Are you ready for Agentic AI?

Agentic AI is no longer a futuristic concept – it’s moving quickly into real-world applications, bringing new capabilities that can fundamentally change how organisations operate. For IT leaders, understanding and preparing for this shift is paramount.

What is Agentic AI?

At its core, Agentic AI refers to intelligent systems capable of operating autonomously to achieve specific goals, often by interacting with other systems, data, and even humans in a non-deterministic, human-like way. Unlike traditional automation, which follows predefined rules, agents can make independent decisions, adapt to new information, and learn from experience. Think of them as more than just an API – they can understand context and work with “fuzziness” to achieve well-governed objectives, similar to a human making a complex decision rather than applying a rigid formula.

The capabilities of Agentic AI are rapidly evolving. While fully autonomous agents are still developing, we are moving towards a future where these intelligent entities will be central to business operations.

How Will Agentic AI Affect IT Leaders?

The arrival of Agentic AI presents both immense opportunities and significant challenges for IT leaders. It’s not just about adopting a new technology. It’s about fundamentally rethinking how work is done, how decisions are made, and how IT solutions support these dynamic new capabilities.

Here are some key areas of impact:

Strategic re-evaluation: IT leaders will need to assess where Agentic AI can provide the most strategic value within their organisation. This goes beyond simple task automation to identifying complex processes where autonomous decision-making can drive efficiency, innovation, and competitive advantage.
Governance, risk, and control: As agents progressively take on more decision-making roles, the need for robust governance, risk, and control frameworks becomes increasingly critical. How will decisions made by agents be tracked and audited? What ethical considerations need to be addressed? IT leaders must establish clear guidelines for the deployment and operation of Agentic AI, especially in highly regulated industries like insurance, where compliance with specific standards is essential for approving claims or policies.
Data readiness: Agentic AI thrives on data. IT leaders must ensure their organisations have comprehensive, accessible, and high-quality data to feed these intelligent systems. This includes addressing existing data access challenges and establishing new data pipelines, as well as strategies to support autonomous operations.
Legacy systems: Antiquated systems often aren’t ready to leverage the power of Agentic AI. To take advantage of Agentic AI, organisations need agile and interoperable platforms that are adaptable. They need modern architectures that can handle dynamic workflows, integrate data seamlessly, and enable new types of interactions.
Process transformation: Before deploying Agentic AI, organisations must have a deep understanding of their existing processes. This is akin to legacy modernisation – you can’t improve something until you understand it. IT leaders will need to lead business process analysis, rationalisation, and optimisation efforts to identify the most suitable areas for Agentic AI integration and ensure it fits seamlessly into existing workflows.
Skill set evolution: The IT workforce will need to evolve. While traditional development skills remain important, there will be a growing demand for professionals who understand AI ethics, governance, data architecture for AI, and how to design and manage agent-driven systems.
Platform approach: The rapid evolution of Agentic AI necessitates a platform-centric approach. IT leaders should prioritise platforms that provide the tools, reusability, and robust governance to manage agent development, deployment, and oversight. This ensures scalability, consistency, structured learning through feedback, and control.

Getting Ready: Your Action Plan for Agentic AI

The time to prepare for Agentic AI is now. It’s coming fast, so IT leaders need to position their organisations to ride this wave successfully. Here’s what you need to do:

1. Assess your readiness: Begin by conducting a baseline assessment of your organisation’s current state across three critical dimensions:

Governance: Do you have a clear framework for decision-making, risk management, and accountability in an AI-driven environment?
Data: Is your data accessible, clean, and structured in a way that supports AI applications?
Processes: Do you have a clear understanding of your business processes, and have you identified areas ripe for AI integration?

2. Define your agentic AI strategy: Identify where Agentic AI can deliver the most impact for your business. This involves understanding your strategic objectives and mapping them to potential AI use cases. Don’t aim to automate everything at once – start with high-impact, manageable projects.

3. Modernise your legacy systems: Agentic AI needs to be connected to your core systems and data. This often means addressing legacy modernisation. Prioritising platforms that can digitalise and streamline processes is crucial.

4. Embrace a platform approach: To effectively manage and scale Agentic AI, a robust platform is essential. Seek solutions that offer:

Comprehensive tooling: Tools for building, deploying, and managing AI agents.
Reusability: Mechanisms for reusing components and models across different applications.
Governance and control: Features for managing deployments and vetting code, plus ensuring compliance.
Integration capabilities: The ability to seamlessly connect with existing systems, whether on modern platforms or legacy environments.

5. Pilot and learn: Start with small, focused pilot projects to gain experience and demonstrate value. This allows you to learn, refine your approach, and build internal expertise.

6. Collaborate and leverage expertise: You don’t have to navigate this alone. Engage with external partners to share learnings and determine best practices. Internally, leverage existing expertise in governance and architecture, as well as business process analysis.

7. Invest in skills development: Prepare your teams for the future of work by investing in training and upskilling programs related to AI, data science, and agent development.

By proactively addressing these areas, IT leaders can ensure their organisations are not just ready for Agentic AI but are positioned to harness its full potential, transforming challenges into opportunities and accelerating their journey towards an intelligent future.

Agentic AI is here. We can help you chart the path forward. Talk to us.