The terms we use in our articles, tools and platform, explained in plain English.
25 terms
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Suggest a termHow much freedom a use case gives the AI to act on its own, from only preparing information (low) to taking actions without a person (high). Scored from 1 to 5 in the MetroMinds Library.
Read more: Who Is Accountable When AI Prepares the Decision and a Person Signs It?
The share of the expected work that people will actually do with the AI solution. It lowers the benefit in a business case to what is realistic.
How well today's AI agents can handle what a use case asks for, such as reasoning, using tools, remembering context and recovering from errors.
Read more: Does This Use Case Really Need an AI Agent?
The broad type of AI a use case relies on, such as prediction, content discovery, conversational AI or agentic AI. The Library uses 12 AI domains.
Read more: Explore the AI domains and labels in the Use Case Library
The skills and understanding people need to use AI responsibly in their work. Under Article 4 of the EU AI Act, providers and deployers must take measures to support it.
Read more: What the EU AI Act Asks of You Once Your AI Register Is Ready
An overview of every AI system an organisation uses, with its purpose, owner, role as provider or deployer, risk category and the controls in place.
Read more: Why EU AI Act Compliance Starts With Finding Your AI
The list in the EU AI Act of areas where AI systems count as high-risk, such as employment, creditworthiness, life and health insurance pricing, public benefits, education and critical infrastructure.
Read more: Why EU AI Act Compliance Starts With Finding Your AI
A low, mid and high value for the effect of a use case, such as a reduction in handling time, based on real-world implementations. Used as the starting point for a business case.
Read more: Why the Biggest AI Business Case Is Often the Weakest One
A business capability is something the organisation does, regardless of who does it or which system supports it. L1 is the broadest level (such as Operations and Delivery), L3 the most specific (such as Case and Exception Handling).
Read more: Where AI Strategy Loses Money: the Gap With Enterprise Architecture
A correction in a business case for how certain the benefit is. A lower factor means more uncertainty about the inputs or the effect.
Read more: Why the Biggest AI Business Case Is Often the Weakest One
An organisation that uses an AI system under its own authority in its work. Most organisations are deployers of the AI they buy, and have their own obligations under the EU AI Act.
Read more: What the EU AI Act Asks of You Once Your AI Register Is Ready
An assessment that certain deployers must carry out before using a high-risk AI system, such as public bodies and organisations that assess creditworthiness or price life and health insurance (Article 27).
Read more: What the EU AI Act Asks of You Once Your AI Register Is Ready
A way of working in which the AI prepares information or a proposal and a person makes and owns the decision.
Read more: Who Is Accountable When AI Prepares the Decision and a Person Signs It?
A group of related roles, such as Operations and Delivery or Finance and Capital Management. MetroMinds shows workforce impact per job family.
Read more: What AI Will Change in Your Workforce, and Why HR Hears It Last
The specific kind of AI solution within an AI domain, such as Document Intelligence or Multi-Agent Collaboration. The Library uses 83 labels.
A correction applied when several use cases target the same capability or role, so that the same saving is not counted twice in the portfolio total.
Read more: Your AI Business Cases Are Counting the Same Savings Twice
The stages a use case moves through in MetroMinds: candidate, accepted, approved for execution, in execution, on hold and rejected. Putting a use case on hold or rejecting it requires a reason.
Read more: Too Many AI Ideas for One Claims Process: How Insurers Can Choose
An organisation that develops an AI system, or has it developed, and places it on the market or puts it into service under its own name.
Read more: Why EU AI Act Compliance Starts With Finding Your AI
The difference between what your AI portfolio demands from the organisation and what the organisation can deliver today, per readiness dimension.
Read more: Take the AI Readiness Snapshot
How well you can see what an AI system does once it is live: its inputs, outputs, errors and drift.
Read more: Who Checks Your AI After It Goes Live?
The four quadrants of the MetroMinds value and feasibility matrix. Scale now: high value and high feasibility. Strategic bets: high value, harder to deliver. Quick improvements: feasible, with more limited value. Park / rethink: limited value and limited feasibility.
Read more: See the value and feasibility matrix
The share of the work that a use case actually affects. A use case that only touches complex cases might have a scope factor of 30%.
Read more: Your AI Business Cases Are Counting the Same Savings Twice
How ready the surrounding technology is for a use case, including integration, data access, observability, safety controls and scalability.
Read more: Why Predictive Maintenance Pilots Rarely Make It to the Factory Floor
What a use case asks of the organisation and the AI, such as goal clarity, decision complexity, exceptions and the impact of errors.
Read more: Does This Use Case Really Need an AI Agent?
The mechanism through which a use case creates value, such as handling time, rework, throughput or risk reduction.
