Breaking the managed services operating model in tech

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Agentic AI is fundamentally changing how work gets done. Yet many managed services models were designed for a world of human-executed workflows, headcount-based delivery, and traditional governance.

This paper explores why technology companies need to rethink managed services from the ground up and build an operating model designed for autonomous, outcome-driven delivery. Discover how a new approach to orchestration, governance, workforce, and commercial models can help organizations capture the value of AI while managing its rapidly evolving risks.

The managed services model is reaching a tipping point

For technology companies, AI integration is becoming central to enterprise strategy. Nearly 64% of TMT leaders now view managed services as a critical driver of technology innovation, while 57% identify AI capability as the single most important criterion when selecting a managed services provider.

But adding AI to yesterday’s operating model is not enough. Organizations need to reconsider how work is orchestrated, how value is measured, where human judgment belongs, and how autonomous agents are governed at machine speed.

Rethink the managed services operating model for an agent-driven environment

Balance AI autonomy and human oversight based on risk, reversibility, and business impact

Modernize commercial models by moving beyond FTE- and rate-card-based delivery toward outcome-based commitments

Embed trust and governance through continuous monitoring, auditability, and appropriate guardrails

Transform the workforce from task execution toward intelligence-assisted supervision and higher-value judgment

Move from strategy to execution through a phased roadmap spanning diagnostics, lighthouse pilots, delivery-model transformation, and an agentic ecosystem at scale