Agentic AI: Making AI Work For You

AI is Evolving – Enter Agentic AI

Artificial intelligence has come a long way. We’ve seen the rise of generative AI, like ChatGPT and DALL·E, which can generate text and images on demand. But now, there’s something even more powerful on the horizon called Agentic AI. Unlike generative models that rely on human prompts, Agentic AI operates independently, perceiving its environment, reasoning, planning, and carrying out tasks without constant human input.

This shift from passive, response-driven AI to dynamic, decision-making AI marks a significant transformation. Instead of just assisting, AI is now playing a more active role; automating workflows, optimising processes, and responding in real time to changes.

How do AI Agents work?

At the heart of Agentic AI are intelligent agents; autonomous systems that monitor, analyse, and act based on real-time data. These agents execute tasks, make decisions, and adapt to evolving conditions, making them invaluable across both public and commercial services.

AI in Healthcare and NHS services: AI supports patient triage by assessing symptoms and prioritising urgent cases, helps allocate hospital resources more efficiently, and automates administrative tasks such as appointment scheduling and medical record management, reducing pressure on staff and improving patient outcomes.

AI in Local Government operations: AI agents enhance citizen services by managing council inquiries, processing applications for benefits and permits, and automating responses to routine queries. They also assist in waste collection scheduling, environmental monitoring, and public safety reporting, ensuring more efficient service delivery and faster response times for local communities.

By automating these tasks, Agentic AI frees up human workers to focus on strategic and complex challenges, improving efficiency and service quality.

Scaling Up: When One AI Isn’t Enough

As Agentic AI develops, managing complex workflows requires orchestration and specialist knowledge. To make Agentic AI work effectively for these tasks, organisations need to leverage superagents, small language models (SLMs), and event-driven architectures.

Superagents: Orchestrating AI for End-to-End Task Management

If Agentic AI were the world of James Bond, superagents would be M, calmly orchestrating missions from behind the scenes, ensuring every agent is in the right place at the right time. James Bond himself? That’s the specialised AI agent, skilled at executing highly specific tasks with precision. Just as M assigns Bond a mission and equips him with the right tools, superagents oversee AI systems, ensuring each agent has the right data, tools, and objectives to function optimally.

Coming back to reality, a superagent is a lot like an AI Project Manager, for instance a legal superagent could oversee an AI-driven case management system by orchestrating one agent to review contracts, identifying key clauses and potential risks; another to monitor real-time legal changes, ensuring firms stay compliant; and a third to conduct case law research, cross-referencing precedents to support solicitors. In this example the superagent ensures that all actions are taken, and all findings are presented efficiently to human legal professionals.

Small Language Models (SLMs): Bringing Deep Expertise to AI Agents

While superagents ensure task orchestration, Small Language Models (SLMs) provide deep, specialised knowledge within each AI agent’s role. Unlike Large Language Models (LLMs) that are generalist, SLMs are tailored for specific domains, making them ideal for precision-based AI tasks.

Legal AI agents use SLMs fine-tuned on legislation and case law to enhance contract analysis and compliance monitoring.

Healthcare AI agents leverage medical SLMs to provide diagnostic support or summarise patient histories accurately.

Financial AI agents use SLMs optimised for fraud detection.

By embedding SLMs within AI agents, organisations benefit from highly accurate, efficient, and cost-effective AI applications that work in harmony under the guidance of superagents.

By combining superagents for orchestration and SLMs for expertise, Agentic AI becomes more than just an automation tool, it becomes a fully integrated system capable of managing complex, multi-step tasks with precision and efficiency.

AI Agent That Reacts Instantly: Event-Driven Architecture

Event-driven architectures are primed to work with Agentic AI in the same way that Small Language Models (SLMs) provide deep expertise to AI agents. While SLMs enhance an agent’s specialised knowledge, event-driven architectures allow AI agents to react dynamically to real-time changes without human intervention.

Unlike traditional AI that waits for prompts, event-driven AI is continuously listening for specific triggers, such as changes in data, system anomalies, or external events. When a trigger occurs, the relevant AI agents are activated instantly, allowing for immediate and appropriate responses.

For example, in a fraud detection system, an event-driven AI architecture could monitor real-time banking transactions. If an unusual spending pattern is detected, an AI agent could immediately flag the transaction, another could cross-reference it with past behaviour, and a third could either approve or block the transaction based on risk assessment. This makes event-driven architectures essential for scenarios where timing and accuracy are critical.

By staying proactive rather than reactive, these systems help public services and commercial sectors become more responsive and efficient.

The Future: Agentic AI as an Independent Problem Solver

The shift from generative AI to Agentic AI represents a major advancement in artificial intelligence. By integrating intelligent agents, orchestrated AI systems, event-driven architectures, and small language models, public services and businesses alike can automate complex processes, optimise decision-making, and respond instantly to real-world events.

We’ve already seen how AI has helped police forces, Agentic AI will play an increasingly important role in enhancing efficiency, supporting public services, and enabling AI-powered autonomy across industries. The future of AI isn’t just about assisting humans anymore, it’s about working alongside them to improve services, support decision-making, and drive automation where it’s needed most.

How Simpson Associates can help

Artificial intelligence is evolving rapidly, and our experts at Simpson Associates know exactly how to help you integrate it into your organisation. With the right guidance you can leverage AI effectively to achieve your goals and drive success.

Read more about Simpson Associates AI Assessment or reach out to us via live chat to get started on your AI journey today.

Blog Author: Ashley Armstrong, Head of Presales and Solutioning at Simpson Associates