AIMEC / Readiness
Know what to build before you spend money building it.
AIMEC readiness work evaluates processes, data, systems, governance and implementation constraints to identify where AI can create measurable value and what has to change first.
Assessment areas
Readiness is more than model access.
01 / Process
Opportunity quality
Which workflows have enough volume, repetition, data and business value to justify AI intervention?
02 / Data
Information readiness
Assess source quality, access, documentation, permissions and the gaps that could undermine an AI system.
03 / Delivery
Roadmap and controls
Prioritize projects, architecture dependencies, human oversight and implementation sequencing.
Readiness research