Agentic AI: Definition, differences from generative AI, and impacts on advertising and creation.
Discover how Agentic AI is Transforming Advertising and Creation: Definition, Differences from Generative AI, and Impact on Professions
Agentic AI and Creative Professions: Definition, Use Cases, and Impacts in 2025
2025: The Year Agentic AI Changes Everything
After revolutionizing content creation with generative AI, artificial intelligence is taking a new step: Agentic AI.
Agentic AI doesn't just create content; it can also analyze, decide, and act autonomously. For agencies and creative professionals, this is not a substitution, but a lever for augmented creativity.
Simple Definition of Agentic AI
Agentic AI refers to autonomous agents capable of analyzing a situation, making decisions, and taking action to achieve an objective without constant human supervision.
Unlike classic automation tools, Agentic AI doesn't just follow programmed rules. It continuously adapts, learns from its environment, and adjusts its actions.
As explained by Anirban Mukherjee (AI researcher and consultant, Avyayam Holdings) and Hannah Hanwen Chang (Associate Professor of Marketing, Singapore Management University):
“Agentic AI can autonomously pursue long-term goals, make decisions, and execute complex, multi-turn workflows. Unlike traditional generative AI, which responds reactively to prompts, agentic AI proactively orchestrates processes.” — Mukherjee & Chang, “Agentic AI: Autonomy, Accountability, and the Algorithmic Society,”, arXiv, 2025
Generative AI vs. Agentic AI: The Key Difference
- Generative AI: Produces content (text, images, video) in response to a specific command.
- Agentic AI: Executes a complex mission from start to finish, combining analysis, creation, budget management, and optimization.
Concrete Example: A generative AI writes an advertising slogan. An Agentic AI designs the complete campaign, adjusts the budget in real-time, and provides a strategic report.
How Does an Agentic AI Work?
- Perception and Data Analysis: Agents collect and process multiple sources of information—market data, audience behavior, and social signals—to understand the context and identify opportunities.
- Autonomous Decision-Making: Based on the set objectives (conversion, brand awareness, engagement), the agent determines the best approach. This can range from choosing a channel and selecting a message to creating multiple variations of a single topic to broaden its impact.
- Action, Adjustment, and Scaling: Once the strategy is defined, agents execute campaigns, measure results, and continuously optimize them. They are able to easily duplicate an idea in different forms, change a title, adapt a visual, vary a tone, and test these variations on a large scale to maximize reach.
Benefits for Creative Professionals and Agencies
- Reduction of Repetitive Tasks: Agentic AI takes on a large part of the technical adjustments and campaign management. This allows creative professionals to focus more on conceptualization and innovation.
- Access to Concrete Insights: Instead of simple raw data, agents deliver directly actionable information: what trends are emerging, which messages are captivating a given audience, or which segments are responding best.
- Enhanced Efficiency: Decisions are based on real-time data, allowing for faster and more relevant action.
- Agents Aligned with Business Needs: When configured with a clear objective, agents become true work partners. They deliver quality results, provide a relevant complement to human teams, and strengthen collective effectiveness.
“Agents are smarter. They’re proactive – capable of making suggestions before you ask for them... they improve over time because they remember your activities and recognize intent and patterns in your behavior.” — Bill Gates (Atera)
Limitations and Points of Caution
- Potential Loss of Control: If objectives are not clearly defined.
- Data-Dependent Quality: An Agentic AI is only as good as the data it relies on. Incomplete or biased data can lead to poor choices.
- The Central Role of Humans: Creativity and strategy remain irreplaceable skills.
Conclusion: An Ally for Creativity
Agentic AI is not here to replace creative professionals but to handle operational complexity. The result: more time to invent, less time spent managing. It’s a true invisible partner that allows human talent to fully express itself.
Agentic AI is less a threat than an ally: it manages complexity to unleash imagination.
FAQ: Understanding Agentic AI
1. What is Agentic AI in simple terms? Agentic AI refers to autonomous agents capable of analyzing a situation, making decisions, and taking action to achieve an objective without constant human supervision. Unlike simple automation, it learns and adapts continuously without needing constant human oversight.
2. What is the difference between generative AI and Agentic AI?
- Generative AI: Creates content (text, images, video, sound) from a specific request.
- Agentic AI: Manages a mission from start to finish, combining analysis, strategic choice, and execution.
3. What are the impacts on advertising and creation? Professions are evolving toward roles of coordination and supervision. Creative professionals remain at the center, but their mission shifts toward:
- Defining creative intentions
- Orchestrating AI-augmented workflows
- Ensuring ethical standards and strategic consistency
4. What are the advantages and limitations of autonomous agents?
- Advantages: Time savings, reduction of repetitive tasks, more personalized campaigns, and support for creativity through precise insights.
- Limitations: Risk of system dependency, data-related biases, and the need for human oversight to guarantee quality and meaning.
5. How can an agency start using Agentic AI? By taking a step-by-step approach:
- Start by automating simple tasks (A/B testing, reporting).
- Train teams to work with agents.
- Adopt a hybrid approach where AI proposes and humans validate.
