Stephen Noble is an innovation expert with robust experience on the media agency side and AdTech & MarTech product creation. He is passionate about translating trends into productive results for agencies, helping them and their customers to gain a competitive edge and impactful returns.
As an industry, advertising has always had to evolve in the face of new consumer trends and to reflect the world we live in. But change has been coming thick and fast over recent years, driven by digital transformation and innovation in technology like artificial intelligence (AI).
In reality, we have been integrating AI tools and applications into processes for some time.
Predictive AI has been applied at scale in advertising since 2014 through programmatic ads, with predictions done by machine learning (ML) models capable of finding similarities, identifying root causes of particular actions in historical data and based on the factors, making data-informed recommendations that decision-makers can act on.
From AI-enhanced audience targeting and segmentation, to developments in programmatic advertising, these are the outcomes of predictive AI. It’s clear however that we are on a journey and that there are so many more possibilities as the technology continues to evolve.
We are seeing predictive AI models being complemented with generative AI within ad agencies. Besides applying it for heavy load stages to win and service clients like creating pitches and automating time-consuming tasks of campaign asset creation, translation and personalization, agencies are already starting to apply generative AI for planning and validation stages.
Part of long-term planning is in understanding trends and predicting consumer expectations now and in the future, and whether brands can meet them. Instead of collecting insights from high-level data, agencies can use generative AI to act as their researcher, interpreting data from websites of retailers’ competitors, and gathering insights on search trends and social media to provide valuable information about consumer interests.
In doing this, generative AI can make specific predictions on future expectations of target audiences with high precision, helping brands plan and stay relevant in the long run.
For ad agencies planning campaigns for specific key audiences, they also need to check if campaign creatives and messaging will resonate with those audiences. Here, generative AI can complement the process by comparing audience engagements with previous similar campaign assets and recommend ones that may resonate better.
Tools like ChatGPT and image and video generators like Midjourney, DALL·E, and NVIDIA Picasso will also play an increasingly important role in the creation process, enabling the development of new images and the conversion of static images into text, headlines and videos. Advertisers can then run personalized ads at scale, meaning AI can create highly personalized variations of ads depending on the audience.
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Take time out when considering AI
Marketing and ad organizations should take the time to assess and identify areas where AI can deliver the most significant benefits. Think of the most mundane tasks, identify a group of the first movers who are curious to learn, and provide a sandbox environment to test the use cases.
It is also important to establish guidelines to safeguard users when looking at how to incorporate generative AI use cases, ensuring responsible use of the technology is at the heart of the agency. Educating staff, providing training and ensuring developments are done in a responsible, transparent way is much more likely to lead to positive and successful outcomes.
There are other risks to consider as AI technologies continue to evolve at pace. As with any technology, it is susceptible to forms of attack and misuse. The tools themselves should also be handled with care and attention. Be aware of limitations, like unconscious bias. AI tools are only as good as the data set they have learned from and can be biased in terms of representation.
No generative AI outputs should be acted on without the right checks and balances in place, with responsible human oversight and safeguards being incorporated. This means agencies providing training for any employees using the tools to explain how these models are trained, and how to curate prompts to get the expected outputs. Access to AI tools through a unified platform allows guard rails to be put in place, protecting things like brand IP and copyright, with all brand data remaining within the platform itself. Establishing a centralized control center within the platform ensures the quality and fairness of both inputs and outputs provided by AI tools.
There’s no doubt that AI and machine learning technology is changing the game within the industry and the impact of a new generation of generative AI tools will be significant for all of us, leading to improvements in campaign planning, testing and performance.
Of course, we cannot do without the creativity and ingenuity of humans, and despite the negative headlines we see around AI, there will always be a need for human skills in the ad world. The technology will be there to do much of the heavy lifting and will enhance agency processes, while allowing teams to focus on strategic planning direction and delivery.
One day we will stop talking about AI as something different but see it as an integral part of the creative process. Right now, we are still in a learning phase, understanding just how AI can help in this process and what exactly it can do.
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