PR agencies ramp up AI spending, but actual use cases remain narrow
PR agencies are investing heavily in artificial intelligence, yet their applications cluster around a handful of specific tasks, according to new research. The gap between budget allocation and practical deployment suggests many firms are still figuring out where AI delivers real value.
The research examined how PR agencies deploy AI tools and where they direct spending. Most agencies concentrate their efforts on a limited set of functions rather than integrating AI across their operations.
Where agencies are actually using AI
Content generation ranks among the most common applications. Generative AI and LLM tools help teams draft initial copy, social media posts, and pitch materials faster than manual writing alone.
Media monitoring and analysis represent another frequent use case. Agencies deploy AI to track mentions, analyze sentiment, and identify relevant coverage opportunities across news outlets and social platforms.
Research and insights generation also feature prominently. AI helps teams synthesize data from multiple sources and surface trends relevant to client campaigns.
Administrative work-scheduling, data entry, and report formatting-accounts for a smaller but measurable portion of AI usage in agencies.
The investment-to-application gap
Spending increases don't always match the breadth of actual use. Many agencies allocate budgets for AI capabilities they haven't yet integrated into workflows or haven't found practical applications for.
This pattern reflects broader organizational challenges: licensing costs, staff training requirements, and uncertainty about ROI often outpace the speed of adoption.
For PR professionals evaluating AI tools, understanding these real-world use patterns matters more than vendor claims about capability. Learning which applications actually move the needle for agencies in your sector helps guide investment decisions.
Those looking to build AI skills relevant to PR work can explore AI for PR & Communications training focused on practical applications in the field.
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