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AI Operations Readiness Assessment

AI Operations Readiness Assessment — Free Assessment

Assessment Form

Contact Name(Required)
Are the operational processes targeted for AI augmentation fully documented and standardised?(Required)
Are the inputs and outputs of target processes digital — not requiring manual data entry or paper-based steps?(Required)
Do staff in AI-impacted roles have sufficient AI literacy to understand what AI systems do and don't do?(Required)
Is role-specific AI training available and completed by staff in roles where AI is being deployed?(Required)
Does the organisation have the change management bandwidth to absorb AI-driven operational transformation alongside other change programmes?(Required)
Is AI transformation sequenced against other change programmes — avoiding change overload on teams?(Required)
Are human-AI collaboration workflows formally designed — with clear handoff points, override mechanisms, and human accountability defined?(Required)
Do staff have clear, easy override mechanisms for AI recommendations in all human-AI workflows?(Required)
Is operational data quality sufficient for AI use — accurate, complete, and consistent at the required volume?(Required)
Is operational data accessible to AI systems in real time or near-real-time for the planned AI use cases?(Required)
Is there a structured AI pilot process — hypothesis, success criteria, time-box, and deployment gate?(Required)
Are success criteria defined for AI pilots before they begin — not discovered after the pilot ends?(Required)
Are SLAs defined for AI vendor services — availability, accuracy, latency, and response time?(Required)
Is AI vendor performance monitored against SLAs continuously — not just at quarterly reviews?(Required)
Is there an AI incident response plan covering model failures, adverse AI outputs, and data incidents specific to AI systems?(Required)
Has the AI incident response plan been tested through a tabletop or simulation exercise?(Required)
Are AI compliance requirements operationally embedded — not just in policy documents but in daily operational processes?(Required)
Do operational staff in AI-impacted roles receive compliance training specific to the AI systems they use?(Required)
Is AI adoption measured operationally — what percentage of eligible staff are actively using AI tools in their daily work?(Required)
Is AI output quality measured operationally — error rates, override rates, and user correction rates?(Required)
Is the energy and carbon footprint of AI operations measured?(Required)
Are AI sustainability targets set — energy efficiency, carbon footprint per AI inference?(Required)
Do operational staff approach AI augmentation with curiosity rather than anxiety?(Required)
Are AI champions identified in operational teams — colleagues who model positive AI collaboration?(Required)