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AI & Model Risk

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AI systems can produce fluent answers and perform well on a benchmark without being dependable in the workflow where a business intends to use them. Accuracy alone misses subgroup failures, changing data, uncertain outputs, human over-reliance and the consequences of an automated action. A technically impressive system can therefore create operational or decision risk even when formal authority remains with a person. Marketways assesses the model, its evidence, intended use, human authority and business consequence together so the client can decide where reliance is justified, where safeguards are needed and where the system should not be used.

When this service may be needed

This service may be useful when:

An organisation is considering deploying or expanding an AI system, model or agent in a workflow where errors could affect customers, employees, money, operations or important decisions.
A system already influences recommendations, approvals or actions, and leaders need to establish appropriate limits for the system’s role.
A model, agent, data source or operating environment has changed, raising questions about whether earlier evidence still applies.
Incidents, inconsistent outputs or recommendations without a clear basis have created concern.
Leaders need to decide when people should review the system’s work, override it, receive an escalation or take over from it.

What we assess

The scope is agreed around the system and the business question. Relevant areas can include:

Performance and limits: whether the system performs adequately for the people, decisions and consequences involved, and whether the available evidence applies to the intended setting. A strong average result can still conceal missed cases or unnecessary interventions that matter to the business.
Behaviour, evidence and explanation: whether a language model uses relevant information when interpreting or generating text, and whether an agent takes suitable actions or refers a case to a person when the available information is insufficient. The assessment can also consider whether claims and recommendations are supported by relevant source material, traceable to that material and faithfully explained.
Human authority and differential effects: whether people retain the information, time and practical ability to challenge, override or stop the system when needed. Where relevant, the assessment also considers whether performance differs materially across groups, customer types or business contexts.
Use after deployment: whether the organisation can identify problems, investigate material changes and return work safely to people or a previous arrangement when the system cannot be relied upon.

AI & Model Risk

An AI system can produce plausible answers, express confidence or complete familiar tasks without being dependable in the setting where an organisation intends to use it. AI & Model Risk examines the system in relation to its intended use, the decisions or actions it affects, the people affected and the consequences of error.

A statistical model uses data to estimate, classify or predict something. An AI agent can interpret information and take actions, such as retrieving information or completing a task. The assessment establishes where the available evidence supports reliance, where people need to review or take over, and where further work or a different approach is needed.

Controls are practical safeguards around a system. They include who can review its work, stop an action or take over when necessary. The service does not provide universal safety certification or transfer accountability from the organisation using the system.

AI & Model Risk examines the AI or analytical system itself. Decision Assurance examines a consequential business decision that may rely on that system.

How this helps the business

Define appropriate reliance. The assessment compares evidence about the system’s performance and limits with the intended use. Leaders can distinguish uses the organisation can support from uses that need safeguards, further evidence or should not proceed.
Make material failure patterns visible. The work examines errors, false alarms and missed issues alongside their business consequences. A false alarm is a case where the system identifies a problem that is not present. This can reveal a system that handles routine cases well but creates an unacceptable review burden or misses the cases that matter most.
Protect meaningful human authority. The assessment clarifies where the system influences or exercises authority, and where review, escalation, override or human takeover must remain workable. An approval step adds little protection if the person approving the result lacks the information or capacity to challenge the system.
Support controlled change. The work identifies the evidence and safeguards that may be needed when a system is introduced, updated or used in changed conditions. This helps the organisation consider a new version, data source or workflow as a business change that needs renewed attention.

How Marketways tests an AI system in the business reality where it will act

We begin with the people, decisions and consequences affected by the system. Evaluation then covers task performance, uncertainty, subgroup behaviour, robustness, drift and failure modes using cases that reflect the intended workflow. We also examine how outputs enter human judgement, when escalation occurs and who can stop or override the system. The client can define appropriate reliance and controls from evidence about the full decision system rather than a laboratory benchmark alone.

Methods and technologies that support this service

Machine Learning & Predictive Analytics: We evaluate predictive performance, generalisation, subgroup behaviour, drift and failure modes against the model's defined use and consequence of error.
Statistics & Econometrics: We test calibration, uncertainty, benchmarks and claims about relationships so a technically impressive output is not mistaken for dependable evidence.
AI Solutions: We connect model evaluation to the wider AI strategy, workflow, human authority, controls and monitoring needed for responsible operational use.

Marketways selects, combines and adapts the method mix to the business question, the available evidence and the decision the work must support.

Getting ready

Bring the system, its intended use, the decisions or actions it affects and examples of its outputs or known concerns. Marketways will define the assessment boundary, material failure modes, evidence partitions, performance tests and escalation rules required to judge whether the system is dependable enough for use.

Where this service fits

AI & Model Risk sits within Business Threats. It addresses technology and model-related conditions that could harm the business, weaken its position or put its future at risk.

Where a consequential business decision depends on an AI or analytical system, AI & Model Risk can assess whether the system has adequate evidence, recognised limits and workable safeguards for its intended use. Decision Assurance may then examine the business decision itself.

AI may enable a proposed offer, support a redesigned workflow or be considered for wider deployment. In each case, the organisation needs evidence that the particular system can perform reliably in its intended role, that people retain appropriate authority and that recovery arrangements are workable when the system fails or conditions change.

Further work may be useful when findings point to a different business question. Risk and uncertainty work may help where leaders need to examine scenarios or wider exposure. Risk detection may help where a deployed system needs early warning of deterioration. Process, workflow or systems work may be relevant where the issue lies in how people and technology operate together. A feasibility study may be useful where the organisation is deciding whether to commit resources to an AI-enabled proposition. These connections depend on the findings and do not form a required sequence.

Related AI pathway

AI Evaluation & Assurance provides the wider pathway when the business needs to assess both an AI system and a consequential decision that depends on the system.

Discuss the scope

Discuss the system, its intended use, the decisions it affects, the information available and the uncertainties that matter most. We can agree a scope around the business question, the organisation’s resources and the level of reliance under consideration.

Discuss AI & Model Risk

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