Perspectives

The State of AI Adoption in Medical Writing

Exclusive results from our webinar polls

Artificial intelligence (AI) is already poised for transformational impact across diverse applications within life sciences, and the field of medical writing is no exception. But where do organizations actually stand today in their adoption curve, and what are the greatest opportunities that lie ahead?

During our recent MMS –hosted webinar, Shaping the Future of AI-Enabled Medical Writing, we launched some quick polls to pose these questions directly to our broad-based audience of CROs, small and midsize biotech, and large pharma attendees. While this was a quick show of hands and not a quantitative survey, the results nevertheless offer a revealing glimpse into current sentiment across the industry and how adoption within medical writing use cases is unfolding.

Current Use of AI: Piloting, but Not Yet Scaling

Our first poll asked attendees how their organizations are currently using AI in medical writing to assess the status of adoption. The largest group by far (33%) reported that they are piloting tools for select tasks and another 22% said they are starting to explore use cases. Interestingly, only 13% are currently actively using AI in multiple workflows, and on the flipside, nearly a quarter (24%) said they have not begun exploring AI at all yet. So, despite the clear enthusiasm around its potential, the reality is that AI adoption in medical writing remains in its exploratory stages. It’s encouraging to see that so many teams are running pilots and exploring possibilities, but it seems that relatively few have moved to scale AI broadly across their workflows.

How would you describe your organization’s current use of AI in medical writing?

Response	Percentage (%)
Piloting tools for select tasks	33
Not exploring it yet	24
Starting to explore use cases	22
Actively using AI in multiple workflows	13
Unsure	8

Barriers to Wider Adoption: Privacy and Skills Lead the Way

We then asked attendees what they saw as the biggest barrier to wider AI adoption in medical writing. The clear leader was data privacy and compliance concerns, with 46% selecting this option.

This result is not unsurprising given the critical importance of confidentiality and data security within our highly regulated sector, and it chimes with the discussions we often have with industry colleagues and sponsors. Naturally, organizations must ensure that data is secure, compliant with global regulations, and handled responsibly when using AI tools and emerging technologies.

The second most significant barrier identified by poll respondents was skills and training gaps (28%). This reflects the discussion during the webinar that to fully harness the potential of AI, the ‘human’ needs to be firmly in the loop, and successful adoption is as much about people transformation as the technology itself. As Teresa Cesena, Executive Director at MMS commented during the webinar, “Medical writers are the key to a successful integration… while the processes and the technology are important, the human knowledge is critical.”

Other barriers included a lack of validated tools (12%), resistance from teams or leadership (9%), and unclear ROI or business case (6%). Together, these findings paint a picture of an industry that needs to address a range of practical, organizational, and regulatory issues before AI can be fully embraced.

What do you see as the biggest barrier to wider AI adoption in medical writing?

Response	Percentage (%)
Data privacy & compliance concerns	46
Skills & training gaps	28
Lack of validated tools	12
Resistance from teams/leadership	9
Unclear ROI or business case	6

The Greatest Potential: Drafting and Content Generation

Finally, we asked where attendees saw the most potential for AI transformation in the next 2–3 years. The results here showed a strong consensus with more than half (52%) identifying drafting and content generation as the biggest opportunity. This reflects the insights of Zach Weingarden, Director AI Technology and Applications at TrialAssure who noted during the webinar, “AI can now take on the task of generating that first draft of content for documents like clinical study reports… what used to take days or weeks can now happen in minutes. But this doesn’t eliminate the medical writer. In fact, it elevates their role.”

Other opportunities flagged included quality control and consistency checks (21%) and literature review and evidence synthesis (15%). Smaller but still notable opportunities were cited in regulatory submission preparation (8%) and workflow automation/project management (4%).

Response	Percentage (%)
Drafting and content generation	52
Quality control and consistency checks	21
Literature review and evidence synthesis	15
Regulatory submission preparation	8
Workflow automation and project management	4

Taken together, these results suggest that AI is currently seen primarily as a writing and review partner, helping to streamline drafting, reduce repetitive tasks, and improve consistency. The emphasis is less on replacing expertise and human judgement and more on enabling writers to focus on higher-value work and boost productivity. Again, this reflects the discussions and use cases highlighted by our expert speakers during the webinar.

What This Means for the Industry

The poll results confirm what many in the field already sense: AI is here, but it’s not yet fully integrated into day-to-day practice. Pilots and experiments are underway, but wide-scale adoption is not yet here.
To move forward, organizations will need to:

Address compliance concerns by working with trusted, validated AI tools and putting governance frameworks in place.
Invest in training so that medical writers and related functions feel confident using AI responsibly.
Build a clear business case, connecting efficiency gains to measurable improvements in cycle times, quality, and team productivity.

In addition, taking a practical approach to innovation, for example by using the kind of structured pilots described by MMS Executive Director Teresa Cesena, breaks down adoption into more manageable steps.

The medical writing industry stands at an exciting inflection point, and AI in medical writing is no longer just a concept; it’s becoming a practical tool. Though clear barriers remain, the opportunities are significant, with organizations who can strike the right balance between innovation and responsibility, and focusing on holistic transformation across people, process, and technology standing to benefit most.