Tomorrow’s top marketers will master gen AI. We don’t exactly know how yet

Unlike other innovative technologies, such as blockchain, a wide array of brand owners, agencies and consultancies have unleashed the power of gen AI and experimented with it across their businesses over the past 16 months. From early dalliances involving the use of it to generate images or text, it is now being used to scale up and or personalize multiple variations of content, which can be rapidly tested, amended, and then distributed within the requirements of a client’s need.

As a by-product, this impact on efficiency and effectiveness is raising questions across brand owner organizations, agencies, and platforms about the shape of organizations we now need, as well as operating models.

Irrespective of whether you want to, [editor’s note: yes, we are all tired of hearing about it... but], no one can now afford to ignore the impact of gen AI in facilitating production, producing creative, campaign management, or saving time and cost across the value chain.

Whether its rise and use is about efficiency or effectiveness is redundant, the answer is... both.

And when it comes to how soon marketers can rely on generative AI to manage marketing effectiveness, there’s no either or. That’s because human intervention has a vital role to play in adding meaning, and meaning makes generative AI’s deployment effective.

As a result, now is an exciting time. For example, marketing effectiveness organization Effie has introduced a new AI category to its awards to recognize the use of AI technology in enhancing marketing effectiveness. Every entrant is being asked if and how AI was used in their campaign – the answers will help us to understand the relationship between AI and effectiveness. Meanwhile, across the spectrum of measuring marketing effectiveness, gen AI can generate more computational market propositions, creative experiences, and content than any human working alone is capable of at the moment.

It can produce more growth at a low cost and with a high output. It can measure that success, avoiding errors and reducing the man hours and effort of churning through thousands and thousands of reports.

It then becomes the utility that unlocks the mystery of what your customers are responding to in your marketing – testing campaign effectiveness quicker than ever before, before providing the blueprint for your efforts to improve it.

Despite their ambitions, however, many organizations are dazzled in the headlights of what’s approaching at a very fast pace. And as a result, there are knowledge gaps in their preparations.

Such gaps include a lack of skills within their business to navigate the rapidly emerging generative AI ecosystem of tools and partners, a lack of understanding among their general workforce of the basics of generative AI, and uncertainty about governance.

Additionally, limited foresight can result in vision documents that are outdated as soon as they are written. To combat this, those marketers who are best positioned have worked to become so by doing a number of things, the most important of which include:

• Adopting generative AI directionally – by which I mean deploying it to see where it will lead them, rather than driving it to achieve a pre-ordained end product. And this is essential because we are only at the beginning.

• Building knowledge within their organization by educating people downstream, arming talent with the basics of gen AI, building knowledge of how to use some of the tools, and factoring all of this into their overarching business strategy.

• Creating and testing use cases. PepsiCo brand Lay’s ‘Messi Messages’ – involving a video experience enabling fans to send personalized videos with Lionel Messi addressing their friends by name (available in eight different languages) – is a powerful case in point. Volvo’s AI chatbot on WhatsApp for new electric car owners is another.

How best to quantify AI’s impact on efficiency and effectiveness – not just large language model (LLM) deep learning algorithms but also hand-in-hand with gen AI – is still a work in progress.

AI’s ultimate promise has two interlocking halves – the utility it provides a brand owner to let their imagination run free and the utility to ensure that freedom is used most effectively to achieve its business goals.

Amir Malik is managing director of Accenture Song and an Effie UK Council member.