Practical training for marketing, communications and audience-engagement teams working in the arts and cultural heritage sectors
Generative AI is changing how audiences find, experience and talk about arts and culture. This intensive in-house course delivered in-person or online helps marketing and communications teams understand how these systems operate and how to use them responsibly.
Through demonstrations and practical exercises, you’ll learn what AI does well and where it fails. We will look at how to build an ethical approach that protects brand integrity, creativity and audience trust.
The programme blends creative exploration with legal and policy awareness so that organisations can adopt AI with confidence and care.
Bespoke to you and your team
The Responsible AI: building trust, creativity and policy training will be bespoke to you and your organisation.
Each package will be planned and adapted to your team, get in touch to explore online or in-house options and costs by emailing membership@a-m-a.co.uk.
You will also have access to supporting course materials including module workbooks, further resources and session recordings through an online learning platform throughout the course.
The training we did with Paul and Carol was exceptionally good thank you. A masterclass in how to run training but I also felt they really understood our needs and challenges and adapted the sessions for that – even making changes from the first session to the second around what was most important to us.
Hannah Yewdall-Brooks, Marketing Account Director & Chair of UK Women’s Network, ATG Entertainment
Why do the Responsible AI: building trust, creativity and policy course?
‘Working with AI is now the status quo’. This is what we are hearing from many marketing and comms teams. Using AI is no longer experimental but becoming business as usual. In particular, the rise in AI overviews is reducing search traffic dramatically to our websites which means we need to quickly adapt to what AI is bringing. Marketing and communications teams already use AI, but many do so without shared principles or guardrails. That gap creates reputational risk and confusion about what’s allowed.
This intensive training course builds a clear foundation. Participants move from curiosity to capability, learning to test outputs critically, document decisions and contribute to their organisation’s wider AI policy.
They leave able to:
- Explain how generative AI creates language and imagery
- Recognise bias, hallucination and over-confidence in outputs
- Apply a human-first prompting framework for copy, design and ideation
- Maintain tone and brand authenticity
- Understand how copyright, data protection and advertising law already cover AI use and current AI standards and policy frameworks
- Contribute to an AI policy and governance framework
- Confidently work with others to explore AI use cases in your organisation
- Explore an AI strategic marketing workflow
What will you leave this training with?
After the two sessions, you will have:
- A grounded understanding of how generative AI systems work
- A shared language for discussing bias, risk and opportunity
- Practical skills in prompting and brand-voice consistency
- Awareness of copyright and data protection as it applies to AI
- A draft AI-use framework and traffic-light tool list
- Strategies for disclosure, sustainability and audience trust
- Confidence to start working with your team and stakeholders on an AI policy and use framework
Delivery and support:
- Two experienced facilitators combining digital R&D, marketing and policy expertise
- Up to twelve participants per cohort
- Pre-course survey
- Digital workbooks and facilitator materials included
- One-hour follow-up clinic for policy feedback or Q&A
- Available in person or online
Session Plans
Session 1 – How generative AI thinks
Duration: 3 hours
Focus: Understanding how generative AI systems work, exploring bias and developing confident prompting and critical thinking skills .
What We Will Cover:
- Set the scene: why responsible AI matters for creative work. We connect to your organisation’s values, governance and brand integrity, review confidence levels and introduce the tools we’ll use.
- Culture and attitudes toward AI : Investigate the challenges and how people feel about AI - excitement, hesitation, guilt or creative fear. We explore how cultural change can shape how teams approach new tools.
- What is generative AI? A plain-language explanation of how large language and image models predict what comes next, not what is true. We’ll explore how words and images are represented in AI systems and look at the difference between text-to-text and text-to-image generation.
- Prompting foundations – human-first approach : We practise structuring prompts with clear role, context and output. Through a series of exercises, participants see how small changes transform quality and tone. We unpack why large models are “pleasers” rather than logical thinkers and how to counter that through human oversight.
- Brand voice and organisation profile : Participants generate a concise organisation profile and a short brand-voice statement. By comparing AI-written content with and without this framing, you will learn how to maintain consistency, inclusion and accessibility across channels.
- Bias and hallucination in language : We test for bias by prompting the model with open descriptions. Participants identify subtle stereotypes and missing perspectives. We explore how AI spots patterns humans might miss, followed by a hallucination demo using incomplete data. Together we build quick bias-checking prompts for system settings.
- Validation and data hygiene: Practical steps for safe use: anonymising data, checking sample size, aligning timeframes, and recording sources. We discuss how these principles feed into AI policy and privacy guidance.
- Team collaboration : We close with how to explore this learning internally: using discussion, short demos and shared experimentation rather than formal teaching.
Session 2 – Part 1: AI Media, Governance and Trust
Duration: 1.5 hours
Focus: Understanding how AI creates images and video, linking creativity to copyright and policy, and building transparent organisational frameworks.
What We Will Cover: Images, video and environment
- Recap and example sharing: We review participants’ examples, discuss where AI outputs succeed or fail, and identify common misconceptions.
- How models work: A clear walk-through of text-to-image generation, showing how noise becomes form. We look at major datasets to discuss transparency, copyright and consent.
- Image generation, editing and bias: Participants compare outputs across tools to uncover repetition, bias and tone issues. We cover when image editing becomes misrepresentation and how to handle background changes responsibly. Then we shift to creative re-use - how to generate new visuals from your own photography and design assets safely, turning AI into a remix engine rather than a replacement.
- Quick video overview : A short demonstration of AI video tools exploring potential use for concept visualisation, accessibility and storytelling - alongside ethical and environmental limits.
- Environmental sustainability : We compare the energy and water impact of text, image and video generation. Participants discuss where creative benefits justify the footprint and how to include sustainability within AI policy.
Session 2 – Part 2: Governance, Copyright and Trust
Duration: 1.5 hours
Focus: Understanding how AI creates images and video, linking creativity to copyright and policy, and building transparent organisational frameworks.
What We Will Cover:
- From ethics to governance : We shift from personal responsibility to organisational accountability.
Participants learn how existing UK law - GDPR, data protection and consumer law already governs AI use, alongside frameworks from DCMS and ACE. - Copyright, authorship and legal context: Through real cultural-sector examples, we explore copyright ownership, consent and safeguarding. We build a matrix to classify scenarios as Safe, Review or Reject based on UK law and organisation values.
- Provenance and disclosure: We demonstrate content-credential tools and show how to label AI-assisted work clearly and confidently without undermining creativity.
- AI visibility and metadata: A short exercise on how AI overviews summarise your web presence. Participants audit a page for authorship metadata and visibility readiness. We map out how we need to be AI ready.
- Drafting an AI use policy or framework :
Groups build a draft policy using the AI Use Framework Canvas to take back to their teams. We introduce the traffic-light system for evaluating tools (Green = approved, Amber = review, Red = prohibited) and combine outputs into a shared template. - Audience trust and authenticity: A discussion on transparency and creative honesty. We consider how disclosure affects audience confidence and how theatre and live performance may become stronger precisely because of their authenticity.
- Environmental and ethical debrief: We revisit sustainability data and identify what to monitor - energy use, disclosure rate and audit-trail compliance.
Trainers
Paul Blundell
Head of Digital Research and Development, Arts Marketing Association
Carol Jones
Editor of AMAculturehive, Arts Marketing Association
Any questions?
Please contact the team and we’ll be happy to help: membership@a-m-a.co.uk
