Braze says AI spending must deliver measurable gains

Braze has published two studies on customer engagement and artificial intelligence, arguing that many brands are failing to turn AI spending into measurable results.

One study, produced by Forrester Consulting, found that organisations using the Braze platform achieved a 457% return on investment over three years, with a net present value of USD $23.5 million and payback in less than six months. The analysis was based on a composite organisation built from customer interviews.

A separate report with Cowry examined broader shifts in digital marketing and customer engagement. It found that consumers now face as many as 10,000 commercial messages a day, increasing pressure on brands to make marketing more relevant and timely rather than simply producing more content.

The findings reflect a wider debate in the marketing technology sector over whether heavy investment in AI is delivering clear commercial gains. Braze argues that while AI adoption is close to universal, only a small share of organisations are generating measurable returns.

Execution gap

The research points to a divide between companies using AI within live customer journeys and those still treating it as a separate experiment. According to the reports, stronger performers tend to act quickly on first-party data, apply decisioning tools within active campaigns, simplify their technology stacks and continuously refine campaigns over time.

That marks a shift away from traditional batch campaigns towards systems that respond to customer signals as they emerge. In an increasingly crowded advertising environment, the reports suggest relevance and timing now matter more than sheer volume.

For marketing teams, the implication is as much operational as technical. Consolidating tools and reducing fragmentation can help teams move faster, while a tighter focus on conversion, retention and revenue gives executives clearer measures of whether AI investment is working.

Market pressure

The studies arrive as brands face pressure to justify marketing budgets while managing rising volumes of data and content. Many companies have adopted AI tools to generate copy and creative assets, but the reports indicate that content production alone is not enough to improve customer engagement.

Instead, the emphasis is on decisioning and orchestration: deciding what to send, when to send it and to whom, based on live data rather than fixed campaign plans. Across the industry, that approach is increasingly being presented as a way to improve both efficiency and customer response.

Braze, which provides customer engagement software, used the studies to frame the challenge as one of execution rather than adoption. It argues that brands able to connect AI tools to real-time data and operational processes are better positioned than those using the technology mainly to increase output.

Astha Malik, Chief Business Officer at Braze, said the issue is becoming more acute as customers are exposed to growing amounts of automated content. “While AI-generated content is potentially infinite, customer attention is finite and loyalty is fragile. Every piece of ‘AI slop’ that reaches a customer simply trains them to tune out,” Malik said.

She said the studies show a widening performance gap between different approaches to AI in marketing.

“The research we’re releasing today highlights a widening gap between brands using AI just to increase output and those focused on driving outcomes like conversion, retention, and revenue. At Braze, we are shifting the conversation from productivity to performance. Our community of ambitious marketers chooses a premium platform not just to build faster, but to deliver outsized business impact,” Malik said.

Taken together, the Forrester and Cowry findings suggest that the next phase of AI use in marketing will be judged less by adoption rates and more by whether brands can turn data, timing and decision-making into stronger customer response and measurable financial returns.