Pricing when you can't predict
Rethinking managed services pricing in the age of AI
Artificial intelligence is changing how quickly value is created and measured. Tasks that once required significant human effort can now be completed in seconds, while business demands, customer expectations and operational priorities continue to shift in real time.
Yet many managed services contracts and pricing structures remain rooted in assumptions of predictability, including fixed scope, stable demand and labor-based economics.
From an executive perspective, Amar Aswatha explores how AI is reshaping the economics of managed services and why organizations are increasingly rethinking traditional pricing models. Drawing on our experience helping clients navigate AI-enabled transformation, the paper examines emerging pricing models, evolving partnership structures and practical strategies for balancing flexibility, accountability and business outcomes in an increasingly uncertain environment.
In this viewpoint, you’ll learn:
- Why traditional labor-based pricing models are becoming harder to align with AI-enabled delivery
- How outcome-based, consumption-based, agent-based and hybrid pricing models are evolving
- What the “token paradox” means for AI economics and cost management
- Why speed, responsiveness and business agility are becoming new measures of value
- How organizations can reinvest AI-driven efficiencies to accelerate modernization and innovation
- The characteristics of adaptive partnership models built for uncertainty
Discover how leading organizations are rethinking pricing, governance and value creation as AI transforms managed services and why the goal is no longer to perfectly price the future, but to design for it.
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