Signed, Sealed….and Understood: AI and the Future of Informed Consent

Imagine assembling an IKEA piece of furniture. With the instruction manual written in legal jargon. In Swedish. Maybe you decide to call a friend, whose knowledge of Swedish engineering stops at perfectly constructed round meatballs, or maybe you give up and decide to just wing it. That’s often how patients feel when handed a traditional informed consent form: distressed, overwhelmed, and unsure if they’re putting all the pieces together right.

Now imagine if that manual was replaced with a step-by-step app, guiding you and answering your questions in real time, using a language compatible with your level of understanding the difference between a washer and a nut. While IKEA hacked their own problems by using a pictographic manual made to be understood regardless of the language, culture, or expertise in making furniture, the one-size-fits-all approach comes with a much higher price than a crooked cabinet drawer when it comes to your health.

The Smart Consent

Informed consent forms (ICFs), the backbone of ethical research, have long been notoriously plagued by dense legal jargon, challenging participants’ comprehension. Traditionally, ICFs have been printed documents explained and signed in person. However, the rise of decentralized clinical trials, telemedicine, and patient-centric care has pushed the industry toward electronic informed consent (eICF). This digital format allows for electronic signatures and real-time updates. The goal? A future where informed consent is safer and more accessible, ensuring that participants fully understand what they’re agreeing to. Enter artificial intelligence (AI): not as a replacement for ethical oversight but as a powerful assistant making consent smarter, clearer, and more human-centered.

Data show that about a quarter of US citizens have rudimentary reading skills and are likely unable to read and understand a bus schedule or directions on cleaning products 1, assessing the average reading grade level for adults in the US to be that of a 7th grader. 2,3 Yet, primary resources by which patients and providers learn about clinical trials options are large, public clinical trial registries, such as ClinicalTrials.gov, are written in highly technical language, inaccessible to most patients. 1 While the eICF and initiatives such as plain-language summaries and multimedia presentations4 are aimed to improve comprehension, the potential for scalable and personalized solutions to improve informed decision making and protocol adherence remains underutilized. 5

The Man Versus the Machine

AI-driven natural language processing (NLP) tools, such as ChatGPT, have emerged as a powerful tool in recent years, enabling the processing and analysis of vast amounts of unstructured textual data in various domains, including healthcare and clinical practice. 6 They can analyze consent documents to identify complex language and suggest simpler alternatives. Large language models (LLMs), such as GPT-4, are a type of NLP technology that present a new opportunity to enhance trial processes via improved patient awareness and engagement. The ability of LLMs to simplify and summarize texts could be used to simplify and clarify the often complex and jargon-heavy information presented in clinical trial documents, including informed consent forms. 7 Experimental results demonstrated that GPT-4 can effectively draft readable and accurate summaries of informed consent forms with straightforward prompting techniques, with patient surveys suggesting potential roles in improving cancer trial awareness and consent quality.8 AI can personalize the informed consent experience based on participant demographics, language preference, or medical literacy, much like Netflix tailors its recommendations to your region or “Because you watched” history. For example, a younger participant might be shown an animated video or an illustration with a voiceover 4, while a physician could receive a detailed PDF.

Studies show that traditional informed consent forms often read at a college level rather than the recommended 6th to 8th grade level 3 and participants often have questions during the consent process. AI-powered chatbots can provide real-time answers, explain concepts, or escalate complex queries to clinical staff. Chatbots are computer programs that use artificial intelligence (AI) and natural language processing to simulate human conversation (written or spoken), allowing humans to interact with digital devices as if they were communicating with a real person. 9 These bots can be trained on validated clinical information and continuously improve through feedback. In fact, the data show that, despite not being perfect, LLM-based chatbots outperformed a surgeon in creating more readable, complete, and accurate consent documentation for 6 commonly performed surgical procedures. 10 To take it a step further, recent studies looking into a routine use of chatbots for obtaining consent in health research indicate that the chatbots were as successful in obtaining affirmative consents when compared with traditional consent conversations with study staff. 9,11

Aside from improving patient understanding, smart ICFs can optimize regulatory approval timelines, thus reducing trial delays. Regulatory agencies like the FDA and EMA have strict guidelines on informed consent content, readability, and documentation. 12 Failure to comply can lead to Institutional Review Board (IRB)/ethics committee rejections, trial holds, or even enforcement actions. AI systems can assist sponsors and IRBs by checking for missing required elements, checking language complexity, tracking version control, flagging inconsistent data, and ensuring compliance with FDA, EMA, or HIPAA regulations. Cumulatively, this reduces manual errors and the risk of noncompliance.

A Smarter Future for Consent

Informed consent is more than a signature; it’s a process of empowerment and trust. By integrating AI into digital consent platforms, we can elevate this process to meet the needs of today’s complex clinical trials. However, human oversight remains essential for ethical judgement and compassionate communication.

AI-enhanced digital informed consent isn't just a tech upgrade; it's a strategic investment enabling safer, supported, and informed decision making for those who matter the most: the patients.

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Sources

1. Bothun LS, Feeder SE, Poland GA. Readability of Participant Informed Consent Forms and Informational Documents: From Phase 3 COVID-19 Vaccine Clinical Trials in the United States. Mayo Clin Proc. 2021;96(8):2095-2101. doi:10.1016/j.mayocp.2021.05.025

   
   

2. Communicating with patients who have limited literacy skills. Report of the National Work Group on Literacy and Health. J Fam Pract. 1998;46(2):168-176.

   
   

3. University of California Santa Cruz Office for Research. Informed Consent: Readability/Literacy Level. Accessed in December 2025. https://officeofresearch.ucsc.edu/compliance/services/irb22_consent_readability.html

   
   

4. Tait AR, Voepel-Lewis T, Levine R. Using digital multimedia to improve parents' and children's understanding of clinical trials. Arch Dis Child. 2015;100(6):589-593. doi:10.1136/archdischild-2014-308021

   
   

5. Waters M. AI meets informed consent: a new era for clinical trial communication. JNCI Cancer Spectr. 2025;9(2):pkaf028. doi:10.1093/jncics/pkaf028

   
   

6. Schopow N, Osterhoff G, Baur D. Applications of the Natural Language Processing Tool ChatGPT in Clinical Practice: Comparative Study and Augmented Systematic Review. JMIR Med Inform. 2023;11:e48933. Published 2023 Nov 28. doi:10.2196/48933

   
   

7. Hadden KB, Prince LY, Moore TD, James LP, Holland JR, Trudeau CR. Improving readability of informed consents for research at an academic medical institution. J Clin Transl Sci. 2017;1(6):361-365. doi:10.1017/cts.2017.312

   
   

8. Gao M, Varshney A, Chen S, et al. The use of large language models to enhance cancer clinical trial educational materials. JNCI Cancer Spectr. 2025;9(2):pkaf021. doi:10.1093/jncics/pkaf021

   
   

9. Rothstein MA. Should Chatbots Be Used to Obtain Informed Consent for Research?. Ethics Hum Res. 2023;45(6):46-50. doi:10.1002/eahr.500190

   
   

10. Decker H, Trang K, Ramirez J, et al. Large Language Model-Based Chatbot vs Surgeon-Generated Informed Consent Documentation for Common Procedures. JAMA Netw Open. 2023;6(10):e2336997. Published 2023 Oct 2. doi:10.1001/jamanetworkopen.2023.36997

    
    

11. Savage SK, LoTempio J, Smith ED, et al. Using a chat-based informed consent tool in large-scale genomic research. J Am Med Inform Assoc. 2024;31(2):472-478. doi:10.1093/jamia/ocad181

    
    

12. US Food and Drug Administration. Guidance for IRBs, Clinical Investigators, and Sponsors: Informed Consent. August 2023. Accessed in December 2025. https://www.fda.gov/media/88915/download