The past two years saw a significant first step movement in the development of AI with an emphasis on generative AI. In most technology cycles, barring sending spaceships to the moon or to orbit, new technology gains value when it can be used at scale and the barriers to entry are lowered for developers and therefore end users. Generative AI showed the promise and has growing use in the day-to-day professional and personal aspects of end users.

The real benefits of use of data science, including predictive and generative AI, is to go beyond the basic and find customized outcomes that can be scaled, that is, where the solutions are pervasive beyond more than a few ecosystems — such as Marketing, HR, Finance, etc. And we are getting there.

What this means is that we are in the process of actively (and enthusiastically) embracing the development of cognitive abilities in software – this is the essence of what AI is - that in the best case scenario will significantly augment human capabilities, and, in the worst case, will replace human cognition en-masse.

While the financial and social costs of developing this “new cognition” has not been fully appreciated, we marketers (who are increasingly expected to have the technical understanding of a junior CTO) must contemplate how one ought to approach the convergence of AI with the vast, often deeply embedded adtech, martech and everything-in-between that marketing teams have been integrating into their operations over the past 15 years.

Will a topical application of AI achieve the required objectives? Or, as I’m sure some of you have already done, should we be sitting down with our finance teams to evaluate the cost of replacing existing tech stacks with new products with embedded AI?

Let's indulge in some productive musings.

Brands rightly want to engage their customers within the ecosystems they (the customers) are already in. This will require re-architecting their visibility of the various ecosystems – commerce, gaming, retail media networks, social – to build connections for each one with a centralised hub for data interactions.  

This is an approach that allows for layering of the architecture with the products and technology, which can interact with each other while offering  moments of interaction with the customer, enhancing experiences and improving loyalty. 

Within these connections, lies the opportunity to apply AI using agents, graph databases, RAG methods, step functions in predictive models and/or automation techniques.  These will power the connective tissue between these ecosystems, and at the same time  offer huge advantages, without completely uprooting existing adtech or martech. 

This re-architecting of our various ecosystems would then also offer up the possibility of achieving that oft-claimed but elusive zenith of data-driven marketing: the delightful connection where media, creative and customer experience know-how, enabled and informed by analyses provided through the AI-powered connective tissue, converge to deliver the right message at the right time with the right experiential and creative touch.

Dentsu’s strategic view of AI already includes internal builds for efficiency and external builds for customer innovation and effectiveness. We are already shipping products to our clients that are specific to their marketing, media, creative needs.

A major push within these bespoke modules is the ability to support our clients with an AI workbench that is tailored for a brand’s collateral and data, ensuring that their content, creative, media and experience design is driven with specific, niche outputs that can be flexibly adjusted and scaled with time. We are on the cusp of a new world of customer experience where brands will no longer be the primary architects of the customer journey. Instead, with new AI-powered tools at their disposal, customers will be the co-architects of their journeys, effectively communicating their expectations through AI agents, bringing a whole new dimension to the brand-customer relationship as creators and consumers both. 

Customer touchpoints and interactions, while being captured via the adtech and martech that has already been deployed, will soon also be signals that brand-side AI agents will parse in order to formulate and deliver personalised customer messaging, offers and experiences. And customers will, using their own AI agents, challenge and invigorate brands to deliver more!

Our teams are already working with cutting edge predictive and generative AI technology that can build deep insights with the data provided to it, thus revealing connections that have not been explored so far.  

While the seemingly unlimited possibilities have us barrelling head first into this new world of “cognitive software”, we must ensure that any evaluation is grounded in the fundamental reasons for engaging any new technology. Because it is cost-effective. Because it is repeatable. And because it enables us to meet the ultimate objective of the industry we love, which, put simply, is marketing products that our audience most desires plus products they have not discovered but should have.

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• _{Nothing in this article is intended to be or should be construed as an endorsement or promotion of AI, generative AI (GAI) including of any particular AI or GAI tool by dentsu. Readers should undertake their independent assessment (including from a legal and ethical perspective) before using or advising on the use of any of the foregoing. Please also see our terms and conditions linked at the bottom of this page.}