Advertising networks are investing big in AI: here's the why and how

Recently, WPP has revealed intentions to allocate £250 million for investments in AI in the year 2024. Last week, Publicis Groupe announced an investment of €300 million in AI.

Across the spectrum of global advertising network agencies, strategic investment in AI technologies has become not only a competitive advantage but a necessity for staying relevant in an increasingly data-driven and algorithmically powered industry.

GroupM projected in the previous year that by 2027, around 90% of digital ad campaigns will be influenced by AI.

Publicis intends to change its positioning and fully harness the power of AI to become an “industry-first AI Intelligent System company”.

As per Publicis, this isn’t an ambition but already a reality and what is happening now is that the company is infusing a layer of AI across its platform organisation to connect its enterprise knowledge under one entity: CoreAI.

WPP has taken substantial steps towards strengthening its AI capabilities, including the acquisition of AI specialist Satalia in 2021, as well as establishing partnerships with industry leaders such as Adobe, Google, IBM, Microsoft, Nvidia, and OpenAI.

“AI is transforming our industry and we see it as an opportunity, not a threat,” WPP CEO Mark Read said. “We firmly believe that AI will enhance, not replace, human creativity. We are already empowering our people with AI-based tools to augment their skills, produce work more efficiently and improve media performance, all of which will increase the effectiveness of our work. We also see opportunities to sell new AI-driven products and services to our clients and to capture more growth in areas like production.”

Omnicom is also actively engaging with AI technologies. DDB recently unveiled RAND, a novel hybrid creative platform dedicated to exploring and implementing new AI solutions within creative processes. Additionally, through a partnership with Microsoft, Omnicom gained early access to ChatGPT, developing its own customised enterprise version named Omni Assist, tailored to assist in campaign creation and planning.

Furthermore, Omnicom has ventured extensively into AI applications, leveraging Google’s Vertex AI platform and Imagen, Adobe’s Firefly generative AI technology, to generate content. It has also integrated its operating system with Amazon Web Services' generative AI capabilities.

Havas has recently introduced Prose on Pixels, a direct-to-client model that expands beyond traditional agency collaborations.

Earlier in January, Dentsu announced that it extended its relationship with Amazon Web Services (AWS) by adopting two key services to scale further its use of generative artificial intelligence (GenAI). The company said that Implementing GenAI will allow it to help its team of over 72,000 employees globally to innovate faster. Using Amazon Bedrock and Amazon SageMaker will help dentsu to more easily and more quickly deploy third-party and open-source models across its product and engineering teams. This development is in addition to dentsu’s deployment of a range of AI tools and services from Microsoft, Google, Salesforce and Adobe.

According to a report by the Capgemini Research Institute last year, organisations see potential in this technology for building distinct brand identities, analysing customer and market trends accurately, reducing marketing expenses, and enhancing content generation efficiency and results.

Generative AI is gradually becoming a catalyst for unlocking fresh creative avenues. With ongoing innovation, AI's application can extend across various domains including data analysis, search engine optimization, customer service, content creation, and image and video generation.

Artificial intelligence (AI) revolutionises advertising by enabling more precise targeting, and leveraging correlations beyond human capabilities. Marketers harness AI to pinpoint niche demographics, craft ad creatives, and refine ad campaigns with unparalleled accuracy.

One significant advantage of AI lies in its ability to identify the most effective targeting segments and allocate budget accordingly, pausing less fruitful avenues. This multivariate testing approach not only reduces costs but also optimises ad spending for greater impact.

AI-optimised online ads exhibit higher conversion rates and amplify return on ad spend (ROAS). Moreover, AI aids in forecasting trends across the advertising and marketing automation landscape, predicting customer behaviour, and projecting ad campaign outcomes by analysing historical data and employing statistical modelling techniques.

While there's a notable increase in advertisers adopting AI, it brings forth a myriad of ethical dilemmas. As AI algorithms become more sophisticated, marketers confront intricate ethical considerations regarding the responsible use of customer data, the transparency of AI-driven decision-making processes, and ensuring algorithms do not perpetuate social inequalities.

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