their workflows. This requires a balance between automation efficiency and human oversight to meet both technical and regulatory standards.

Best practices include hybrid workflows where AI automates routine translation tasks while certified linguists perform validation to guarantee accuracy. ISO 17100-compliant translation steps should be integrated into the pipeline to provide a clear structure for quality management. In addition, audit-ready quality assurance frameworks ensure that every language-related decision is traceable, which is essential for regulatory review.

Technical innovation is also driving new possibilities. Agentic AI can be combined with translation memory and terminology management systems to enforce consistency across large volumes of clinical content. Domain-trained large language models, such as SesenGPT, offer the ability to process specialized medical and regulatory terminology at scale. Real-time in-context quality checks performed by AI agents further reduce risk by flagging issues during translation rather than after delivery.

By embedding these practices, sponsors and CROs can deploy AI agents that accelerate trial execution while maintaining compliance and protecting patient safety.

The Future of AI-Driven Clinical Operations with Language at the Core

Over the next three to five years, AI agents are expected to take on routine trial functions such as responding to site queries, managing scheduling, and performing compliance checks. These capabilities will reduce administrative workload and create more efficient trial ecosystems. However, the organizations that integrate multilingual and compliance-ready workflows into their AI strategies will set themselves apart.

Early adoption of language-enabled agents will give sponsors and CROs a competitive advantage by reducing translation timelines, accelerating global trial launches, and improving the accuracy of regulatory submissions. Companies that build this foundation now will be positioned to expand more quickly into diverse markets.

There is also an ethical and equity dimension. Clinical trials depend on inclusive participation, and accurate multilingual communication ensures that patients from diverse populations can provide truly informed consent and engage fully in the study process. By placing language at the core of AI-driven operations, the industry can advance both scientific progress and patient trust.

Sesen’s Perspective and Role

At Sesen, we specialize exclusively in life sciences translation and localization with a focus on regulatory compliance and multilingual precision. Our approach combines advanced technology with expert human validation to deliver accurate, audit-ready content for global clinical trials.

We support sponsors, CROs, and technology providers by delivering patient-facing and regulatory materials in more than 150 languages. Our hybrid workflows leverage machine translation with post-editing and domain-trained AI models while every output is validated by subject matter experts to ensure compliance with clinical and regulatory standards.

Sesen operates under ISO 17100, ISO 13485, and ISO 9001 certifications, which provide a structured framework for quality and risk management across all projects. These standards guarantee that every translation is traceable, auditable, and aligned with global regulatory expectations.

We also integrate seamlessly with leading AI agent platforms such as Medable and Veeva, enabling language-enabled automation within clinical operations. By embedding multilingual and compliance-ready processes directly into AI workflows, we help clients accelerate trial execution while maintaining patient safety, data integrity, and regulatory acceptance.

Key Takeaways: : Language as the Foundation of AI in Clinical Trials

AI agents are poised to transform clinical operations by automating workflows, supporting site staff, and reducing administrative burden. Yet global trials demand more than efficiency. Without multilingual precision and validated compliance, adoption will face critical barriers.

Language is not a secondary consideration. It is the foundation that ensures patient safety, regulatory acceptance, and the effectiveness of AI-enabled clinical research. Organizations that embed language and compliance into their AI strategies today will be positioned to accelerate global trials and lead the industry in the years ahead.

Take the Next Step with Sesen

Sesen partners with sponsors, CROs, and technology providers to make AI-driven clinical operations multilingual, compliant, and globally scalable. Our expertise in life sciences translation and regulatory workflows ensures that AI agents deliver accurate, audit-ready results across patient-facing and regulatory content.

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