AI in advertising has to transform the ways of our thinking and working

Neil Perkin, tutor of the new IPA course "Advanced Application of AI in Advertising" explores why unlocking the value of AI in advertising is about both optimisation and transformation.

The acronym ‘GPT’ in ChatGPT stands for ‘generative pre-trained transformer’ in reference to the type of large language model on which it is based. But it may as well stand for ‘general purpose technology’ which is a term that has long been used to describe innovations and technologies that have the potential for a significant impact on society.

Beyond enabling new business models, general purpose technologies like Generative and other forms of AI may facilitate different ways of working, or even wider changes in social and economic structures. Examples through history include the steam engine, electricity, information technology and the personal computer.

Cascade of innovations

Just like other general purpose technologies AI enables a cascade of other innovations. It has a multitude of applications and potential benefits and impacts, and its application to marketing and advertising is no different. We can use AI to do anything from assisting us with research and concepting, to content production, to automating ad targeting, to creative treatment optimisation, to summarising meetings, to analysing data at scale.

Yet whilst this breadth of new possibilities creates huge opportunities it also presents a not insignificant challenge in understanding where we should focus, where the value is, and how we should evolve or transform ways of working to adapt to the new world and derive the maximum benefit. The risk, as so often happens with significant technological shifts, is that we look at the new through the lens of the old, and that we don’t think big enough about how we can redesign and reinvent our ways of working and propositions around these new possibilities.

Thirty years to reap the true benefits of electricity in manufacturing

Let me give you an example of how easy this is to do, based on the introduction of one of the other historical general purpose technologies I mentioned earlier. Despite the first electricity generating stations and electric motors being built in the 1880s it took thirty years for the true benefit of electricity in manufacturing processes to emerge. Factories had long been powered by a single, huge steam engine that then powered a succession of shafts, belts, hammers and presses, and the whole layout of the factory was designed around access to this power.

When electrification became possible, engineers did the seemingly logical thing. They simply replaced the big steam engines with big electric motors. But the shafts, belts and presses still worked as they did before and the levels of productivity gain were disappointing. To get the real value from the new technology factory owners needed to think bigger. Instead of a single big power source that powered everything, electricity actually enabled there to be many smaller electric motors that could deliver power locally wherever it was needed.

This changed everything. Instead of being arranged on the logic of steam power, suddenly factories and production lines could be designed and organised around the flow of materials. This in turn enabled the automated production line and fundamentally changed how factories and factory workers worked leading to huge productivity gains. To get the true benefit of electricity, factory owners needed to change how they thought about not only the new power source but about the manufacturing process itself.

Zoom forward to the present day and the risk is that we see a similar productivity lag when we look at realising the full potential of AI in marketing and advertising. Fulfilling this potential will come not only from optimising what we currently do now but in transforming ways of thinking and ways of working.

Substitution, augmentation, modification and redefinition

One of my favourite ways of thinking about this idea of optimisation and transformation draws on a framework originally conceived by Dr. Ruben Puentedura for use in the education sector. Based on the acronym SAMR which stands for Substitution, Augmentation, Modification and Redefinition, it articulates four levels through which we can understand the full potential of new technology:

• Substitution: here the technology can act as a direct substitute to other ways of completing the outcomes. You may be introducing new tools or technology to an existing process or workflow for example, but you’re not changing the fundamental method or approach
• Augmentation: here the introduction of new technology may enable the optimisation of a process or way of working. It enhances it but you’re still not fundamentally changing the approach.
• Modification: this involves a much bigger evolution whereby the technology or tools can enable a more fundamental redesign of the process or methods.
• Redefinition: this is the most fundamental level of change since the technology is enabling entirely new tasks, processes or models to be created. This may be transformative but it also may be disruptive to existing models or ways of thinking.

In this model augmentation and substitution are both examples of enhancement or optimisation. Modification and redefinition are both more transformative.

One of the characteristics of general purpose technologies is that they are combinatorial. This means that, as Strategy Director Matthew Cox has observed, the real power of AI ‘lies in how it combines with other technologies, data, and processes to create new possibilities’. We need to incorporate AI in pragmatic ways to augment efficiencies but we also need to think bigger about entirely new possibilities. My new course with the IPA will cover critical aspects of how AI can be applied to the advertising process to support greater efficiency, using hands on exercises and recent case studies to provide more strategic learning around how AI tools can support broader marketing objectives and be applied through the customer journey. The future of AI in marketing and advertising will be about both optimisation and transformation.

Neil Perkin is running a one-day face-to-face workshop on the Advanced Application of AI in Advertising on 18 September and virtually on 9 and 10 December. This course is relevant for advertising and marketing professionals with a few years’ experience, who might have explored AI tools, but desire a more strategic view on how they can understand the value that AI can bring to their roles and their clients.

The opinions expressed here are those of the authors and were submitted in accordance with the IPA terms and conditions regarding the uploading and contribution of content to the IPA newsletters, IPA website, or other IPA media, and should not be interpreted as representing the opinion of the IPA.