Crack the AI scaling wall and redefine business success via Services-as-Software

This report outlines how enterprise leaders in retail, CPG, healthcare, insurance, and industrials are deploying AI to compress decision time, improve customer experience (CX), and industrialize operations, and why most efforts stall at scale. We test what ‘good’ looks like for governance, measurement, and sourcing in the emerging Services-as-Software (SaS) era. The findings translate directly into buyer actions, KPIs, governance gates, and contract levers.

Insights were drawn from several interviews with CIOs, CTOs, heads of AI, and senior business leaders in healthcare, retail, CPG, insurance, and industrials across North America and Asia (anonymized where requested).

- Pilots are stalling at a scaling wall. Despite enthusiasm, only a few AI pilot projects reach enterprise scale (10–15%). This is because organizations continue to grapple with data/tech debt, process drag, talent deficits, and trust gaps.
- Where is AI delivering now? Bets beyond cost positively impact decision latency and CX. Enterprise leaders treat AI as a tool to make faster decisions, personalize at scale, and industrialize operations, not merely to reduce cost. They track decision latency, forecast accuracy, cycle time, conversion, and CSAT/NPS as default AI metrics.
- Human + AI dominates. Full automation is not realistic in the near term. AI augments frontline and knowledge work in customer service, marketing, and supply chain. Agentic patterns are piloted with a human in the loop (HITL).

Three years ago, it took half an hour. Now the same person can do it in five seconds. That’s not a fad. That’s transformation.

— Head of AI at a US-based healthcare company

- Pragmatic governance can infuse speed and trust. Leaders now ask: How do we know when a model or agent is ready for production? How should it be versioned? And how do we prevent a ‘Wild West’ of pilots? With this mindset, governance councils and readiness gates are emerging as essential accelerators of safe, scalable deployments.

AI can be a buzzword. It’s not a magic wand. Sometimes it kills one issue and creates another.

— CIO of an Asia-based insurance company

- Regarding vendor and provider relationships, SaS is the next frontier. Services are getting codified into platforms with outcome SLAs. Software vendors are encroaching on services as automation reduces labor. Buyers are negotiating on outcomes, portability, and explainability.
- AI engagement models with providers are following a hybrid approach. Large, mature firms hold strategic, IP-sensitive AI in-house. Early/mid-maturity firms lean on providers; most scale efforts and blend both. Moreover, there’s geographic variation in relative AI adoption. The US moves the fastest. Asia is rapid but varied, with India strong in delivery talent.
- The road ahead. Firms must harmonize technology, talent, processes, and partners. The winners will be those embedding AI into the fabric of their operations (and culture), upskilling their people to work alongside AI, fostering cross-functional agility, and demanding outcome-driven solutions from their partners. This requires bold leadership and an experimentation mindset, but the payoff is an organization that can pivot on a dime in the face of change.

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Author

Ashish Chaturvedi Executive Research Leader

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