Why Agentic AI is Taking Over in 2025 — and What This Means for Marketers
The Super Bowl has long been a cultural barometer for emerging trends. If something makes it to a Super Bowl ad, it’s officially mainstream. This year’s game made one thing clear: artificial intelligence isn’t just a niche technology anymore — it’s front and center. From Google showcasing how generative AI (GenAI) enhances everyday business tasks to OpenAI emphasizing that we're entering a new era, the message was clear: AI is transforming how we work, create and market.
From Content Generation to Intelligent Automation
Two years into the rise of ChatGPT, its most visible applications remain writing, summarization, translation and rewriting. While these are valuable use cases, they barely scratch the surface of AI’s capabilities. The next evolution — agentic AI — is poised to redefine how businesses, particularly marketers, leverage AI.
What is Agentic AI?
Agentic AI refers to AI models operating autonomously within workflows, making decisions about the next steps without human intervention. Unlike traditional AI tools that generate content on demand, AI agents act within a process, dynamically determining actions based on context.
For example, in a retail setting, these are incremental improvements that can be quickly achieved using agentic AI:
- AI can assess whether a consumer’s comment in a chat conversation signals purchase intent and then recommend a next step.
- Lead scoring can be automated, distinguishing between spam inquiries and high-value prospects needing follow-up.
- AI can manage personalized product recommendations dynamically, adjusting in real time based on customer behavior.
Why This Matters for Marketers in 2025
The shift to agentic AI means marketing automation will become smarter and more autonomous. Today, AI-powered chatbots and recommendation engines operate on static decision trees. With agentic AI, these tools will evolve into dynamic agents that self-adjust based on ongoing interactions.
Beyond real-time personalization, agentic AI unlocks opportunities in more sophisticated areas:
- Proposal and campaign generation: AI can draft customized pitches based on audience data.
- Deep research automation: AI agents can synthesize insights across multiple sources, as OpenAI’s deep research initiatives suggest.
While fully autonomous AI solutions require time to mature, businesses don’t need to wait for the “perfect” AI system. The real opportunity now is identifying small, incremental ways to integrate AI into existing workflows. This means going beyond text-based automation and embedding AI into decision-making processes — without requiring a dedicated AI team.
The Practical Next Step
For marketers, the focus should be on finding pragmatic, low-lift applications of agentic AI. Instead of using AI only for content creation, look for ways it can enhance lead qualification, customer interactions, or personalized recommendations. These small wins will lead to the next level of AI-driven efficiency, without the complexity of full automation.
AI has officially arrived in the mainstream, and agentic AI is the next phase. The question is no longer whether AI will change marketing, but how quickly businesses will adapt to these smarter decision-making systems. The companies that embrace this shift now will have the advantage in 2025 and beyond.
Seymour Duncker is executive strategist, AI and ML, Decision Counsel, a content marketing and strategy firm known for its dynamic activations and innovative growth strategies.
Seymour Duncker is executive strategist, AI and ML, Decision Counsel, a content marketing and strategy firm known for its dynamic activations and innovative growth strategies.
