Are marketers ready for the future?

This feature was originally published in the Summer 2024 issue of strategy magazine

By Will Novosedlik

While marketing has been rocked by one technological change after another over the last 25 years, nothing appears to be so radical as the promise of artificial intelligence. That said, marketers appear to be struggling when it comes to balancing the competing demands of the CEO’s AI strategy, the relentless pace of product development in the space, a deluge of hype and – lest we forget – the daily pressures of meeting quarterly forecasts.

As a consequence, there exists a major gap between the belief in AI as a panacea for the future, and marketers taking action to bring the technology to their teams.

In a recent study by Plus Company and Statista, 75% of marketers agreed that AI adoption was critical to the future of their field; 75% agreed that AI’s learning capabilities provide profound insights into customer behaviour and preferences; 69% agreed that AI-driven insights assist in optimizing spend across channels; and 66% agreed that AI helps anticipate and mitigate risks by modeling potential outcomes.

Yet, 75% of them have not taken any steps to adopt AI.

To be fair, a recent article by Goodmans LLP pointed out that firms with 100 or more employees are more likely to adopt AI, with a 20% adoption rate in Canada. But that still means 80% are laggards. Why is this the case? Goodmans claims the main obstacle – cited by 69% of

Canadian businesses currently not using AI technology – is the challenge of identifying a business case for AI. Additionally, 28% reported being unaware of available AI tools. For firms already in the AI marketplace, the cost of technologies and skills gaps in their workforces were identified as the primary barriers to adoption.

When it comes to marketers, specifically, there are other barriers to consider.

“I think the first major issue is organizational,” Raja Rajamannar, chief marketing and communications officer (pictured left), as well as founding president of the healthcare business at Mastercard, tells strategy.

“Since AI is a technology, the CEO immediately claims it as his or her territory. Classical marketers, particularly those who have reached CMO level over the last 20 to 30 years, tend to be more qualitative. They focus on psychology, sociology, anthropology, design, brand positioning – all the finer aspects of marketing. They are a little scared of data, technology and numbers, which includes finances. As a result, they naturally do not gravitate toward technology. Additionally, someone else (such as the CTO) claims the domain of technology, which further deters them from embracing it.

“Number two, there have been early incidents where companies using Gen AI had their data become public. Consequently, many companies clamped down, allowing AI use only on personal devices for hobbies, not for company work, due to confidentiality concerns.

“Number three, AI is fundamentally complex. You have machine learning, deep learning, neural learning and different types of AI like Artificial Narrow Intelligence, Artificial General Intelligence and Artificial Super Intelligence. There’s a distant awareness of AI, but its exact workings are unclear, especially in the marketing community, which is not tech-driven,” he concludes.

But perhaps the greatest hesitation is the threat of job loss.

With all the recent news about Starbucks, McDonald’s, Etsy, Walgreen’s, UPS, Lowe’s, Johnson & Johnson, Uber and Lyft eliminating the CMO role at their respective companies, you can understand a CMO’s fears. In March 2023, Goldman published a report suggesting that AI could replace the equivalent of 300 million jobs. A recent CNBC Workforce survey revealed that 51% of people in advertising and marketing and 46% of people in business logistics and support worry that AI will take their jobs.

But Rajamannar strongly encourages the industry to push aside their fears and embrace change in the age of AI. “Tools like ChatGPT single-handedly made AI accessible. Marketers started playing with it, asking it to write poems or press releases, and saw its potential. But this also created a sharp divide: some CMOs see it as an unprecedented empowering tool, while others fear their jobs might be taken away.

“Overall, this situation will likely sort itself out quickly. Historically, new technologies take years to settle, but I predict most companies will adopt AI in less than two years due to its cost-efficiency and empowering nature. AI augments intelligence rather than substituting it.”

Who’s adopting AI – and how?

Over the last year, strategy approached several Canadian marketing heads to discuss their use of AI. Almost all denied or ignored requests for interviews, except TD’s Tyrrell Schmidt (pictured right), who shared some thoughts over email. She says TD’s approach to implementing AI has been cautious, which makes sense given the banking world’s unique challenges when it comes to transparency and security.

“Our customers expect us to have their best interests at heart as we adopt new technologies,” says the CMO. “We are focused on maturing our AI capabilities, talent pipeline and technology infrastructure in a transparent and trustworthy manner.

“Currently, the bank is using AI to forecast customer behaviour and market trends… For content creation we’re leveraging marketing-leading tools and capabilities to optimize and test more personalized creative for marketing interactions. And for customer experience, we’re using AI models to help us understand sentiment and emotion through customer feedback channels.

“Gen AI is something that we’re working our way into, with a lot of important considerations for our customers and our organization. We do see tremendous opportunities, especially in areas like digital marketing and creative,” adds Schmidt.

One key thing to remember in the adoption of artificial intelligence is that it is not plug and play.

“There’s a lack of awareness about embedding AI capabilities into a company. It involves organizing data, training the AI engine for your specific context and maintaining confidentiality,” says Rajamannar. IBM’s Intelligent Marketing global lead, Alexis Zamkow, agrees: “You can’t just turn on one of these models and expect it to speak in your brand voice and understand tone, values, personas, products and your legal mandatories.

“When it comes to brand compliant communications, there is an enormous amount of tuning and training that has to happen so that the model can reflect the brand. And that means you have to pull in all the brand standards,” adds Zamkow (pictured left). “You’ve got to digitize them, you’ve got to tune the model, and then you’ve got to train the model with images and text together. So there’s training around the structure, there’s training around the basic capabilities and the understanding of the brand.”

WPP’s chief technology officer, Stephan Pretorius, says some tend to over-estimate AI’s possibilities without thinking through not only the technical and short-term limitations ­– but also what kind of future business environment they want to create.

“We did two things at the same time [when creating WPP’s Open AI platform]: create a safe, secure environment… and then examine potential use cases across the entire supply chain of our offering – from strategy to brand consulting, to creative ideation, development, production, media buying, planning, activation, experience management, CRM commerce and PR,” says Pretorius.

The WPP team found that all of the use cases fall under three categories: ideation, automation or optimization. “Ideation is about where you are using AI to come up with more ideas, better ideas, more informed by market research and more informed by different perspectives – a lot faster. You can test concepts, you can you ideate new ways of thinking about or visualizing a product,” says Pretorius (pictured right).

Then there’s automation, which is about “taking the humans out of existing marketing processes or eliminating steps altogether.”

Rajamannar shares Mastercard’s own use of AI for automation, pointing to the company’s team in Singapore, which developed a B2B generative AI tool (currently being rolled out globally) to shorten the response time for RFPs – a time-consuming process that ties up organizational resources. “An RFP that used to take seven weeks now takes a few hours,” says Rajamannar.

Another example of automation would be the ability to develop campaign creative into dozens of different formats and languages, that looked like it was filmed in different locations, says Zamkow. “This is the labour intensive work where the savings are going to happen, but you need to have your model properly trained before you can get to that derivative content development.”

As for optimization, this is where you get the biggest bang for your buck. An example would be WPP’s Performance Brain, which basically looks at a hundred visual elements in any marketing content (such as video or static ads), links them to campaign metrics (like brand lift studies or conversion reports) and then builds a prediction model to show how the new ads will perform.

“The optimization cases are already very clear,” adds Jason Dubroy, founder of strategy consulting firm The Commercery (pictured left). “From retail media planning to predictive analytics, or from brief writing to copy prompts, brands and agencies are identifying or manufacturing opportunities to make, save or invest their scarce dollars. The key won’t be if AI can be trusted, it will be how it can be trained to know that it’s right.”

To Pretorius’ areas of ideation, automation and optimization, Dubroy adds a fourth: personalization. “This is the most prominent immediate next use of this tech, democratizing data analysis and making it more accessible. However, it is essential to remember that in its current state, AI has limitations and is uniquely fallible, even if many people believe that it’s not.”

He cites successful examples including Nike’s “By You” campaign, which uses AI to allow customers to design their own shoes; Coca-Cola’s

“Create Real Magic” campaign, which implemented an AI-powered web app that invited digital artists to create artworks using AI tools; and Sephora’s Visual Artist, where a person can try on different products virtually, using AI to match skin tones with the perfect foundation shade.

For marketers who are not quite sure where to start when it comes to adopting the emerging tech, Rajamannar has this advice: “First, invest a few hours learning about AI – not the technical aspects, but the scope of its applications… There are many ways to train yourself, but one free training program is Generative AI for Executives by Shelly Palmer. It’s simple, easy to understand, and covers the basics.

“Understand what goes on behind-the-scenes to ask intelligent questions and assess the answers. Every vendor today claims their solution is powered by AI. Ask them to explain exactly how, and you’ll often find a lack of substance. CMOs need to educate themselves to leverage AI smartly. If they treat it as a black box, they risk garbage in, garbage out situations. The key is to understand enough to use AI effectively.”