AI-driven advances in drug discovery and development have accelerated R&D, expanding portfolios and compressing launch timelines—placing unprecedented demands on go-to-market teams.
At the same time, the Life Sciences industry has endured persistent headcount reductions and tightened capital, leading to the human capital fabric being stretched too thin. This gap is widening at a fast pace as new therapies come to market faster.
Life Sciences organizations need to turn their humans into Super Humans with agentic AI.
1-2 Years
AI is reducing drug development time by 1-2 years, and counting.
While system-based AI agents can increase the efficiency of tasks, they don’t simplify overall jobs and elevate individual performance.
Why? Because across customer-facing roles in pharma, individuals interact with an overwhelming patchwork of a dozen or more systems, spanning CRM, workflows, content & training, compliance, external portals, clinical data, and communication tools.
Tasks are streamlined, work is not.
Role
Estimated Systems / Apps Used
Field Sales Rep
10–17
Medical Science Liaison
10–18
Field Reimbursement Specialist
10–16
Patient Services Agent
10–17
While AI may streamline tasks within individual tools, the broader burden of navigating multiple systems—and now multiple, disconnected AI agents—has only intensified.
The solution to this problem is role-based AI agents designed to augment the entire job, not just isolated steps.
The benefits of ACTO’s role-based AI SuperAgents include helping Life Sciences organizations close the widening human-capital gap by augmenting people—not replacing them—with empathy, connection, and compliance.
Industry Advisor, Health & Life Sciences, Microsoft
Source
See how ACTO’s role-based SuperAgents can transform your Life Sciences workforce.
AI solutions have been developed by system and application providers to make using their platforms easier, which is great for workflow, but not necessarily great for the workforce.
The pressure to “do more with less” is most acute in customer-facing functions that have undergone significant layoffs, downsizing, and restructuring.
In a highly regulated industry like Life Sciences, strict standards must be met before any system, application, or tool can be deployed—and agentic AI is no exception.
