Value and investment priorities

You · How do we measure AI value and prioritise investment for adoption?

Value is measured by what changes in the business, not by how fast a model generates text. TRIAI’s Assess pillar starts with a process lens: pick a repeatable job where approval latency, volume, and exception classes are clear. Then define the right metrics for that job — they are not universal; they are job-specific. Typical measures used across sectors include: - Cycle time (how long the whole task takes) - Throughput (how many units complete per day) - Human time saved (hours reclaimed for higher-value work) - Error or rework rate (fewer mistakes = lower cost) - Escalation rate (fewer exceptions = less managerial overhead) - Customer response time or conversion rate (if the job touches the customer) - Cost per completed job - Percentage of work still requiring human intervention These numbers are compared before and after redesign with agentic capabilities, not before and after a demo. Prioritisation follows a simple filter: 1. Intake scorecard: Does the process have high volume, repeatable steps, and clear exception handling? If no, the work is often better left as “acceleration” rather than “adoption”. 2. Business Decision Owner (BDO) clarity: Is there a single owner who can decide whether the redesigned job is worth the change? If not, the project stalls. 3. Risk tier: Map the job to the EU AI Act risk categories (unacceptable, high, limited, minimal). Only