2025 was quite a whirlwind year for generative AI adoption. And despite disagreement about the ROI so far, there’s little sign that AI growth will slow at all in 2026. Catch your breath as best you can now and brace for the next wave: Agentic AI.
At this point, many publishers have started using AI to get content started and/or analyze audience data. Agentic AI will go a few steps further by helping publishers’ teams take action. This isn’t “assistive AI.” It’s AI as a teammate.
Think of the possibilities:
- Newsletters that build themselves
- Audience segments that appear automatically
- Campaigns that optimize without waiting for humans
- Insights that come with recommended next steps (or already taken ones!)
And for publishers battling tool sprawl, slow workflows, and the eternal data–action gap…this is huge.
Are you ready for it?
What is agentic AI?
Agentic AI refers to systems that don’t just answer questions or assist with tasks. They autonomously take action based on goals, rules, and real-time data.
- Instead of prompting a model with “Draft a newsletter,” agentic AI will learn your style and build the newsletter itself, including copy, personalization, layout, and segment-specific versions.
- Instead of “Pull an audience report,” an agent will automatically analyze your data, find anomalies, and suggest (or even execute) next steps.
- Instead of: “Which segments should we target for this event?” agentic AI will identify micro-segments, generate campaign variants, schedule them, test messages, and optimize based on performance.
For publishers, this marks a shift from AI as a tool to AI as a collaborative worker. It will be able to handle time-consuming, repeatable tasks so teams can focus on strategy, creativity, and relationship-building.
This concept is a bit worrisome for many publishers, media operators, and their teams. Can/should we really “let agents loose” to function autonomously? How will this impact people’s jobs and futures? Entry-level employees’ training and learning? The human connection that is foundational to media and publishing?
These are legitimate questions, and addressing them is part of being organizationally ready to adopt and scale agentic AI.
Why agentic AI Is a game-changer in media
1. It closes the data–action gap.
Most publishers say data is a competitive advantage, but few act on it consistently. Agentic AI helps teams:
- Clean and classify audience data
- Identify high-value segments
- Trigger campaigns automatically
- Recommend or launch next-best actions
It turns passive dashboards into active workflows.
2. It enables true personalization at scale.
Manual segmentation always hits a ceiling.
Agentic AI can continuously:
- Discover micro-audiences
- Tailor content and offers
- Adjust messaging in real time
…without adding more headcount.
3. It makes operations dramatically more efficient.
Agentic systems can execute tasks that normally require coordination across marketing, editorial, product, and revenue teams. This reduces:
- Time-to-market
- Manual handoffs
- Operational drag
- “Set it and forget it” workflow failures
4. It helps publishers compete with platforms.
The big platforms already run agentic, data-powered systems:
- TikTok recommends
- Amazon optimizes
- Google experiments
- Meta rebalances
Agentic AI lets publishers reclaim speed and sophistication without needing platform-scale engineering.
Getting ready for agentic AI
Across the media industry, AI has already shifted from hype to habit. Many publishers use AI for content tagging, headline testing, trend spotting, and analytics support. But a new wave of capability, agentic AI, is poised to reshape how publishers work, create, monetize, and serve audiences altogether.
If the first phase of AI helped teams analyze and automate, agentic AI helps them act.
Here’s what publishers can do now to prepare for what’s coming next.
1. Get your first-party data house in order.
Agentic AI is only as strong as the data feeding it.
Publishers should focus on:
- Converting unknown to known users
- Consolidating data into a unified platform
- Standardizing taxonomy, tagging, and naming conventions
- Practicing good data hygiene
Poor data = poor outcomes
Clean, unified data = powerful agents
2. Build clear rules, guardrails, and governance.
Agentic AI works best when it knows:
- What it can do
- What it shouldn’t do
- What success looks like
- When it needs human review
Publishers should define:
- Brand voice guidelines
- Editorial standards (especially around accuracy and ethics)
- Approved data sources
- Automation limits (when to pause, escalate, or ask for human oversight)
AI should take action, but not without direction and supervision.
3. Identify high-impact workflows to automate first.
Start with repetitive, rules-based, or labor-heavy tasks.
- Audience segmentation and scoring
- Campaign setup and personalization
- Content tagging and metadata
- Newsletter versioning
- Lead routing and sponsor reporting
- Churn prediction and retention nudges
If it happens every week, AI can likely assist, or even own it entirely.
4. Train your teams to collaborate with AI, not compete with it.
Agentic AI changes roles, not relevance.
Teams should be coached to:
- Use AI for production, so humans can focus on strategy
- Review AI-generated insights with editorial judgment
- Become “editors of intelligence,” not just content
Upskilling is not optional. It’s the bridge to higher-value work.
5. Invest in platforms built for activation, not just analysis.
AI thrives in environments where:
- Data is centralized
- Content is structured
- Campaigns can be triggered automatically
- Results flow back into the system
Tools that unify CDP + campaign orchestration + content metadata offer the ideal foundation.
Without workflow integration, agentic AI becomes just another siloed assistant.
6. Start small, experiment often, and scale what works.
Agentic isn’t a flip-the-switch upgrade. It’s an iterative, test-and-learn journey.
Publishers should:
- Launch a pilot workflow
- Measure time saved and outcomes improved
- Expand to adjacent processes
- Build confidence and trust before scaling
The publishers who start now will leap ahead.
What success looks like in the agentic era
Publishers and media operators that prepare effectively for an agentic AI future stand to unlock meaningful gains across both revenue and operations. With the right foundations in place, teams can launch campaigns faster, personalize experiences more deeply, and drive higher conversion and retention. Advertising attribution becomes clearer, cross-team collaboration more efficient, and tool sprawl easier to contain. Perhaps most importantly, data starts to feel usable instead of overwhelming, turning insight into action and strengthening value for sponsors and partners.
As part of your organizational change management, assure team members that agentic AI won’t replace human creativity, instincts, relationships, or storytelling. What it will replace is friction. It will eliminate bottlenecks, streamline workflows, and remove the countless manual tasks that slow teams down, freeing publishers to act on the insights they already have and focus on the work that truly moves the business forward.
The bottom line
Agentic AI isn’t some distant future. It’s the next evolution of how digital publishing works, and it’s coming just as fast as generative AI did. The good news is, publishers don’t need to overhaul everything at once, but they do need to start preparing their data, workflows, and teams today.
Are you ready to get ready for agentic AI on your teams? Omeda can help with data hygiene, unification, content tagging, and more. Get in touch with us to start laying the right groundwork together.
