Find out everything a CMO needs to know to optimise their marketing strategy using GenAI.


Generative Artificial Intelligence or GenAI is here to stay

As it happens with most revolutionary technologies, generative artificial intelligence, also known by its abbreviation "GenAI", has been the subject of equal levels of enthusiasm, doubt and scepticism. The latest Forrester's ‘GenAI Marketing Adoption Framework 2024’ confirms that the vast majority of companies have already started to experiment with generative artificial intelligence.

Despite the high adoption of GenAI, the same study also notes that nearly 35% of AI decision makers believe that the potential of generative artificial intelligence is being overstated and believe it will not have a real impact on their business.

However, Forrester says that GenAI will revolutionise marketing, not only by accelerating content generation, but also by improving personalisation and customer experience, as well as optimising the measurement of marketing results.

If you want to analyse the impact of generative artificial intelligence on your marketing team, don't miss our evaluation template based on Forrester's criteria.


GenAI Guide for CMOs

Download the guide and discover how to implement GenAI in your marketing strategy and how to evaluate its impact.

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GenAI vs AGI: Differences

Due to the similar acronyms, it is common to confuse the terms GenAI (Generative Artificial Intelligence) and AGI (General Artificial Intelligence), although they are very different concepts. 

The difference between GenAI and AGI

What is GenAI?

GenAI stands for generative artificial intelligence. That is, AI technologies that focus on the generation of content, such as images, music, text, among others.

  • GenAI systems use generative approaches such as generative adversarial neural networks (GANs) or generative language models to create new and plausible content, which is often indistinguishable from that created by humans.
  • While GenAI does not necessarily focus on creating artificial intelligence systems with general cognitive abilities, it is still an important field within artificial intelligence, with applications in creativity, design and content generation.

What is AGI?

AGI stands for "artificial general intelligence" and refers to artificial intelligence systems that have the ability to understand, learn, reason and perform tasks in any cognitive domain, similar to humans.

  • AGI systems are capable of applying their intelligence to a wide range of problems, without needing to be reprogrammed or redesigned for specific tasks.
  • The aspiration is that AGI systems will be able to show an understanding and adaptability comparable to that of humans in multiple domains, from pattern recognition to abstract reasoning.
  • Although AGI remains a long-term goal in the field of artificial intelligence, it has not yet been fully achieved and presents significant challenges in terms of design and development.


GenAI in marketing

Artificial intelligence has revolutionised the way companies carry out their marketing strategies. GenAI, in particular, has proven to be a technology with incredible potential to completely transform the way brands connect with their audience. Its capabilities to analyse large amounts of data, identify patterns and trends, and personalise user experiences are just some of the reasons why GenAI has become a must-have tool for companies looking to stand out in an increasingly competitive marketplace.

According to Forrester's experts: "Marketers who master the use of GenAI will have a clear advantage over those who don't."

With genAI, brands can create more effective marketing campaigns, increase customer loyalty and improve user satisfaction, all while optimising their resources and maximising their return on investment.

Below, we explore 6 best practices for creating a robust genAI strategy that accelerates marketing and business objectives. It also introduces Forrester's B2B marketing genAI readiness assessment framework, which can help you move forward with greater speed and certainty, avoiding potential pitfalls and enabling you to leverage the benefits of genAI more efficiently.

What every CMO should know about Generative AI

6 best practices for implementing GenAI in Marketing

1. Make informed decisions about GenAI

To maximise the short and long-term benefits of GenAI, it is important for marketing executives to have an accurate vision of how this technology will drive both business and marketing objectives. In addition, close collaboration with IT and security managers is essential to ensure that the processes and applications associated with GenAI safeguard intellectual privacy and customer confidentiality, thereby protecting brand reputation.

2. Communicate a clear vision and strategy

The adoption of generative artificial intelligence should be based on a realistic assessment of the marketing objectives it addresses and how it will advance the marketing strategy in the long term. For example, one of the main goals of most marketing managers is to improve customer engagement, and GenAI can be used to create more personalised experiences that foster loyalty.

A clear vision for the use of GenAI should be supported by business objectives and KPIs.

3. Implement a data governance framework

A strong governance framework for the adoption and use of genAI is critical to avoid privacy compliance risks. In this regard, it is advisable to work closely with internal legal and security teams to understand the sensitivities associated with intellectual property, the evolving regulatory space, the role of human authorship in ensuring copyright protection, and how to protect internal data.

As marketing increasingly merges with AI, companies will need to optimise their data governance processes to adapt to the new demands of GenAI.

4. Understands the requirements and limitations of the technology

New genAI technologies are apparently easy to use, but can be very complex to implement. It is therefore essential that marketing managers or CMOs work closely with the company's CIO or CTO to understand what the technology can do, what its limitations are, and what additional investment will be needed.

5. Sort and organise your marketing data

GenAI needs continuous data ingestion to generate value and train AI models for continuous improvement of the results provided.

It is therefore critical that, before adopting generative AI, CMOs invest in data management and data governance. It is especially important to pay attention to the management of the most common unstructured data in marketing, such as customer feedback from open-ended surveys or social media posts.

6. Train your team to understand and work with GenAI

To harness the value and capabilities of generative AI, it is essential that the company's marketing team has knowledge and skills linked to the technology and knows how it works, as well as its capabilities and limitations.

In this regard, a CMO must ensure that their team is adequately trained and empowered. Marketers who master the use of GenAI will have a clear competitive advantage over those who do not. In addition, while some teams may use GenAI tools individually, adopting a coordinated approach can ensure that everyone uses them responsibly and in accordance with company-sanctioned policies and tools.


Before you go...

Don't miss our exclusive guide for CMOs where you will find the keys for a good use of GenAI in marketing. Analyse the risks and benefits that GenAI could bring to your company with our evaluation framework!

GenAI Guide for CMOs

Download the guide and discover how to implement GenAI in your marketing strategy and how to evaluate its impact.

Download now


Posted by Núria Emilio