The comms world is on the cusp of another AI evolution. While we've all gotten (fairly) comfortable with LLMs cranking out branded social media posts and polishing press releases, agentic AI represents something far more transformative.
Agentic AI is artificial intelligence that doesn't just respond to our prompts, but actually thinks ahead, makes decisions, and takes action.
A standard LLM might craft a compelling product launch announcement when prompted. If you want further adjustments, the user prompts and tweaks again, until the task is complete.
An agentic AI system, however, continues working toward its goals even when a human isn’t there to babysit. It could monitor industry trends, detect the optimal timing window, automatically segment target audiences, draft personalized pitches for different journalist beats, schedule distribution across time zones, and then track engagement—adjusting the approach in real-time based on what's working.
To be fair, some of this is aspirational. The tech needs to develop, as does our ability to trust agentic AI to have this kind of autonomy without excessive risk.
Or, as PRophet CMO Jason Brandt winkingly puts it: “Very few agents—perhaps none—are autonomous at this point. But that’s the end goal, of course...without them destroying us.”
The scene: Your brand wants to partner with as many micro-influencers as possible in advance of a new product launch. But doing proper discovery and vetting, at scale, isn’t feasible.
Agentic AI is already embedded in products like PRophet Influence, which leverage the tech to make basic influencer discovery more efficient. This conversational style interface—the ability to ask the interface to “find influencers that fit this specific profile”—is agentic, but fairly simple, says Brandt.
Greater layers of complexity could make influencer management much more automated. For instance, a fully agentic system could:
Obviously, this puts a great deal of faith in the accuracy of your agentic system. When AI agents directly engage with potential collaborators by sending messages and discussing terms, your brand or agency needs to weigh the efficiency gains against potential risks. This is why the current level of agentic autonomy is still modest, despite the field’s aspirations.
Looking ahead to the next six months, expect to see more sophisticated agentic solutions across the comms, PR, and social media space.
That means things like enhanced multimodal monitoring (analyzing images, audio, and video alongside text), or improved integration of standalone AI tools into coordinated “autonomous” functions across the marketing tech stack.
The agentic applications for influencer marketing are pretty diverse. Influencer-focused agents could:
The real shocker will be systems that can seamlessly coordinate across multiple channels while maintaining consistent brand voice and strategic alignment.
We’re long past the point where it’s business-savvy to pride yourself on old school tactics alone. A future-proofed team will learn to “love the machine,” and the most successful marketing and comms professionals will learn how to partner with these agents as seamlessly as possible.
As the tech is improving daily, being able to focus on the human stuff—strategy, relationship building—offers a good model for how to get the most value out of any tech and people investment.
