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2026 Statistics

Key Facts: CIM AI Marketing Exam

Official MCT Questions

CIM AI Marketing Specification 2024 V2.0

90 min

Exam Time Limit

CIM AI Marketing Specification 2024 V2.0

60%+

Pass Mark

CIM Module Grading

Credits (100 TQT / 80 GLH)

CIM Qualification Size

£165

Typical Assessment Fee (2026 centre quote)

Belfast Met course page

On-Demand Assessment Windows / Year

CIM Specification

CIM Level 6 AI Marketing is assessed by a 45-question/90-minute onscreen MCT (pass 60%+). It covers AI concepts/data/benefits, organisational ethics and skills, and AI marketing planning/tools across 10 credits (100 TQT).

Sample CIM AI Marketing Practice Questions

Try these sample questions to test your CIM AI Marketing exam readiness. Each question includes a detailed explanation. Start the interactive quiz above for the full 100+ question experience with AI tutoring.

1According to the CIM Level 6 AI Marketing syllabus, which statement best defines supervised machine learning?

A.The model discovers clusters without any labelled outcomes

B.The model learns patterns from labelled training examples to make predictions on new data

C.The model only stores raw records without learning a predictive mapping

D.The model replaces all human marketers without using data

Explanation: Supervised learning trains on labelled examples so the algorithm can map inputs to known outcomes and generalise to unseen cases. CIM indicative content lists supervised and unsupervised learning as core AI concepts for marketers.

2In unsupervised machine learning, what is the typical training goal?

A.Discover structure or groupings in data without labelled outcomes

B.Predict a pre-labelled target variable for every record

C.Minimise a labelled loss function on known outcomes only

D.Guarantee perfect campaign ROI without analysis

Explanation: Unsupervised methods (for example clustering) find patterns in unlabelled data. Marketers use these techniques for segmentation and insight discovery when outcomes are not pre-tagged.

3Deep learning typically relies on which architecture family listed in the CIM AI Marketing indicative content?

A.Single-layer linear scorecards with no hierarchical features

B.Single if-then rules that never use data

C.Manual focus groups as the only model

D.Neural networks with multiple processing layers

Explanation: Deep learning uses multi-layer neural networks to learn hierarchical representations. CIM LO1.1 explicitly lists neural networks and deep learning among key AI concepts.

4What do large language models (LLMs) primarily learn to generate or interpret?

A.Only tabular CRM fields with no language modelling objective

B.Natural language text based on patterns in large text corpora

C.Only fixed rule engines that never predict the next token

D.Only image-classification labels with no text generation capability

Explanation: LLMs are trained on large text datasets to predict and generate language. CIM LO1.1 includes large language models alongside NLP as core AI concepts for marketing applications.

5Natural language processing (NLP) in marketing is best described as AI that:

A.Only ranks products by price without reading language

B.Only schedules media buys with no text understanding

C.Only stores pixel click logs without interpreting words

D.Analyses or generates human language for tasks such as chat, search, and content

Explanation: NLP enables machines to work with human language—classification, generation, summarisation, and conversation. It underpins chatbots, sentiment tools, and content assistants referenced across the CIM AI Marketing module.

6Which prompt style asks an LLM to follow explicit step-by-step instructions for a marketing task?

A.Example-led prompt only with no instructions

B.Contextual prompt that supplies brand facts but no task directive

C.Zero-shot prompt that asks for output with neither steps nor examples

D.Instructional prompt

Explanation: CIM LO1.1 lists prompt engineering types including instructional, contextual, and example-led prompts. Instructional prompts give clear directives the model should follow.

7An example-led (few-shot) prompt primarily helps an LLM by:

A.Removing all brand constraints from every prompt

B.Showing sample inputs and desired outputs so the model can mirror the pattern

C.Blocking all API data sources

D.Removing customer consent records

Explanation: Example-led prompting supplies demonstrations so the model can infer format, tone, or structure. CIM lists example-led prompts as a prompt-engineering type marketers should understand.

8A contextual prompt for marketing copy generation typically includes:

A.Relevant brand, audience, channel, and offer details that frame the task

B.Only a blank message with no background

C.Only a request to ignore the brand style guide entirely

D.Only unrelated competitor stock prices with no campaign brief

Explanation: Contextual prompts supply situational information so outputs align with brand and campaign needs. CIM LO1.1 names contextual prompts among prompt-engineering approaches.

9In the data '4Vs' framework referenced by CIM, velocity refers to:

A.How trustworthy the data values are (that is veracity)

B.How many different formats the data include (that is variety)

C.How large the dataset is in total (that is volume)

D.The speed at which data are generated and need to be processed

Explanation: Velocity is how fast data arrive and must be handled—critical for real-time personalisation and streaming analytics. CIM LO1.2 lists volume, velocity, variety, and veracity.

10Within the 4Vs, veracity primarily concerns:

A.Trustworthiness, accuracy, and quality of data used for AI

B.How quickly new data arrive (that is velocity)

C.How many records exist in the dataset (that is volume)

D.How many formats the dataset spans (that is variety)

Explanation: Veracity addresses whether data are reliable and fit for purpose. Poor veracity undermines model accuracy and marketing decisions—hence CIM emphasises quality data preparation.

About the CIM AI Marketing Exam

The CIM Level 6 Specialist Award in AI Marketing (Ofqual 610/2849/6) is a 10-credit module that builds strategic capability to apply AI in marketing. It covers AI concepts and data, organisational adoption and ethics (including FATE), and planning/tooling for AI-enabled marketing activities. Assessment is a 45-question, 90-minute onscreen multiple-choice test.

Assessment

Onscreen multiple-choice test covering AI application in marketing, organisational/ethical challenges, and planning for AI utilisation.

Time Limit

90 minutes

Passing Score

60% (Merit 70–79%, Distinction 80%+)

Exam Fee

About £165 assessment registration (2026 centre quote) plus membership and tuition (Chartered Institute of Marketing (CIM))

CIM AI Marketing Exam Content Outline

~34%

Application of AI in Marketing

Key AI concepts, how data fuels models, and marketing benefits such as automation, CX, insights, and competitive advantage.

~33%

Organisational Challenges & Ethics

Adoption models, FATE ethics, privacy/bias/transparency, and skills for implementing AI safely.

~33%

Planning AI Utilisation in Marketing

AI tools, implementation planning with KPIs/testing/stakeholders, and impact/governance/continuous improvement.

How to Pass the CIM AI Marketing Exam

What You Need to Know

Passing score: 60% (Merit 70–79%, Distinction 80%+)
Assessment: Onscreen multiple-choice test covering AI application in marketing, organisational/ethical challenges, and planning for AI utilisation.
Time limit: 90 minutes
Exam fee: About £165 assessment registration (2026 centre quote) plus membership and tuition

Keys to Passing

Complete 500+ practice questions
Score 80%+ consistently before scheduling
Focus on highest-weighted sections
Use our AI tutor for tough concepts

CIM AI Marketing Study Tips from Top Performers

1Memorise the three learning outcomes and map every study session to LO1 concepts/data/benefits, LO2 adoption/ethics/skills, or LO3 tools/planning/impact.

2Practise distinguishing supervised, unsupervised, and reinforcement learning, and know when regression, classification, and clustering apply.

3Learn FATE (Fairness, Accountability, Transparency, Ethics) and be ready to apply it to bias, deepfakes, consent, and targeting scenarios.

4Know evaluation metrics—accuracy, precision, recall, F1—and why train/validation/test splits matter.

5For planning questions, rehearse a full loop: objectives and gap analysis → tool selection → KPIs/testing/stakeholders → monitoring and continuous improvement.

Frequently Asked Questions

What is the CIM Level 6 Specialist Award in AI Marketing?

It is an Ofqual-regulated Level 6 specialist module (610/2849/6) from the Chartered Institute of Marketing. It develops strategic knowledge of applying AI in marketing, including concepts, organisational ethics, and planning.

How is the AI Marketing module assessed?

By an onscreen multiple-choice test: 45 questions in 90 minutes, available across six on-demand assessment windows each year.

What is the pass mark?

A module pass requires 60% or above. Merit is 70–79% and Distinction is 80% or above. Fail is 0–59%.

How much does the assessment cost?

Accredited centres quote CIM assessment registration around £165 (2026 figures, subject to change), plus CIM Affiliate Student Membership and centre tuition.

How long does the module take to study?

CIM sizes the award at 10 credits with about 100 hours Total Qualification Time, including 80 Guided Learning Hours.

What topics appear on the exam?

The three learning outcomes: identifying AI applications in marketing (concepts, data, benefits); understanding organisational challenges and ethics; and planning AI utilisation with tools, implementation stages, and impact assessment.