Brand Breakthroughs: Marketers - Experiment at scale to win in the age of AI

Marketers, for the past few years, have been facing increasing pressure to demonstrate ROI in terms of business growth. Achieving these performance targets, while navigating budget constraints and evolving consumer behavior has certainly not been easy. Now, with the maturing of AI for marketing and its promise to enhance human creativity, to enable mass personalization, make predictions and offer insights into opportunities, the plot just got thicker.

Because, while expectations of AI are high, no one really has the exact blueprint for getting it all right. Leaning on conventional tactics to learn, test and scale sequentially and incrementally, that have served brands for decades, may not necessarily serve as well today. A more fluid approach, allowing for multiple simultaneous experiments and quick pivots in response to results – an agile way forward is the need of the hour.

And yet, not all marketing teams are able to embrace this way of working. Perhaps, the biggest lesson that we’ve learned, as we steer marketing at Infosys to be AI-first, is getting comfortable with the process of always-learning rather than the pursuit of perfection. And that’s nothing short of a cultural shift. Here are three things that are serving us well as we work to make AI work for marketing, and marketing to work smarter for the business:

Aligning AI experiments with business goals. Many times, marketing experiments in AI are conducted separately from the function’s primary focus areas - often to not disrupt core campaign work that’s tightly aligned to key business goals. For example, AI for video or social media copy generation. While this can seem like a prudent move to protect high impact areas from the deficiencies of an untested experimentative setup, this, at the same time, does not move the function forward in material ways.

Fencing off innovation efforts means relegating them to an almost extracurricular pursuit — letting them absorb resources with little to no accountability for driving business-fueling ROI. Instead, experimenting, especially with AI, needs to be everyone’s business because marketing for growth is everyone’s business on the team.

For example, when we started to explore ways to use AI and gen AI for marketing, we didn’t set up a CoE or designate specific teams to lead the charge; we simply started several experiments where everyone looked for relevant ways to apply AI to up the efficiency and efficacy of their campaign-build. As the experiments grew in impact on ROI, so did the learning and success of the AI-first new marketing tactics.

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Making it easy for data to weigh in with intuition. The data fabric underlying all our programs and processes is inevitably greatly strengthened when we prepare marketing to be AI-ready. While marketers already use data, it’s usually pieced together to justify intuition or decisions that are already in place.

The renewed data fabric creates the potential to make an important cultural shift – moving from being outcome focused to leaning into the process of learning, improving continuously through trial and error, and posing what-ifs more ubiquitously. This is accelerated when amplified by a modern marketing tech stack.

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The team is then able to harness data to anticipate customer responses, personalize and optimize campaigns, while continuously boosting marketing performance. Even more significantly, it can drive stronger attribution of campaign impact to business results. This is perhaps the greatest gift that being experimentative and data-first brings for us marketers: elevating us as leaders with a voice at the table that matters.

Actively rewarding learning and sharing, even if it’s from a failed experiment. When dealing with something as transformative and relatively untested as AI for marketing, unexpected and underwhelming outcomes will likely be as many as the desired ones. Is the team able to navigate these troughs and peaks with equanimity?

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Creating a space where employees feel comfortable trying new things, sometimes making those inevitable mistakes, and knowing that if they are learning from them, and applying the learning to future tactics and campaigns – their efforts are not in vain.

It’s up to marketing leadership to nurture this space where they trust their team members and reward failures that teach, because this is the process of planting ideas, nurturing these, and doubling down when the idea starts to grow, knowing well that not all ideas will grow.

With AI and gen AI fundamentally transforming marketing – sporadic or siloed experimenting is a luxury progressive teams can ill afford today. The only way forward is to embrace experimenting as a way of everyday work, for everyone, challenging past practices and assumptions, bringing a strong tech stack to track and measure progress, with AI to amplify our collective marketing potential. And all this while making sure the team feels valued in this environment designed not for hard-set outcomes but to keep changing for the better.

Sumit Virmani is the global chief marketing officer at Infosys. He writes a column series 'Brand Breakthroughs’ on Storyboard18.