Marketing: The unexpected leader in the gen AI revolution?

Our recent research demonstrates a surprising shift: It’s creative teams, not just technical teams, that are driving transformation through tools like generative AI.

As companies ramp up their generative AI investments, an unexpected leader is emerging: marketing. Consistently leading in investments, adoption and innovative use cases, marketing teams are using AI to transform how they operate—and setting the bar for how enterprises can use this technology to fuel innovation.

Cognizant’s recent gen AI research reveals that marketing is on the leading edge of funding gen AI investment, outpaced only by IT. This is more than just another technology adoption story; marketing’s success demonstrates a shift in enterprise innovation strategy—one where creative teams, not traditionally technical ones, are driving transformation through tools like generative AI.

Why marketing is positioned to lead the AI revolution

When gen AI burst onto the scene in late 2022, it was the ultimate solution looking for a problem. Marketers were among the first to partner with IT to find ways to use this technology to solve real, existing challenges.

For example, in 2023, LinkedIn launched its collaborative articles program, which leveraged AI to start conversations and solicit feedback from community experts. On the other end of the spectrum, The Coca-Cola Company’s ad team tapped gen AI to break through a crowded landscape with its Masterpiece campaign, which brought famous artworks to life through computer animation.

Both of these examples demonstrate how adept marketing is at leveraging technology to engage users in new and compelling ways.

The making of a change agent: Redefining marketing with gen AI

According to The State of AI report from McKinsey, of the marketing and sales teams using gen AI, 37% report cost decreases of at least 10%, while 53% say gen AI adoption has increased revenue by 5% or more.

This underscores the idea that marketing isn’t leading AI adoption because low-level tasks are a prime opportunity for automation, but because there is a revenue opportunity for companies that do. For example, using AI to create audience personas or generate content that captures the unique perspective of thousands of employees can save time, increase accuracy and produce provocative results.

IT + marketing partnership: Unlocking the potential of AI

It’s important to note that developing tools of this nature requires close collaboration between IT and marketing. While this may seem like an unlikely partnership, it is actually the ideal combination.

Marketers are problem solvers, constantly testing, learning and improving; IT teams are innovation enablers capable of implementing new technologies efficiently to solve those problems. When dreamers and makers come together, innovation can flourish.

Despite vastly different remits, both IT and marketing are usually viewed as cost centers and are under pressure to streamline budgets. This has created a natural innovation culture among both teams. By embracing new technology instead of resisting it, marketing and IT can leverage their shared drive for efficiency to produce results quickly. The result is game-changing innovation that sets the standard for the rest of the organization.

Marketing can open the lines of communication with IT on the premise that it serves as an important example for the business in terms of AI adoption—essentially, marketers can volunteer themselves as both test subjects and subject matter experts.

Paving the way to wider transformation

While AI has expanded into areas like supply chain optimization and product R&D, marketing remains at the forefront for one simple reason: its ability to deliver measurable results that drive innovation forward. As companies become more eager to tap the benefits of gen AI, marketing's success offers a valuable blueprint for adoption. Here are four practical steps companies can take.

1. Do more than just ‘get started.’ Innovation projects can languish without a sense of direction and urgency. Functional leads should form a partnership with IT to identify challenges, define a roadmap and understand budget implications.
   
   One way to do this is by kicking off a six-week innovation sprint with IT and marketing to identify a use case, run feasibility testing and secure buy-in for scaling results. The defined timeframe will give you something to react to and a true start to your project.
   
   
2. Build momentum. Early wins build excitement and credibility—but the key is to make those wins meaningful. Instead of defaulting to low-risk projects, prioritize use cases that clearly demonstrate value and impact, like a pilot that cuts time to market or boosts productivity.
   
   
3. Leverage pilots. When it comes to complex use cases, “pilot” is the magic word. A carefully defined pilot—one conducted in partnership with IT in a controlled environment, with clear parameters on data usage, participant involvement and governance—can be the key to greenlighting wider use of AI.
   
   
4. Iterate and scale. Adopting gen AI isn’t a one-and-done effort; it’s an ongoing process of learning and adapting. Build on early successes by formalizing a continuous improvement framework. Establish quarterly reviews to assess impact, refine models and integrate feedback from users. Stay engaged with how AI is changing and what opportunities are developing across the organization. Scaling isn’t about just doing more—it’s about doing it better.

AI and generative AI will play a critical role in almost every business’s future. With marketing leading the charge, the future might arrive sooner than expected.