L7 Informatics CEO explains why the next wave of life sciences innovation depends on digital unified platforms that orchestrate workflows, contextualize data, and enable AI-actionable operations.
AUSTIN, TX — February 11, 2026 — The life sciences industry has spent the last decade modernizing legacy systems and integrating data across expanding application stacks. Those investments created operational table stakes, but rarely delivered a competitive advantage. According to Mark L. Spencer, President and CEO of L7 Informatics, the next chapter requires a fundamental shift from digital transformation to digital differentiation through disruptive innovation.
"Modernization creates table stakes," said Spencer. "Digital differentiation is disruptive innovation. It happens when your digital environment not only stores information but also governs execution. It does not just connect systems; it orchestrates work. It does not just make data available; it makes it contextual, traceable, and ready for AI to use inside real workflows."
Spencer argues that most organizations are not short on applications but short on cohesion. When LIMS, ELN, MES, analytics, quality systems, and niche tools operate as independent islands, execution becomes a relay race of manual handoffs and brittle integrations. "When you're managing double-digit disconnected systems, each with its own license costs, validation burden, and training overhead, simplification becomes economically necessary," Spencer noted. "But rationalization only becomes feasible when the backbone is consistent."
L7 Informatics addresses this through L7|ESP®, a unified digital data and workflow backbone designed for life sciences organizations. The platform enables scientific workflow orchestration, low-code configuration for subject-matter experts, AI readiness grounded in contextualized data, and end-to-end traceability through an audit-ready digital thread.
A key distinction Spencer makes is between AI-ready and AI-actionable operations. Many organizations treat AI adoption as exporting data, cleaning it, and building fragile pipelines because context remains fragmented across systems. L7|ESP captures context at the point of workflow execution, enabling AI to participate inside governed processes rather than operating as an external advisory layer.
"The organizations that make AI real stop treating context as an afterthought," Spencer explained. "When workflow and data are managed together, AI has a stronger foundation for advanced analytics and operational deployment."
Click here to read the full article: Modernization was the First Chapter, Digital Differentiation is the Next One
