Alongside the surge in generative AI, a new paradigm is emerging: agentic AI. Unlike generative AI systems, such as ChatGPT from OpenAI and Copilot from Microsoft, which are designed primarily to generate content, agentic AI systems can reason and act autonomously towards defined goals.

In other words, it's a form of AI that does not simply answer prompts from the user. It acts as a truly autonomous agent. In this article, we will explore why agentic AI is the future of artificial intelligence.

What is an Agentic AI?

The Agentic AI is an approach where the AI systems go beyond responding to isolated prompts. Instead, they are built to reason about it, make decisions and take actions to achieve specific goals.

For example, while a generative AI like ChatGPT might help draft an email, an agentic AI could write the email, check your calendar, schedule the meeting, and even follow up with participants—all with minimal human supervision.

The entire process enables the agentic AI to perceive its environment by analysing data, sensors, text and images. Their reasoning is based on breaking down targets into multiple sub-tasks. This enables them to act autonomously and execute actions using tools and software.

With experience, an agentic AI can learn and adapt to the user's preferences based on feedback. In summary, an agentic AI has intentions and goals, and takes the initiative to achieve them.

How Agentic AI Differs from Generative AI?

As you might have guessed, there are significant differences between agentic and generative AI. A generative AI model responds to a prompt. For example, the prompt could be 'What is the weather like in London?'. The generative model would simply answer the question.

In contrast, an agentic AI model understands the goal, considers the options and then takes action. It turns the initial request into something more substantial. It plans the entire journey, compares flight prices, books accommodation and adds the event to your calendar.

In essence, agentic AI acts as a proactive assistant rather than a reactive tool, bridging the gap between understanding a user’s intent and executing complex tasks with minimal supervision.

Opportunities, Risks, and the Future of Agentic AI

Using an agentic AI model can be highly beneficial for business teams as it can perform and automate complex tasks, thereby increasing productivity and acting as an intelligent, multitasking assistant.

However, while agentic AI offers remarkable capabilities, it also comes with significant risks. A lack of human control over autonomous decision-making can lead to unintended consequences. These systems may amplify errors, producing inaccurate or misleading outputs.

There are also serious concerns regarding security and bias, as agentic AI can exploit vulnerabilities or perpetuate existing inequalities if it is not properly monitored and regulated. Therefore, careful oversight, robust safeguards and ethical guidelines are essential to ensure these systems are used safely and responsibly.

The future of agentic AI lies in multi-modal, collaborative agents that are seamlessly integrated into our everyday environments, whether at work, at home or in smart cities.

These agents will be able to process multiple types of data, interact with humans and other AI systems, and coordinate complex tasks across various domains. The vision is of AI systems that are proactive collaborators, not just tools, enhancing efficiency, convenience and decision-making in ways that are deeply embedded in our daily lives.