Artificial intelligence (AI) has reached a pivotal turning point. The next wave is not defined merely by automation but by autonomy.
Of course, I’m talking about the era of agentic AI: intelligent systems that can independently plan, adapt and execute complex tasks without constant human direction or involvement.
Head of AI & Data Science at SAS for Northern Europe.
Unlike the AI models you might already be familiar with, which follow predefined rules or narrow patterns, agentic AI can make contextual decisions in real time, re-prioritizing its goals as situations evolve.
Our new global study found that half (52%) of enterprise organizations globally report that they’ve already begun using agentic AI. Trustworthy AI investment specifically for agentic AI is increasing across industries and globally, 25% of organizations report that they plan to “significantly increase” spending on trustworthy AI investment for agentic AI.
The allure is clear. Faster, more confident decision-making, reduced costs and unprecedented organizational agility. And it’s not just a future aspiration – it’s already delivering results.
In industries such as financial services, retail and healthcare, autonomous systems are transforming workflows and optimizing operations. It has been predicted that, by 2029, agentic AI will autonomously resolve 80% of common customer service issues without human intervention.
Meanwhile, 42% of healthcare providers expect it to improve quality of patient care, and over a quarter of financial services firms expect annual savings exceeding £2.9 million from using agentic AI. These are efficiencies that were unimaginable with earlier AI generations.
From automation to autonomy
For decades, the story of AI has been one of automation. We trained models to classify data, recognize patterns and perform repetitive tasks faster than a human could.
That’s been transformative, but also has its limitations, particularly as these models still rely heavily on human guidance. It’s like having a brilliant assistant who needs constant instruction every step of the way. But agentic AI changes that dynamic.
Instead of performing single, isolated functions, these systems can assess a situation, map out possible actions, weigh trade-offs and choose the best course. This is all in real time and often across multiple interconnected domains.
Think of it as moving from “AI as a tool” to “AI as a collaborator.” A collaborator who doesn’t just carry out your instructions, but can also decide what needs doing next and why.
Why the stakes are so high
The shift to agentic AI is not merely technological; it’s strategic. Those that deploy it effectively will be able to move faster, adapt sooner and innovate more boldly than their competitors.
But there’s a critical caveat: the same autonomy that makes agentic AI powerful also makes it risky. Systems capable of making high-impact decisions without human approval must be designed, monitored and governed responsibly.
Successful AI projects place humans firmly back into the loop where necessary. This is not just a governance checkbox; it’s the foundation for sustainable, trustworthy AI.
Models learn from historical data, but they don’t understand the world the way humans do. They detect patterns, but they don’t grasp nuance, context or evolving social norms.
Human oversight bridges these gaps. AI does not create value in isolation – it creates value through the people who guide it, interpret it, and make decisions with it.
Without transparency in decision-making, oversight of autonomous actions and accountability for outcomes, the technology risks eroding trust. And without trust, adoption will stall.
This means embedding ethical guardrails and explainability into every layer of design and operation, including transparent decision paths, so stakeholders can understand why an AI system acted the way it did – making sure that autonomy can be overwritten where needed.
Looking ahead
This isn’t about slowing down the pace of innovation – on the contrary. Responsible governance will accelerate adoption, by giving organizations the confidence they need to use agentic AI at scale.
The coming years will see agentic AI reshape industries in ways we can only imagine at this stage. Autonomous systems will be deployed not just as operational tools, but as strategic partners capable of discovering new opportunities, managing complexity and solving problems that have previously been far beyond reach.
For leaders, the message is clear: waiting on the sidelines is not an option. The organisations that succeed in the agentic AI era will be those that combine ambition with responsibility. You must embrace autonomy, while keeping transparency and good governance at the core of everything you do.
If we strike that balance, agentic AI will not simply change processes; it will redefine possibilities. Handled responsibly, it won’t replace human ingenuity; it will magnify it, freeing us to focus on the challenges only we can solve.
The era of agentic AI is here. The only question is: who will lead it?
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