2025 has been heralded as the year of AI agents. Several major players have recently announced agentic solutions, including Google and NVIDIA, and many in the industry are touting AI agents as the next frontier of artificial intelligence. In fact, a recent survey found that 77% of IT executives are ready to invest in agentic AI this year.
But what is agentic AI, and how does it differ from existing forms of artificial intelligence?
Agentic AI 101
Agentic AI refers to AI systems that operate with a high degree of autonomy, meaning they can independently take actions to achieve goals. Unlike conventional forms of AI, which primarily respond to inputs or follow predefined rules, agentic AI can plan, reason, and execute multi-step processes without continuous human intervention. The intelligence behind the agent’s decisions comes from large language models (LLMs).
For example, generative AI models such as ChatGPT or Gemini create outputs based on the user’s instructions. However, they cannot take further action without additional inputs. By contrast, agentic AI can plan and execute tasks end-to-end based on the final goal or outcome it’s been instructed to achieve.
Crucially, agentic AI can also learn from previous interactions and optimize its approach over time. This enables agentic AI systems to simulate human-like decision-making in complex environments, making them useful for a number of dynamic and unpredictable scenarios. This unpredictability is also a feature of true AI Agents in that their workflow and output isn’t fully deterministic.
Many modern AI agents use LLMs like GPT-4 and external tools, such as web browsers, APIs, and databases, to complete tasks or realize outcomes. This is what allows them to gather real-time data, reason through problems, and take actions beyond simple text or image generation.
Agentic use cases for marketing and PR
For marketers and PR professionals, agentic AI has the potential to make campaigns more efficient, personalized, and data-driven. As these systems become more advanced, businesses that leverage AI agents effectively will gain a massive competitive advantage.
Some possible use cases for agentic AI include:
- Content management: AI agents can write and publish blog posts, press releases, social media posts, and other forms of content tailored to specific audiences. They can also respond to social media interactions without human intervention; adjust tone and messaging based on audience sentiment and engagement data; and dynamically tweak copy, headlines, and landing pages based on live audience behavior.
- SEO optimization: AI agents could continuously analyze evolving search trends, recommend keywords, and update website content to improve SEO rankings.
- Audience segmentation and dynamic ad targeting: When setting up an ad campaign, AI agents could analyze customer data and create detailed audience personas. Once the campaign has launched, digital teams can leverage AI agents to automatically adjust ad spend, placement, and messaging based on user interactions and performance.
- Predictive customer engagement and nurture: Using historical audience data, AI agents could identify when a customer is most likely to engage and automate its outreach at optimal times. Agents can also track customer engagement data and autonomously follow up with high-value leads.
The future of agentic AI
We are in the early stages of agentic AI, but the technology is rapidly evolving. As agentic AI advances, future agents will become more capable, personalized, and seamlessly integrated into everyday workflows.
However, with this power comes the responsibility to ensure AI remains aligned with human values, responsible AI principles, and security best practices. As with other forms of AI, governance frameworks, safety mechanisms, and human oversight will be crucial to mitigating cybersecurity and ethics concerns. After all, the future of AI isn’t just about smarter systems—it’s about building AI that we can trust.
Want to learn more about the latest developments in artificial intelligence? Visit the MG Labs page to explore our AI tool reviews, testing insights, and more.
