AI Readiness
Definition
AI Readiness is the measurable ability of an organization to adopt, deploy, and benefit from AI across strategy, data, governance, talent, infrastructure, operations, and culture. Readiness is a scorecard, not an opinion.
Why it matters
The business case for AI Readiness.
Most failed AI pilots trace back to a readiness gap that was never diagnosed. Measuring readiness before investing is how disciplined enterprises avoid the 95% failure rate.
How SynthesisArc applies it
From concept to production.
The SynthesisArc AI Readiness Snapshot is a free 13-question diagnostic that scores readiness across seven dimensions in under five minutes. The paid INSIGHTS assessment maps operations end-to-end and produces a dollar-valued roadmap.
Go deeper
Field Notes on AI Readiness.
Related terms in Operational Intelligence
Operational Intelligence
Operational Intelligence is the practice of embedding AI directly into business operations to drive measurable, repeatable outcomes. It is the real-time loop between data, decision, and action.
Business Intelligence (BI)
Business Intelligence is the retrospective analysis of historical data to understand what happened in a business and why. BI produces reports and dashboards.
Real-Time Decision Making
Real-Time Decision Making is the ability to evaluate data and execute decisions within the operational window where those decisions matter, typically seconds to minutes.
Workflow Automation
Workflow Automation is the use of technology to execute defined business processes with minimal human intervention. AI workflow automation extends this to decision-heavy workflows that previously required human judgment.
Operational Metrics
Operational Metrics measure how well a business runs day-to-day. The four core operational metrics are cost per transaction, throughput, error rate, and time to decision.