If you’ve ever felt overwhelmed while booking complex travel plans, coordinating supply chains, or managing multi-layered systems, the emergence of AI agents — also known as agentic AI — offers a compelling glimpse into the future. These advanced AI systems act on behalf of users, taking on multiple tasks autonomously to achieve broader goals, allowing individuals and organisations to focus on higher-value work.
Unlike traditional AI, which typically responds to single prompts, agentic AI can operate across numerous platforms and services. It doesn’t just follow pre-programmed instructions — it learns and adapts, executing tasks with an increasingly human-like sense of initiative and efficiency. Whether it’s scheduling meetings, overseeing logistics, or planning detailed itineraries, AI agents are poised to transform the way we interact with technology.
The concept mirrors age-old productivity methods like the Pomodoro Technique, where tasks are broken into manageable chunks. AI agents are doing the same — only at an industrial scale, coordinating across systems and domains with growing intelligence. According to the Harvard Business Review, agentic AI is set to revolutionise human-machine collaboration, and Deloitte estimates that by 2027, half of all businesses using generative AI will incorporate agentic systems.
“Agentic AI is very exciting and could be the biggest productivity boost yet that everyone has been expecting from AI. It’s more than automation—it will help us manage complex and dynamic objectives at high speed, increasing the impact that machine systems make for us. But with that comes new security risks,” says Gerhard Swart, Chief Technology Officer at cybersecurity firm Performanta.
As these agents become more capable, so do the risks. Trust is a cornerstone of effective delegation — whether between an executive and their assistant or a doctor and their patient. In much the same way, AI agents require deep access to systems, information and processes, which could make them highly attractive targets for cybercriminals and internal threats.
“The same applies to AI agents, which immediately flags the biggest security concern,” says Swart. “For agentic AI to work, it needs access to secure systems—often several different systems. That kind of access is very dangerous if it falls under the influence of malicious employees or cybercriminals.”
To mitigate such risks, security measures for AI agents should mirror those for human users with elevated privileges. These include robust identity management, restricted access, encryption, and ongoing behavioural assessments. Shadow AI — unauthorised or unmanaged agents — also poses a threat, underscoring the need for clear internal policies.
According to Swart, “An AI agent can have access to important business data, scheduling and email applications, SaaS services, and such things. There is much we can determine from that vantage, such as ensuring we understand and limit the agent’s access to systems.”
One of the most crucial defences is continuous monitoring. Top managed security service providers (MSSPs) deploy real-time monitoring and automated remediation tools, many of which use AI themselves, to detect and respond to threats swiftly.
“Partnering with an MSSP is particularly prudent for AI agents. MSSPs invest in active monitoring and remediation tools, including AI agents, that can act as fast as the attackers,” says Swart. “Active monitoring and remediation are crucial and need to be very fast. They should be as fast as machines can act. MSSPs invest in this speed and accuracy. If you want to get the most from AI agents while keeping risks and costs down, especially as you start to deploy agents, partnering with a top MSSP is the best option,” he concludes.
As organisations begin to embrace this emerging wave of intelligent automation, security must evolve in tandem. The potential of agentic AI is immense — but it must be paired with a vigilant, risk-aware approach to truly deliver on its promise.