The news: AI is showing little payoff for major companies despite ever-increasing investments, per a report from Apollo’s chief economist, Torsten Slok. And the efforts of marketing teams are inextricably linked to this challenge.

Slok’s analysis looked at every company in the S&P 500 and found that revenues per worker, profit margins, and productivity growth have remained relatively flat for 493 of them since the AI boom began. The only S&P 500 companies that have seen notable growth for these metrics are the tech giants of the Magnificent Seven: Alphabet, Amazon, Apple, Meta, Microsoft, Nvidia, and Tesla—all of which sell AI-related products.

A recent survey from Arketi Group and JM Search shows that marketers are proving vague forms of ROI that don’t necessarily translate to real bottom-line growth:

• 29% of marketing professionals said output and volume are the most measurable gains from AI, followed by speed to market (19%) and analytics and insights (15%).
• 53% said content creation is AI’s most valuable application today, followed by research (33%) and analytics and reporting (31%).

Why this matters: Just 6.5% of North American advertising/marketing professionals are measuring AI investments against defined metrics, per Basis. While AI is showing a positive impact on marketing activity and output, concrete business outcomes like customer and sales growth remain elusive. This disconnect points to a larger misalignment between marketing teams and company financial goals, with minimal revenues to show for it.

Marketers need to demonstrate that the gains they are seeing have a clear positive impact for their business. Illustrating that an AI tool is leading to more output is insufficient—teams have to prove that this volume leads to actual boosts in engagement and ultimately conversion rates. Otherwise, time and resources may be better spent investigating other AI experiments.

Recommendations for marketers: Refocus strategies for evaluating AI investments by coordinating efforts with the wider organization.

• Stake out concrete ROI benchmarks with other teams, including sales, operations, and finance.
• Design each AI experiment with a bottom-line outcome in mind. Ask, “Would the CFO care about this?” before settling for vague KPIs like hours saved.

Communicate the need for real business outcomes to agencies and ad tech vendors. These partners can sometimes rely too heavily on offering access to the latest and most powerful AI models, but if this technology can’t clearly move the needle, then it probably isn’t worth the company’s money or time.

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