Anticipate
Use signals and patterns to identify emerging needs and risks before they become disruptions.
An EAOC operating-model application
Self-Driving IT: exploring a more proactive way to operate technology.
Self-Driving IT is a developing operating-model perspective for using AI, automation and operational intelligence to anticipate needs, prevent disruption and continuously improve IT services—with people remaining accountable.
A working definition
What is Self-Driving IT?
An AI-enabled IT operating model in which services progressively become proactive, predictive, automated and self-resolving within clearly governed boundaries.
The shift
Move from responding to demand toward anticipating outcomes.
The goal is not to remove people from IT. It is to reduce avoidable friction and allow people to focus on judgment, experience, innovation and higher-value work.
Prevent
Act early to reduce incidents, service degradation and avoidable demand.
Enable
Give employees intelligent, contextual self-service for everyday technology needs.
Resolve
Automate trusted, repeatable actions while preserving controls and clear escalation paths.
Assist
Help people make faster, better-informed operational and service decisions.
Improve
Learn from experience, outcomes and feedback to continuously strengthen services.
A progressive journey
Autonomy is built in stages—not switched on all at once.
Reactive
Respond after an issue or request is reported.
Automated
Execute defined tasks and workflows consistently.
Proactive
Identify and address needs before users are disrupted.
Predictive
Use operational signals to anticipate likely outcomes.
Increasingly autonomous
Coordinate trusted actions with human oversight and governed boundaries.
Powered by enterprise capability
Self-Driving IT depends on more than technology.
Enterprise AI Operating Capability provides the strategy, trusted data, governance, technology foundations, workforce readiness and value discipline needed to make this operating model scalable and responsible.
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