The most commonly used amongst the agency community include Adobe’s AI-enhanced suite, Microsoft Co-Pilot, ChatGPT, Google Gemini, Claude, Waldo.fyi, DALL-E, Midjourney, Stable Diffusion, Sora, and Runway.

FuturePedia does an excellent job of tracking AI tools broadly

While many stakeholders have been calling for regulation establishing clear guidelines for the development and use of AI, AI legislation is still in early stages in the U.S. The EU’s AI Act may well become a global point of reference and is worth exploring to understand the different directions U.S. based legislation may take. State and federal governments are exploring the issue and are drafting a wide variety of bills and legislation. Several lawsuits are pending regarding copyright and other IP violations, but as of this writing (March 2025), nothing substantial has been passed or finalized. It is important to watch this space and seek expert legal counsel on AI-related issues.

The most pressing legal risks facing agencies today surround IP and copyright. Details on current status can be found in this 4As Webinar.

Further information on the legal risks of AI facing agencies today can also be read in this 4A’s whitepaper.

In the most recent update to its Media Buying Contract template, the ANA stipulates that “an agency must obtain the advertiser’s prior consent to use any artificial intelligence applications in the delivery of services.” AI usage should also be covered in detail in any vendor contracts. Read Here

The 4As released guidance on the template overall, including some proposed amendments to the AI language, which seeks to acknowledge that AI has been in use by agencies for a long time and has become table stakes for many use cases. Amended language is proposed on page 22.

The ANA’s Ethics Code of Marketing Best Practices outlines some high level guidelines for AI transparency, bias mitigation, protection of IP rights, and responsible AI use. The 4As continues to study the space and work with the ANA and other ecosystem partners on additional related guidelines.

The 4As has developed a high-level template for agency policies on artificial intelligence, highlighting key issues and including sample language.

Some companies have gone so far as to prohibit employees from using ChatGPT and other generative AI tools, often out of fear that confidential information will be unintentionally entered into a tool, thereby violating confidentiality agreements and potentially contributing training data to the models that power the tools. Platform terms and conditions vary but tend to skew in favor of the platform itself, sometimes going so far as to claim that any data entered into the system becomes the property of the platform and can be used to train models. In the case of ChatGPT for example, unless a user specifically opts out of having their data used for training, any and all inputs/prompts via Non-API sources can be used for training. It is important to read and understand the terms of service and related policies for each platform your agency chooses to engage with.

How OpenAI uses your data

IPG and McCann Worldgroup have joined the Partnership on AI to Benefit People and Society (PAI), a nonprofit organization that aims to advance responsible AI. The holding company joins more than 100 organizations already on board, including most of the big tech companies.

Publicis became the first advertising holding company to join The Coalition of Content Provenance Authenticity (C2PA), a foundation dedicated to setting standards for content authentication.

The 4As has been studying the broader issue of content provenance and recently released a guide that outlines the need for an industry standard and related key considerations.

Explore the paper here

The NIST (national Institute of standards and technology) AI Risk Management Framework (AI RMF) is intended for voluntary use and to improve the ability to incorporate trustworthiness considerations into the design, development, use, and evaluation of AI products, services, and systems.

Miscrosoft has a website on Responsible AI, with articles covering the latest on AI policy, research and engineering.

Read More

Anthropic, Google, Microsoft, and OpenAI recently launched the Frontier Model Forum, with the aim of “ensuring the safe and responsible development of frontier AI models.”

It has been said that GenAI automates the grunt work and liberates the great work. It is still relatively early days and most businesses appear to be in the experimentation phase (at least with GenAI), the potential use cases are broad – and span the entire lifecycle of marketing program development. Below is an initial list that will undoubtedly grow over time. In the near term, most GenAI use cases require human oversight and collaboration. The potential benefits and implications of these use cases are equally broad, including:

• Workflow acceleration (reducing time spent on tedious, repetitive tasks and creating time / space for more strategic and higher value work)
• Performance improvement (analyzing large data sets to extract insights and/or automatically make changes to media allocations, creative messaging, etc. – for performance optimization)
• CX improvement (enabling customer self service via chatbots, accelerating issue resolution by equipping human agents with AI-powered tools, personalizing interactions, predicting customer needs and potential churn risks, and more)

The 4As recently partnered with Forrester to study GenAI adoption amongst agencies. 

AI Overview for Brands and Agencies – The Good, Bad, and Ugly. What Marketers Need to Know About AI for Agency Scopes.

• Dynamic Creative Optimization / DCO (AI can test multiple versions of ad creative to determine which performs best)
• Programmatic decisioning (AI can analyze hundreds of attributes in a bid request to determine whether and how much to bid)
• Predictive analytics (AI systems can forecast customer trends and behaviors to help advertisers plan better ad campaigns)
• Sentiment analysis (AI can mine social media and other data sources to gauge public sentiment on brands, products, or campaigns, allowing advertisers to monitor and respond appropriately)
• Ad fraud detection (AI can identify bots, fake traffic, and other forms of click fraud to ensure advertisers are not wasting money on invalid impressions or clicks)

What’s Next is Everything (WNIE) is a blog that is cataloging examples of brands using emerging tech – including AI and Generative AI

Strategy & Planning

Insights

• Research
  • quickly tracking down statistics
  • summarizing articles
  • condensing findings from white papers
  • uncovering data points and other info that fuels
• Probing for trends and data around consumer behavior or mindset
• Persona development and inquiry

Ideation

• Sparring partner for high level ideas
• Mood board generation

Content Production

(use caution here as IP and copyright questions abound – see legal risks section above)

Writing:

• Content outlines
• Copywriting or script writing
• Social posts
• Email copy

Media Generation

• Text generation (similar to writing above)
• Image generation
• Audio (including translation) and music generation
• Video generation
• Presentation development, outlines, structure
• Code generation