• by Ray Schultz , Columnist, 5 hours ago

Marketers are hampered by data quality issues and lack of automation, problems that drill right down into email. AI might provide some relief, judging by a new study titled “The 2026 AI and Marketing Performance Index,” from GrowthLoop, working with Ascend2. 

Personalization is particularly affected by data issues. The respondents cite these challenges as the most common in this area: 

• Hard to measure real impact—44% 
• Data latency—40% 
• Fragmented data/tools—39% 
• Identity resolution issues—36% 
• Too much manual work/not enough resources—32% 
• Risk/compliance/governance—32%

And in general, the greatest barriers to accelerating marketing growth are: 

• Delayed approvals & decision-making—36% 
• Limited resources/budget—31% 
• Manual processes/limited automation—31% 
• Reliance on input from other teams—28% 
• Siloed data across teams—27% 
• Difficulty identifying/engaging right audience—25% 
• Delayed/prolonged sales cycle—25% 
• Limited personalization capabilities—24% 
• Difficulty leveraging technology—21%

“Siloed data across teams increased significantly from 21% to 27%, while limited personalization capabilities rose from 21% in 2025 to 24% this year,” the study notes. 

What prevents measurement of experimentation outcomes? Data quality and reliability were cited by 42%, compared to 37% apiece for technology or tooling imitations and time or resource constraints. 

Meanwhile, most marketers are using AI, and applying it in these areas:

• Generating insights and recommendations—38% 
• Content generation or ideation—35% 
• Predicting customer behavior—34% 
• Automating audience segmentation—32%
• Personalizing content at scale—31% 
• SEO/content optimization—30%
• Optimizing campaign journeys—29% 
• Not actively using AI in marketing—13%

But there are limits to AI’s use and effectiveness.

“Despite the growing application of AI and its promising relationship to revenue impact, few marketing teams are allowing AI to execute actions independently,” the report states. “The most common autonomous capability reported is generating insights and recommendations (26%), followed by predicting customer behavior (19%) and optimizing campaign journeys (19%). 

It continues, “Autonomous applications in areas like SEO optimization (18%), audience segmentation(17%), and content generation (17 %) are even less common, while just 13% report autonomous personalization at scale.”

The biggest barriers to AI adoption? Concerns about data security, picked by 36% of respondents. Other barriers include: 

• Uncertainty about AI effectiveness—31% 
• Lack of internal expertise—30% 
• High implementation costs—30% 
• Difficulty integrating AI with existing systems—26% 
• Lack of confidence in current AI offerings—24% 
• Internal red tape and/or board approvals—23%
• Desire to use AI with our data source of truth vs. point solution—20% 
• Resistance to change from leadership or teams—17%

Still, AI still seems to be effective in many areas: 

• Predicting customer behavior—26%
• Generating insights and recommendations—26%
• SEO/content optimization—18% 
• Automating audience segmentation—17%
• Content generation or ideation—17%