Replay: Operationalizing Services-as-Software™: From AI ambition to enterprise execution

AI adoption is nearly universal, but enterprises are still struggling to turn investment into meaningful business outcomes. The biggest barrier isn’t the technology, it’s the legacy operating model. Services-as-Software™ offers a fundamentally different approach, shifting from human-led, effort-based services toward AI-led delivery, proprietary enterprise intelligence, and outcome-based models.

In this webinar, HFS’ Saurabh Gupta, President, and Rohan Kulkarni, Life Sciences & Healthcare Executive Research Leader, explored how enterprises can operationalize Services-as-Software and bring the model to life through a pharma manufacturing use case.

The discussion examined how agentic AI can transform knowledge-intensive work in pharma manufacturing, from detecting and investigating deviations to accelerating batch release, while keeping humans in control of critical decisions and exceptions. Saurabh and Rohan also discussed the business case, barriers to adoption, and a practical five-step roadmap for moving from AI ambition to enterprise execution.

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Key takeaways

• Services-as-Software is a business model shift, not simply another AI implementation. It moves services from human-led delivery and effort-based pricing toward technology-led execution, proprietary IP, and outcome-based models.
• Legacy operating models are holding back AI value. Enterprises need to rethink how work is organized, governed, and activated rather than layering AI onto existing processes.
• Pharma manufacturing provides a compelling use case. Agentic AI can transform deviation management and batch-release processes by automating knowledge work while retaining human oversight at critical decision points.
• The value goes beyond productivity. HFS frames the opportunity around four Ps – productivity, prediction, personalization, and performance, with performance connecting AI transformation directly to business and financial outcomes.
• The economics can be significant. HFS’ illustrative single-site use case estimates a $1.8 million startup investment with payback inside the first year and the potential for a 10x return over three years.
• Trust, economics, and organizational change are the critical barriers. Success requires explainable and auditable AI, new outcome-based financial models, and workforce adoption.
• Operationalization requires a structured path. HFS outlines five steps: diagnose and quantify; design the operating model; build the foundation; deploy, adapt, and scale; and measure and mine.

Learn more

Services-as-Software requires more than deploying AI. It demands a rethink of the operating model, commercial model, governance, workforce, and how enterprises measure value.

Watch the replay to see how HFS brings the model to life through a practical pharma manufacturing use case and lays out a roadmap for moving from AI experimentation to measurable enterprise outcomes.

Contact us to learn more about how HFS can support your Services-as-Software sourcing journey.