Digital Explainer: What is agentic AI and what AI systems are driving 2026?

Agentic artificial intelligence is an artificial intelligence (AI) system that can accomplish a specific goal with limited supervision. It consists of AI agents: systems based on machine learning models that mimic human decision-making to solve problems in real time. In a multi-agent system, each agent performs a specific subtask. An AI agent can work from normal speech inputs because they can use advanced natural language processing techniques of large language models (LLMs) to comprehend and respond to inputs.

What’s an AI agent?

It’s a system that autonomously performs tasks by designing workflows with available tools. AI agents can perform a wide range of functions. AI agents solve complex tasks across enterprise applications, including software design, IT automation, and code generation. The latter is creating a debate about copyright in code because copyright is a property right which subsists in a work (and that can be code; the law principally speaks of authors of works being people creating it, but if AI agents create it, who is the author?

Unlike traditional or standard AI models, which operate within constraints and require human intervention, agentic AI exhibits autonomy, goal-driven behaviour, and adaptability. ‘Agentic’ refers to these models’ agency, or their capacity to act independently and purposefully.

AI was the buzz term of 2025, but in 2026 we are seeing it embed more and more in business and people’s everyday lives. Many search engines now include an AI element, and everyone is looking at AI automation of tasks, both in business and in their personal lives. AI is now being talked of as a co-worker, assistant, or even teammate. Agentic and multi-agent AI systems can manage workflows once controlled by humans, while humanoid and physical robotics have advanced from demonstrations to pilot deployment in factories, warehouses, and labs (and increasingly, on pavements as delivery vehicles), marking the dawn of physical AI.

Yet, 2026 may also bring a reality check. Gartner, a leading research and advisory company providing business and technology insights on IT to C-suite executives, predicts that more than 40% of agentic AI projects will be cancelled by the end of 2027 due to escalating costs, unclear business value, or inadequate risk controls. Carefully planned use cases and strong, consistent AI governance will become essential for any organisation hoping to scale beyond pilots.

If AI becomes your assistant, you need to understand its limits and your legal risks. The UK is still debating a bespoke AI law, and different parts of the world are taking distinct regulatory approaches, but in all cases, existing laws have impact and consequence.

The EU AI Act currently prohibits some uses like:

• deploying subliminal, manipulative, or deceptive techniques to distort behaviour and impair informed decision-making, causing significant harm.
• exploiting vulnerabilities related to age, disability, or socio-economic circumstances to distort behaviour, causing significant harm.

When integrating AI into your business, you need to be asking questions about what the AI can do, and what guardrails you have around your systems.

What is general purpose AI?

General purpose AI (GPAI) is another important type of AI. The EU AI Act defines GPAI as:

“an AI model, including where such an AI model is trained with a large amount of data using self-supervision at scale, that displays significant generality and is capable of competently performing a wide range of distinct tasks regardless of the way the model is placed on the market and that can be integrated into a variety of downstream systems or applications.”

An important feature of GPAI systems that that can drive cost savings is called transfer learning: applying knowledge from one task to another. These systems typically rely on ‘foundation models’ and are characterised by their widespread use as pre-trained models. Important questions for those deploying them are, what data were they trained on and is it safe to use them for your purpose?

A single GPAI system for language processing can be used as the foundation for many other applied models, and the speed with which this can be accomplished – and at reduced cost – is very attractive for business. As a result, GPAI systems are increasingly used in applications in medicine and healthcare, finance, life sciences, and chemistry, including in the devising of new inventions.

The EU AI Act requires all GPAI model providers to provide technical documentation, and instructions for use, and they must comply with the Copyright Directive, and publish a summary about the content used for training. Generally, free and open licence GPAI model providers only need to comply with copyright and publish the training data summary.

In addition to the Act, the European Union, USA, and UK all announced in September 2024 that they would be participating in the AI convention/treaty proposed by the Council of Europe. The treaty or AI Convention’s stated aims are to address the risks AI could pose while promoting responsible global innovation. It aims to promote protection for human rights of people impacted by AI systems. Additionally, it has set out a legal framework that will cover the entire life cycle of AI systems. Amongst other things, the framework says AI must not undermine democratic institutions or compromise the rule of law, must have transparent oversight mechanisms, must ensure accountability, and that equality must be promoted.

Some of the key treaty aims are to:

• protect personal data
• emphasise non-discrimination
• promote human dignity
• ensure safe AI development

What should guide you in use of agentic or other forms of AI?

You may find it helpful to adopt guidelines, or questions to always ask before you use AI, such as:

• Is the use lawful?
• How will you ensure the use of AI will comply with applicable laws, standards, and regulations?
• Are you comfortable with the level of transparency?
• What do your staff and customers understand about your use of AI, are you in a regulated space and can you justify what you use AI for?
• How readily can you explain it, and justify its decisions, if required to satisfy an enquiry, especially one from a regulator or court?
• What levels of cyber security are in place?
• Who is responsible in your organisation for the safe use of AI? Is there sufficient human oversight?
• Is there a risk of automated decision-making that creates a data protection problem?
• Can you trust the inputs and the consequent outputs?
• What data was/will be used to train the AI, and what data will be analysed by the AI?
• Will the AI be robust and reliable enough for its intended purpose?
• How will you assess the AI’s performance? Do you have the ability to track and report on the quality of outputs?
• Can you trace all the data used?
• Do you know the source of all the data used by the AI?
• Can you interrogate the supply chain to ensure legal compliance?

If you have questions or concerns about the use of agentic AI, please contact James Tumbridge or Robert Peake.