Beyond acceleration: the rise of Agentic AI

We already find ourselves at an inflection point with AI. According to a recent study by McKinsey, we’ve reached the turning point where ‘businesses must look beyond automation and towards AI-driven reinvention’ to stay ahead of the competition. While the era of AI-driven acceleration isn’t over, a new phase has already begun – one that goes beyond making existing workflows more efficient and moves toward replacing existing workflows and/or creating new ones.

This is the age of Agentic AI.

Truly autonomous AI agents are capable of reshaping operations entirely. Systems can act autonomously, make decisions, and adapt dynamically. These agents will go beyond conversational interfaces, responding to user input and proactively managing tasks, navigating complex IT environments, and orchestrating business processes.

However, this shift isn’t just about technology — it also comes with a few considerations. Companies will need to address regulatory challenges, build AI literacy, and focus on applied use cases with clear ROI if the evolution is to succeed.

Moving from acceleration to transformation

So far, companies have primarily used AI to accelerate existing processes, whether through chatbots improving customer interactions or AI-driven analytics optimising workflows. In the end, these implementations make businesses more efficient.

But acceleration alone is no longer enough to stay ahead in the game. The real opportunity lies in replacing outdated workflows entirely and creating new, previously impossible capabilities.

For example, AI plays a vital role in automating troubleshooting and enhancing security within the network industry. But what if AI could autonomously anticipate and predict failures, reconfigure networks proactively to avoid service level degradations in real time, and optimise performance without human intervention? As AI becomes more autonomous, its ability to not just assist but act independently will be key to unlocking new levels of productivity and innovation.

That’s what Agentic AI is about.

Navigating the AI regulatory landscape

However, as AI becomes more autonomous, the regulatory landscape governing its deployment will evolve in parallel. The introduction of the EU AI Act, alongside global regulatory frameworks, means companies must already navigate new compliance requirements related to AI transparency, bias mitigation, and ethical deployment.

That means AI governance can no longer be an afterthought.

AI-powered systems must be designed with built-in compliance mechanisms, data privacy protections, and explainability features to build trust among users and regulators alike. Zero-trust security models will also be crucial in mitigating risks, enforcing strict access controls, and ensuring that AI decisions remain auditable and secure.

The importance of AI literacy

As stated, the success of Agentic AI’s era will depend on more than just technical capabilities – it will require alignment between leadership, developers, and end-users. As AI becomes more advanced, AI literacy becomes a key differentiator, and companies must invest in upskilling their workforce to understand AI’s capabilities, limitations, and ethical considerations. A recent report by the ICT Workforce Consortium found that 92% of information and communication technology jobs are expected to undergo significant transformation due to advancements in AI. So, without proper AI education, businesses risk misalignment between AI implementers and those who use the technology.

This can lead to a lack of trust, slow adoption, and ineffective deployment, which can impact the bottom line. So, to unlock the full potential of Agentic AI, it’s essential to build AI literacy across all levels of the organisation.

As this new era of AI blooms, companies must learn from the current era of AI adoption: focus on applied use cases with tangible ROI. The days of experimenting with AI for innovation’s sake are ending – the next generation of AI deployments must prove their worth.

In networking, it could be projects such as AI-powered autonomous network optimisation. These systems do more than automate tasks; they continuously monitor network traffic, predict congestion points, and autonomously adjust configurations to ensure optimal performance. By providing proactive insights and real-time adjustments, these AI-driven solutions help companies prevent issues and outages before they occur.

This level of AI autonomy reduces human intervention and enhances overall security and operational efficiency.

Identifying and implementing high-value, high-impact Agentic AI use cases such as these will be vital.

Trust as the adoption hurdle

While we’re entering a new era, trust plays a key role in widespread AI adoption. Users must feel confident that AI decisions are accurate, fair, and explainable. Even the most advanced AI models will face challenges gaining acceptance without transparency.

This is particularly relevant as AI transitions from assisting users to making autonomous decisions. Whether AI agents manage IT infrastructure or drive customer interactions, organisations must ensure that AI decisions are auditable, unbiased, and aligned with business objectives.

Without transparency and accountability, companies may face resistance from both employees and customers.

The future of AI

Looking ahead, 2025 holds exciting potential for AI. As it reaches a new level of maturity, its success will depend on how well organisations, governments, and individuals adapt to its growing presence in everyday life. Moving beyond efficiency and automation, AI has the opportunity to become a powerful driver of intelligent decision-making, problem-solving, and innovation.

Organisations that harness Agentic AI effectively – balancing autonomy with oversight – will see the greatest benefits. However, success will require a commitment to transparency, education, and ethical deployment to build trust and ensure AI is a true enabler of progress.

Because AI is no longer just an accelerant, it is a transformative force reshaping how we work, communicate, and interact with technology.

Photo by Ryan De Hamer on Unsplash

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