New thought leadership highlights the foundational role of data orchestration in enabling intelligent automation and Service-as-Software in biopharma.
[Austin, TX – September 5, 2025] — As artificial intelligence continues to shape the future of life sciences, new insights suggest that data infrastructure is now the primary barrier to scaling intelligent automation in scientific and manufacturing settings.
A recent article authored by Vasu Rangadass, Ph.D., explores the rise of AI corporate citizens—autonomous agents that go beyond task automation to reason across processes, adapt to outcomes, and collaborate with other agents in real-time. Referencing McKinsey’s and Gartner’s latest research, the article highlights how the transition from Software-as-a-Service (SaaS) to Service-as-Software (SaS) is accelerating, with AI-native companies outpacing traditional software providers by 40%.
Yet, despite increasing investment in AI initiatives, ranging from drug discovery to digital tech transfer, many life sciences organizations remain stuck in proof-of-concept mode. The limiting factor? Fragmented, siloed data that prevents AI agents from operating with context.
The piece emphasizes the growing importance of data orchestration: the ability to harmonize and contextualize data across laboratory instruments, electronic systems, and manufacturing workflows at the point of generation. Rather than relying on traditional data integration methods, orchestration platforms connect experimental results to their full lineage (protocols, materials, operators, and quality metrics), ensuring that AI agents have the structured, standardized, and contextual data needed to act meaningfully.
In the context of the emerging Service-as-Software paradigm, where organizations purchase outcomes rather than tools, this foundational capability becomes even more critical. Services such as "batch release automation" or "clinical trial optimization" require seamless access to harmonized data across systems, something orchestration uniquely enables.
L7 Informatics, developer of the L7|ESP® platform, is one company addressing this infrastructure gap. Designed as a data orchestration layer for life sciences, L7|ESP supports real-time contextualization across R&D, CMC, and manufacturing environments. According to internal customer outcomes, the platform has helped research institutes reduce document preparation time by 80% and manufacturing teams increase operational efficiency by 50%.
“The conversation is shifting,” writes Rangadass. “AI corporate citizens aren’t theoretical; they’re here. But only organizations that invest in contextualized, orchestrated data will be positioned to move from AI experimentation to AI at scale.”
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full article is available here: https://l7informatics.com/blog/the-rise-of-ai-corporate-citizens-why-life-sciences-organizations-need-data-orchestration-not-just-more-software/
To learn more about L7 Informatics and the L7|ESP platform, visit https://l7informatics.com
