Scientific communication is becoming a technology problem as much as a content one. Life sciences teams work across complex data, regulatory requirements and specialized audiences, while the volume of material they need to turn into presentations and other communications continues to grow.
AI is increasingly being used to handle parts of that process, from generating presentations to transforming existing content. But automation does not eliminate the need for human expertise. In many cases, the challenge is deciding how to combine both without creating additional layers of software, budgets and procurement processes.
That challenge is becoming more apparent as AI adoption expands across the sector. Deloitte found that 41% of life sciences executives identified generative AI as a major trend for 2026, yet only 22% said their organizations had successfully scaled AI and 9% reported significant returns.
The gap is shifting attention from experimentation to the systems and workflows needed to make AI useful across an organization.
Moving from software to consumption
For enterprise teams, adopting another communication tool is rarely just a matter of creating an account. Different services can come with separate budgets, billing processes and approvals, making it harder to scale their use across an organization.
Usage-based models offer a different approach. Instead of paying for individual services through separate processes, organizations can draw from a shared pool based on what teams actually need.
That model is now moving into life sciences communication.
Prezent Vivo, an AI-powered communication platform built for the life sciences sector, has launched Prezent Vivo credits, a unified consumption model that allows customers to access expert-led services through a shared pool of credits.
Each credit is equivalent to one U.S. dollar. Credits are deducted when an eligible service request is completed, while administrators can allocate balances, establish usage limits and monitor consumption across teams and users.
The approach also separates access to expert services from the platform’s core AI capabilities. Generating and transforming presentations with AI, creating fingerprints, uploading files, accessing learning resources and downloading best-practice materials remain available without consuming credits.
That distinction is important for organizations trying to understand where they are spending on AI and where they are using additional human expertise.
Combining AI with human expertise
The model reflects a broader challenge in enterprise AI adoption. Organizations are not necessarily looking for technology to replace specialized knowledge. In many cases, they want AI to make that expertise easier to access and apply.
For life sciences teams, that can mean combining automated presentation creation with services such as editorial support, coaching or projects that require deeper human involvement.
Under Prezent Vivo’s new model, Overnight Presentations and editorial services, Fixed-Price Projects and Coaching Workshops can all be accessed through the same credit pool.
Francine Carrick, President of Prezent Vivo, described the model as a way to give organizations more flexibility while keeping communication tied to their broader scientific goals.
“By giving life science organizations greater visibility, flexibility, and control, we’re helping them scale high-quality scientific communication while keeping the focus where it belongs, on advancing science and improving patient outcomes. As life science enterprises increasingly seek flexible ways to combine AI with expert services, credits remove the friction of managing multiple budgets, purchasing processes, and approvals.”
For Prezent, the move represents a change in how its services are packaged. Instead of managing AI capabilities and expert services as separate experiences, the company is putting them behind a single consumption model.
“Our customers have always been at the center of everything we build. Credits reflect our commitment to giving life sciences organizations a simpler, more seamless way to access the expert services and AI-powered solutions they need, exactly when they need them,” said Rajat Mishra, CEO and Co-Founder of Prezent.
A different approach to enterprise AI adoption
The significance of usage-based credits goes beyond billing. Enterprise organizations increasingly need ways to introduce AI without losing visibility over how it is being used across teams.
A shared balance gives administrators a way to manage access while allowing individual teams to draw on services as their needs change. That can make adoption less dependent on predicting demand in advance or setting up separate purchasing processes for every service.
It also points to a more nuanced phase of enterprise AI adoption. The conversation is moving beyond whether companies should use AI and toward how AI fits into the workflows, expertise and governance structures that already exist.
For life sciences, where communication often sits between complex scientific information and decisions that affect research, healthcare and patients, that distinction matters. AI can accelerate the work, but the systems surrounding it will determine how effectively organizations can put that acceleration to use.
Disclosure: This article mentions a client of an Espacio portfolio company.
