When AI Investments Pay Off in Marketing

Marketing leaders are realizing gains from AI in three key areas, new research shows: increasing sales productivity, increasing customer satisfaction, and reducing marketing overhead costs.

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From content creation to software coding and customer segmentation, artificial intelligence deployment fever is real. But amid a great deal of media, analyst, and executive speculation about how AI will impact enterprises, it’s still not easy to see where organizations are reaping the results. To get new insights into what is currently happening with AI deployments in marketing and the associated payoffs, The CMO Survey asked a sample of 316 marketing leaders at for-profit U.S. companies to rate how the use of AI in marketing has affected outcomes. The marketing leaders, 95.6% of whom were at the vice president level or higher, reported gains in three key areas: a 6.2% increase in sales productivity, a 7% increase in customer satisfaction, and a 7.2% decrease in marketing overhead costs.

Given these positive results, we took a deeper dive into the survey findings to understand the factors that improve or hurt AI payoffs. What we found is that the return on AI investment varies depending on AI tool adoption time, the company’s digital transformation stage, and its level of experimentation with AI. Let’s take a closer look at the data and what it shows marketers.

The AI Adoption-Payoff Curve

A striking finding from the survey is that AI does not have a long history in marketing at most organizations. The results indicate that 60.4% of companies have used AI in marketing for less than one year, 17.9% for one year, and 18.7% for two to five years, and only 2.9% have used AI in marketing for more than five years.

Why the slow start for so many organizations? Many companies have experienced challenges scaling AI in business functions due to the cost, effort, and complexity of training and deploying AI data models. However, the launch of ChatGPT in November 2022 made it much easier to try AI tools. Leaders began exploring generative AI’s potential to innovate, optimize tasks, and enable domain-specific business processes more broadly across their organizations. Gartner has predicted that more than 80% of enterprises will use generative AI APIs or will have deployed generative AI applications by 2026. That’s up from 5% in 2023.

AI’s adoption time matters when it comes to payoffs.


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