Meta’s AI business assistant is now resolving account issues 20% faster, its Q1 earnings call revealed. 

With the assistant having been fully deployed in the last quarter, this allows the social media conglomerate’s advertisers to manage campaigns more efficiently, access tailored recommendations, and resolve common issues without relying on human support. 

This positions the assistant as part of a broader automation layer across advertiser workflows, with the tool operating directly inside day-to-day support, optimization, and campaign management rather than as a standalone feature. 

Susan Li, CFO at Meta, highlights the success of the assistant in Q1 as it delivers practical value across advertisers’ workflows, simplifying key tasks and improving how they run and optimize campaigns at scale. 

“We are also leveraging AI to make it easier for businesses to manage their customers, develop ad creative, and engage with customers,” she explained. 

“The Meta AI business assistant has now been fully rolled out to all eligible advertisers on supported Meta buying services, providing personalized recommendations to advertisers, resolving account issues, and surfacing campaign insights to help optimize results.”

Meta’s AI Business Assistant Records 20% Improvement

With Meta’s AI business assistant having moved from testing to deployment, this tool now operates at scale with its core ads platform as a support and optimization layer. 

“Performance has been strong since we began testing the assistant in Q4, with common account issues being resolved at a 20% higher rate,” Li continued. 

The assistant is now capable of handling millions of advertiser interactions weekly, seeing a strong growth in comparison to the previous quarter. 

These measurable gains indicate a stronger first-line resolution with human intervention, with the assistant now handling routine advertiser problems, offering tailored recommendations, and surfacing campaign insights, all in one place. 

As a result, this reduces friction in managing ad accounts and lowers the need for manual troubleshooting or support escalation, signaling that the system is effectively dealing with repeatable, high-volume issues that slow down campaigns. 

Faster Issue Resolution in Campaign Workflows

For marketing teams, this changes how brands interact with Meta’s platform, meaning instead of relying as heavily on support channels or manual analysis, they can resolve issues faster and act on real time guidance within the workflow.  

The 20% improvement in issue resolution suggests that more problems are being handled instantly or on first contact, meaning campaigns are less likely to stall due to account errors, policy flags, or setup mistakes. 

By reducing friction in day-to-day campaign management with automated support and troubleshooting, this ensures faster fixes, less downtime, and fewer manual escalations when issues arise. 

As a result, this enables marketers to spend more time on strategy, creative testing, and performance optimization, while the AI handles diagnostics, basic fixes, and insight generation in the background. 

This tool also shifts campaign optimization into an always-on AI layer, with the assistant now able to surface insights and recommendations by moving away from reactive capabilities, allowing marketers to get guidance in real time rather than relying solely on periodic analysis or human support. 

At a broader level, this moves marketing toward self-service and operations at scale, allowing teams to manage more campaigns with fewer resources, while support teams become less central for routine issues.  

Eventually, this can lower operational overhead and increase the speed of execution across paid media teams. 

Reducing Friction in Customer Service

For CX, this signals a shift toward more automated resolution of common issues without needing human support intervention. 

The problems that previously required tickets or back-and-forth with service teams are now being resolved at a faster rate, reducing waiting time and limiting disruption when something goes wrong. 

This shift also transforms the structure of support, with the assistant combining troubleshooting, guidance, and insight delivery in one system, meaning users are more likely to get immediate, contextual answers inside the platform they are already using, reducing friction and keeps workflows uninterrupted. 

With fewer cases getting escalated beyond the first layer of support, thanks to the 20% improvement in resolution rate, this means lower workload for CX teams and frontline agents, with more capacity to focus on complex or high-value issues that an AI cannot handle. 

This move toward embedded, AI-driven service models where assistance is proactive and continuous rather than reactive and ticket-based will improve consistency of experience and reduce delays across the customer journey. 

Meta’s Key Earnings Results

In its quarterly earnings report, Meta saw strong results in advertising revenue growth, higher ad pricing and impressions, increased user engagement across its platforms, and expanding adoption of AI tools for advertisers that improved campaign performance and support efficiency. 

• Meta reported total revenue of $56.3BN, up roughly 33% year over year 
• Advertising remained it dominant revenue source by generating $55BN, roughly 95% of total revenue 
• Roughly 3.56 billion people used at least one Meta app daily on average 
• Ad impressions increased by 19%  
• Average price per ad increased by 12%