Pharmaceutical companies spend years developing treatments, but getting scientific information to the people who need it presents a different challenge. Clinical findings must be translated into documents for physicians, patients and regulators, each with its own requirements. As research advances and product portfolios grow, keeping that information accurate, consistent and accessible becomes an increasingly demanding task.
Artificial intelligence offers a way to accelerate parts of this process. It can help teams organize research, prepare initial drafts and adapt complex information for different audiences. Yet scientific communication leaves little room for error. A sentence that oversimplifies a clinical result or overlooks an important qualification can change how a treatment is understood.
AI is changing the way life sciences teams communicate science
These challenges are shaping the work of Prezent Vivo, a platform focused on helping life sciences companies create scientific and medical communications. Its services cover materials such as scientific posters, literature reviews, brochures and presentations, which teams use to communicate research findings and product information.
The company is building its offering around a practical problem: scientific experts often spend considerable time preparing and revising documents when their knowledge could be used for more complex work. AI can help with the initial production process, but the content still needs to reflect the evidence accurately and meet the expectations of its intended audience.
That distinction matters in an industry where documents move through several rounds of medical, legal and regulatory review before reaching healthcare professionals. Automating parts of the drafting process does not remove those responsibilities. Instead, it can give teams more time to assess the evidence, refine explanations and ensure that the final material communicates findings appropriately.
Prezent Vivo combines AI-powered tools with human expertise to support this work. Its approach reflects a broader shift in enterprise AI: the objective is not simply to generate content faster, but to make existing workflows more manageable without compromising the standards that govern them.
Rajat Mishra, CEO of Prezent, addressed this shift at Articulate 2026, the company’s summit focused on the future of life sciences communication. He predicted that “by 2030, AI will be the baseline,” arguing that expertise, judgment and trust will become the real differentiators as AI becomes more widely adopted.
For life sciences companies, that means the competitive advantage may not come from having access to AI alone, but from knowing how to use it responsibly. As these tools become part of everyday work, human judgment will remain central to deciding what scientific evidence means and how it should be communicated.