Electronic informed consent, or eConsent, is no longer a novel approach to clinical research. Regulators around the world increasingly recognize electronic, remote and technology-enabled approaches to informed consent as part of modern clinical trial conduct.

But the regulatory environment has changed significantly.

The most important development is not a single new eConsent regulation. Instead, updates to Good Clinical Practice, electronic systems guidance and national clinical trial frameworks are changing how sponsors can design, document and manage informed consent.

ICH E6(R3) is central to that change. FDA issued E6(R3) as final guidance in September 2025, describing the revision as a modernization of GCP that embraces innovation in trial design, conduct and technology while emphasizing quality by design, participant protection and risk-based approaches. FDA subsequently withdrew its E6(R2) guidance in April 2026.

At the same time, regulatory developments in the United States, European Union, United Kingdom and Canada are providing clearer frameworks for electronic records, remote interactions and alternative ways of documenting consent.

For sponsors, CROs and clinical trial sites, the question is therefore changing. It is no longer simply, "Can informed consent be electronic?"

Increasingly, the question is: How can electronic informed consent be implemented in a way that protects participants, supports understanding, verifies identity where required, preserves reliable records and meets the requirements of every jurisdiction involved in a trial?

‍

The clinical trials industry is at an operational inflection point. Despite decades of process refinement, drug development timelines have continued to lengthen, and manual workflows still account for a significant portion of skilled operator time across key trial functions. The emergence of large language model-based AI platforms has introduced a new variable into this equation, with multiple vendors now positioning their technology as a solution to these structural inefficiencies.

Two categories of vendors appear frequently in sponsor and CRO evaluations. The first are  general-purpose AI platforms, whose large language model capabilities have become some of the most widely benchmarked in the industry. The second are purpose-built clinical technology platforms with an established operational presence across decentralized and hybrid trial environments. 

Both have made substantive investments in life sciences AI in 2026. Their approaches, however, differ significantly in architecture, regulatory readiness, and deployment scope. This analysis examines those differences to help sponsors and CROs assess which type of platform is better suited to their operational requirements.

‍

Artificial intelligence is reshaping clinical trial operations in 2026. Sponsors and CROs are no longer evaluating standalone tools. They are choosing platforms that can connect with existing systems, automate complex workflows, and scale without disrupting ongoing studies. This guide breaks down the vendors best positioned to integrate with the clinical trial infrastructure you already have.

‍