Agentic AI Explained: What Business Leaders Need to Know Next 

AI adoption has accelerated quickly over the past two years, but most organisations are still only scratching the surface. 

According to the British Chambers of Commerce, 54% of UK businesses are now actively using AI, up from just 25% in 2024. Yet the vast majority are using it in limited, tactical ways, primarily for content, analysis, or individual productivity rather than embedded business operations. That’s starting to change. 

What is agentic AI?  

Agentic AI refers to AI systems that can plan, decide and take action across multiple steps and tools to achieve a defined goal, with human oversight and clear boundaries. 

In other words, instead of only responding to prompts, agentic AI focuses on outcomes. It can coordinate tasks, move work between systems, and escalate when it’s unsure, acting more like a digital “doer” than a digital “assistant”. 

For leadership teams, this isn’t just another AI feature. It’s a shift in how work is designed, governed and scaled. 

From assistants to agents: what agentic AI changes for businesses 

Most AI tools in use today are reactive. A person asks, the system responds, and the human decides what happens next. Agentic AI works differently. 

These systems are designed to: 

• Understand a goal 

• Break it into steps 

• Decide which tools or data to use 

• Execute actions across workflows 

• Escalate or pause when confidence drops 

This is why agentic AI is often described as goal‑driven, rather than prompt‑driven. 

Gartner predicts that 40% of enterprise applications will include task‑specific AI agents by the end of 2026, up from less than 5% in 2025, signalling a rapid move away from standalone AI tools towards embedded digital workers.  

In practice, that means less time coordinating work between systems, and more time focusing on decisions that genuinely require human judgement. 

The gap between AI adoption and AI impact 

There’s a growing gap between AI adoption and AI outcomes.  

McKinsey’s global research shows that while nearly 90% of organisations are using AI in at least one function, fewer than 40% are seeing measurable impact at an enterprise level. One of the main reasons is that AI has often been added on top of existing processes, rather than reshaping how work flows end‑to‑end. 

Agentic AI begins to address that gap. 

Instead of improving a single task, agentic AI focuses on orchestration, coordinating people, data and systems across multi‑step workflows. That’s why early use cases are emerging in areas like IT operations, service management, reporting and compliance, where speed and consistency matter just as much as accuracy. 

Agentic AI isn’t about replacing people 

There’s understandable caution around autonomous systems. And in reality, most businesses aren’t looking for AI that “runs unchecked”. 

The real value of agentic AI lies in removing the invisible admin that sits between teams and systems, the chasing, copying, checking and updating that slows everything down. 

That distinction matters. Agentic AI depends on good governance and readiness, not blind trust. 

Agentic AI use cases: where it delivers value first in business 

Despite the headlines, agentic AI isn’t something most businesses should deploy everywhere. The strongest early candidates tend to be: 

• Well‑defined processes with clear rules 

• Tasks spread across multiple systems 

• Low tolerance for delays or human error 

Examples include: 

• IT incident triage and monitoring 

• Internal service workflows 

• Cross‑system reporting and audits 

• Sales or customer service coordination 

This measured approach aligns with what we’re seeing in the UK market. BCC research shows that while AI use is rising, only one in ten SMEs are investing in more advanced, bespoke AI systems – and those organisations are far more focused on process maturity and oversight.

If you’re planning early AI use cases, our AI‑Ready IT Strategy Pack helps you map priorities and foundations. 

Agentic AI risks leaders can’t afford to ignore 

With increased autonomy comes increased responsibility. Without clear boundaries, agentic systems can: 

• Act on incomplete or poor‑quality data 

• Make decisions that don’t align with policy 

• Create gaps in auditability and accountability 

• Increase security and compliance exposure 

Gartner estimates that by 2028, 15% of day‑to‑day work decisions could be made autonomously, but only in organisations with strong governance, identity control and monitoring in place.  

That’s why agentic AI is as much a leadership and readiness challenge as a technical one. 

AI readiness for agentic AI: why foundations matter more than “experimentation” 

One of the biggest misconceptions is that agentic AI is still years away. In reality, its success depends on decisions businesses are making right now about: 

• Data quality and ownership 

• Legacy infrastructure and integration 

• Security, access and identity management 

• Operational accountability 

Microsoft’s 2025 Work Trend Index found that 81% of leaders expect AI agents to be part of their core strategy within 18 months, but only a fraction feel confident in their readiness to support that shift at scale.  

Agentic AI doesn’t hide weak foundations, it exposes them. 

What leaders should do now: a for responsible AI adoption 

This isn’t about rushing to deploy autonomous systems. The most successful organisations will be deliberate. 

A practical approach looks like: 

1. Build leadership understanding of agentic AI 
   Enough to ask the right questions about governance, risk and outcomes. 

2. Identify low‑risk, high‑value pilot workflows 
   Start with process areas that are well defined, measurable, and auditable. 

3. Strengthen data, security and integration foundations 
   If your systems don’t connect cleanly today, agentic AI will amplify the gaps. 

4. Define governance before capability 
   Decide upfront what the agent can do, when it must escalate, and how actions are logged. 

The businesses that succeed won’t be the loudest early adopters. They’ll be the ones that prepare properly, then scale responsibly. 

From experimentation to readiness 

Agentic AI isn’t hype, and it isn’t science fiction. It’s a natural evolution of how AI is moving from helping individuals to supporting entire workflows, with humans firmly in control, but no longer buried in admin. 

For leaders, the real opportunity isn’t automation for its own sake. It’s building an organisation that’s ready to use AI confidently, securely and on its own terms. And that starts with understanding the shift, before it becomes unavoidable. 

If you’re working out what needs to be true before you scale AI, our AI‑Ready IT Strategy Pack helps you prioritise the foundations and map next steps.