Abstract
The enterprise AI market is expanding rapidly, yet traditional pricing models—including subscriptions, consumption-based models, and even outcome-based constructs—are struggling to deliver sustained value as AI scales. The core issue isn't the pricing of AI itself, but rather how the enterprise fundamentally produces work. This whitepaper delves into why AI pricing falters when it's simply layered onto unchanged, human-centric delivery models, leading to instability in measuring and governing AI systems and a disconnect from tangible value.
To address this, Tech Mahindra introduces a new execution framework designed for AI-driven enterprises. This framework comprises three integrated constructs: structured human + AI agent teams (Vector Squads), productized outcome units (Service Tokens), and a novel analytical lens for pricing decisions (the Pricing Model Suitability Quadrant). Together, these constructs fundamentally redefine how outcomes are produced, governed, and measured within an organization. This innovative approach makes outcome-based pricing not only operationally stable but also contractible and scalable for the first time, transforming AI from a theoretical value proposition into a source of predictable, measurable, and sustained business impact.
Key Insights
Current AI pricing models—from subscription to consumption to digital workers—break down at scale because they are merely layered onto unchanged, human-centric delivery structures. Without a fundamental redesign of how enterprise work is produced, priced outcomes remain unstable, unmeasurable, or disconnected from actual business value, necessitating a complete overhaul of the operating model.
Meaningful enterprise outcomes consistently emerge from structured teams, orchestrated processes, and role-based accountability, rather than from individual AI agents or isolated automations. Pricing AI solely at the agent level overlooks this foundational truth, leading to a critical disconnect between AI deployment and the complex, collaborative nature of enterprise work.
The whitepaper introduces "Vector Squads" as the core innovation: multi-role teams comprising both humans and AI agents designed to mirror existing enterprise workflows. These squads create stable, repeatable execution patterns by having agents absorb variability in volume while humans focus on judgment and exceptions, thereby enabling predictable, governable AI-driven delivery.
"Service Tokens" transform the stable outputs of Vector Squads into productized outcome units that are easily measured, governed, and audited. This innovative approach elevates outcome-based pricing from a theoretical ideal to a practical, scalable commercial model, offering fixed prices, precise scope, and standardized governance for complex services.
By integrating Vector Squads for stable delivery and Service Tokens for productized outcomes, enterprises can finally unlock a new pricing “sweet spot.” This allows high-value, outcome-based pricing to become operationally measurable, predictable, and commercially viable for the first time, driving faster throughput, stable margins, and tangible business value.
A New Operating Model Which Makes Outcomes Measurable
The paper introduces Vector Squads, Service Tokens, and a Pricing Model Suitability Quadrant that together form a new operating and commercial framework. This approach stabilizes delivery, absorbs workload variability, and enables high-value outcome-based pricing that is operationally measurable.