The AI Agents Guide: Leading Your Organisation into the Agentic Era
Dear Tech Enthusiasts,
We’re back!
This month, our newsletter is all about your AI Agents Guide, which will take you from the fundamental "what" to the practical "how," giving you the clarity needed to lead your organisation into the agentic era.
Here's what you can expect in today's issue:
🤫 Want a shortcut? Go to the bottom of this newsletter to find a list of the linked content, or download your AI Agent 2025 Guide
Let's clear up a common misconception.
While a chatbot is designed for conversation, an AI Agent is designed for action. This is the critical difference between an AI that can merely talk and one that can truly act on your behalf. Using powerful techniques like Retrieval-Augmented Generation (RAG), they can access and reason over your company's knowledge to perform their work accurately using tools.
Grasping this new reality is the first step to building a future-proof strategy for the next wave of technological change.
And to lead the charge, you need to speak the language. The world of AI Agents comes with its own terminology, but it boils down to three core concepts:
✔ An AI Agent is your fundamental building block, an autonomous entity performing tasks to reach a goal.
✔ A Single Agent is a pattern where one AI Agent operates individually to provide services on a limited scope.
✔ Agentic AI is a system where multiple, specialised AI Agents collaborate to solve complex problems with minimal human oversight.
Understanding these distinctions is the first step to architecting a truly intelligent system. For more foundational information, see our AI Agent FAQ.
Once you understand the 'what', the immediate next question is the 'how'.
The good news is, you're not starting from scratch. The major cloud platforms are all rolling out powerful ecosystems to support agentic AI. Whether you're leveraging Microsoft's AI Agents, exploring the AWS AI Agentic Ecosystem, or building with Google Cloud's Vertex AI, the tools are becoming more accessible.
The key is to have a solid foundation, which means preparing your data infrastructure to be "agentic-ready". A well-designed data platform is the engine that will power your agents' success.
This transformation is not just about technology – it represents a fundamental shift in how we think about, organise, and utilise data. Laurent LETOURMY , EMEA Alliance Manager Snowflake
The potential is clear, but the starting line can seem blurry. For leaders, the core strategic question is: should we build a custom solution or buy a ready-made one? Your first step is to frame your strategy.
We recommend basing your decision on the "AI Tech Sandwich" by Gartner.
💰 You can BUY a pre-made solution (the green layer of the sandwich), offering speed and simplicity, getting you to a solution quickly.
🧱 You can BUILD a custom agent from foundational models (the blue layer of the sandwich), providing a custom-fit solution tailored perfectly to your unique processes.
🍅 In between are the fillings - you can make solutions using low-code or no-code frameworks that offer a blend of customisation and speed.
The right choice depends entirely on your specific use case, resources, and strategic goals.
The true power is unlocked when multiple, specialised agents collaborate in an Agentic AI system. Building such a system requires a robust architecture. New frameworks are emerging as the engines for these multi-agent systems, allowing your teams to design and deploy collaborative agents that mirror, and even improve, your business workflows.
As you deploy more agents, they need a common language to collaborate effectively.
As you deploy more AI agents, their ability to collaborate effectively becomes crucial. This is especially true when using agents from different platforms. This is where Agent-to-Agent (A2A) communication protocol (or ACP) become essential. This protocol provides a common language, enabling agents to seamlessly hand off tasks to one another and enabling complex, automated workflows.
The rise of agents doesn't mean the end of human jobs; it means the evolution of them.
As a leader, you must ask yourself: are you ready to be the boss of a hybrid human-AI team? Your teams will move from doing tasks to managing and directing their new digital colleagues. This new reality is already impacting specific roles; Project Managers for instance, but isn’t a wholesale replacement.
So, rushing in without a strategy can be perilous. The fintech company Klarna famously had to rehire 700 employees after an overzealous AI implementation led to a drop in service quality. The lesson is clear: prioritising cost-cutting over quality is a mistake. The future is collaborative, where humans guide, oversee, and work alongside their new digital colleagues, making the "Human-in-the-Loop" concept more critical than ever.
As you integrate agents, their status evolves from a simple tool to a core strategic asset. This reflects a mature strategy where agents are not just an IT project, but a C-suite concern that directly impacts the company's market position.
There are two primary paths to get started:
So, which path first?
Often, the Quick Win path is the best start. A successful MVP provides the business case and the internal excitement needed to fund the broader, more strategic path.
With a strategy in mind, it's time to execute. You have two primary paths to begin your journey.
Your "Build vs. Buy" decision comes to life with the tools you choose. The ecosystem is rich with options:
💰 BUY: This includes off-the-shelf agent solutions or platforms with strong agentic features. Solutions on platforms like ServiceNow can automate complex enterprise workflows with pre-built capabilities. However, ServiceNow also provides robust tools for building custom, low-code or even full-code agentic workflows, blurring the line between buying and building.
BUILD: Low-Code vs. Full-Code.
🧩 LOW-CODE: These platforms allow for rapid development with minimal coding. The Microsoft ecosystem is a prime example, offering a suite of tools that empower teams to build and deploy agents quickly. For rapid development and prototyping, low-code platforms like Copilot Studio enable business users to quickly create agents.
⌨ FULL-CODE: For a fully custom solution, you'll turn to powerful cloud platforms and frameworks.
This flexibility allows teams to choose the right development path based on the project's complexity and their internal resources.
An agent is only as good as the trust you can place in it.
Deploying an autonomous workforce introduces a new class of risk that requires C-suite-level attention. This means ensuring your agents are transparent, fair, and accountable for their actions, so that your customers and regulators can trust.
Theory is good, but results are better.
Companies are already reaping the benefits of AI Agent implementation.
These examples prove that whether it's enhancing support efficiency or tackling complex project management tasks, AI Agents are already delivering a measurable return on investment.
📅 Want to see how AI Agents can deliver these results in your specific industry? Join us at one of our upcoming events to see live demos and learn from our experts:
Or rewatch past events on AI Agents:
The transition to an agentic enterprise is one of the most significant strategic opportunities of this decade. You have the ambition. We’ll help deliver the impact.
Your journey starts now, with a clear vision, the right partners, and a single, high-impact use case. It’s about building a more intelligent, responsive, and effective organisation
To continue your learning, we recommend downloading our new AI Agent whitepaper for a full strategic overview:
We want to know your thoughts and questions about AI Agents. What are your biggest challenges? What opportunities excite you the most?
Drop a comment on the right 👉🏻
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Thanks to all our experts for their contributions in creating this knowledge base Olivier Mallet & Laurent LETOURMY ⭐ Download the whitepaper here: https://www.devoteam.com/whitepaper/enterprise-ai-agents/