Agentic AI Explained: The Future of Autonomous Intelligence

Published 11/02/25 under:

Think of Artificial Intelligence (AI) as a super sponge, soaking up every tiny bit of data and then somehow puzzling that together to create a picture of the world as we know it, as well as predict the future.

But here’s the kicker: if the data is dodgy, the predictions will be too. It’d be like trying to bake a cake with salt instead of sugar.

AI has come a long way, evolving from simple automation to sophisticated generative models that create content on demand. However, the next frontier in AI is Agentic AI.

In a recent episode of Learning Kerv podcast, we explored the transformative potential of Agentic AI, highlighting its ability to solve current AI limitations and optimise business operations.

But how exactly does Agentic AI revolutionise the business landscape? Let’s break it down!

Understanding Agentic AI

While Generative AI is reactive – responding to prompts with generated text, images, or code – Agentic AI takes things further by introducing autonomy. As Learning Kerv guest Will Dorrington explains, “Agentic AI can plan, decide, and act to achieve goals with minimal input.” This means it can break down tasks into steps, gather relevant information, make informed decisions, and iterate until it reaches the optimal outcome – something that Gen AI lacks.

Agentic AI operates through multi-step reasoning and long-term planning, making it particularly useful in dynamic environments that require continuous adaptation and strategic execution. Unlike traditional automation, which follows predefined rules, Agentic AI dynamically assesses situations and adjusts its approach based on new data in real time.

Real-World Applications of Agentic AI

The potential applications of Agentic AI span various industries, driving efficiency, reducing costs, and enhancing decision-making processes. Here are some examples where it is making an impact:

• Workforce Optimisation: Agentic AI can automate employee scheduling and resource allocation, ensuring optimal workforce management.
• Customer Service: AI agents can handle complaints, resolve customer queries, and provide support without human intervention.
• Financial Management: It can analyse financial data, compare investment options, and generate necessary documentation with minimal oversight.
• IT Operations: As Will explains, “You can instruct an agent to proactively monitor a system, check for missing updates, install them, and report back.” This level of automation reduces manual IT workload and enhances security.
• Travel Planning: An AI agent could handle an entire holiday booking process – from flights to hotel reservations – based on user preferences.

Sustainability is also a growing concern in AI development. Agentic AI can contribute to energy efficiency through optimised AI models that leverage specialised AI chips and techniques such as pruning and quantisation, reducing energy consumption while maintaining high performance.

Ethical Considerations

In Season 1 episode 6 of Learning Kerv, we addressed the risks of AI misuse, such as deepfakes and phishing scams. While AI can be used for good, it can also be exploited for harmful purposes.

Dealing with these risks can be intimidating but it’s essential to have robust cybersecurity measures in place to ensure you can protect your privacy and data from any potential threats.

Governance, testing and human interference should always be a given when using AI applications, Will emphasises this, by stating “Businesses must conduct thorough testing, keep humans in the loop, and adhere to ethical AI guidelines to navigate the risks associated with autonomous agents.”

Future Outlook

Looking ahead, the potential of Agentic AI is immense.

According to Will, “By the end of 2025, we will see more maturity and adoption of agentic AI, with businesses leveraging it for advanced processes and personalised interactions.”

The future also holds exciting developments in AI ethics, explainable AI, and transparent AI, which will be crucial for public adoption and trust.

If you’re looking to break into the world of AI, as one of the Learning Kerv listeners is, Will shared his top tips: start with understanding how to use AI tools effectively before delving into the technical aspects. AI cannot give you the result you want without writing good prompts and understanding the history and development of AI models.

Want to dive deeper into the world of AI? Stream the whole Learning Kerv Series 1 on all platforms, including Spotify and Apple Podcasts..