IT in Manufacturing


Agentic AI: are we building castles on quicksand?

May 2025 IT in Manufacturing

Artificial Intelligence is in a strange spot. With the explosion of AI tools and applications we find ourselves teetering between two inseparable yet intertwined paths – the promise of extraordinary capability and the peril of unmitigated risk.

This precarious balance gives rise to the question: “Are we building something truly enduring or are we rushing ahead on unstable foundations, building castles on quicksand?”

Agentic AI covers quite a diverse range spanning from simple chatbots to the vision of fully autonomous systems that can act, reason and take initiative. While the current hype often overshadows practical discussions there is undeniable potential for rapid advancements in this field. Agentic AI systems go well beyond mere button-based conversational interfaces offering tools that integrate into complex enterprise operations.


Stef Adonis, head of marketing at Helm.

While the appeal is undeniable, a leap of this magnitude toward fully autonomous systems in enterprise-level applications could lead to unforeseen risks. While the threat of these risks remains a reality, we should instead be focusing on human-led Agentic AI – a level where intelligent tools enhance operations while ensuring human oversight.

The key distinction lies in initiative and the ability to plan. For example, an LLM is like an incredibly well-read librarian who can instantly recall and synthesise vast amounts of information from books. When asked a question the librarian will provide a comprehensive, eloquent response, drawing from their extensive knowledge, or the wealth of information at their disposal. If prompted and asked really nicely, they might even respond as a pirate. They’re exceptional at retrieving and combining information, but they always wait for your specific query.

An agentic application, on the other hand, is like that same librarian, but instead of simply answering your question they take it a step further by showing some initiative. They might say, “Based on what you’re asking, I think you might also want to explore these related topics. I’ll go ahead and pull some additional resources, draft a preliminary research summary and even reach out to some subject matter experts who might provide deeper insights.”


Ari Ramkilowan, head of Machine Learning at Helm.

The agentic application introduces a layer of goal-oriented behaviour breaking down complex tasks into sub-tasks, making decisions, and taking actions beyond mere information retrieval. It has the capacity to perceive an environment and take purposeful actions toward a specific goal rather than following a specific query or a predetermined sequence of events. This holistic approach underlines its superiority to rigid, workflow-based tools that falter in handling edge cases.

While the journey toward fully autonomous agentic systems may still be on the horizon, enterprises are beginning to invest in the technology. The interest lies in faster iteration and broader scope where agentic systems introduce flexibility without replacing existing workflows.

However, the promise of agentic AI comes with a great deal of risk, especially for businesses – misalignment of goals, unpredictable behaviour, loss of human oversight, amplification of bias and security risks – all of which demand careful navigation.

So, we must ask ourselves not whether we can build this but should we build this.

There is a path forward that is more of a hybrid model – one that lies between structured processes and autonomous agents. This will give us the efficiency of agentic AI and the security of human involvement.

The allure of agentic AI is immense, but so are the responsibilities that come with it. Oversight, accountability and ethical alignment must serve as the foundation of our innovation. These systems should enable autonomy within controlled parameters, minimising risks while maximising potential.

As we look ahead, human-led Agentic AI may just emerge as the sweet spot - a balanced middle ground where technology supports rather than replaces human expertise.

The evolution of agentic AI is not just about technology; it’s about deliberate and thoughtful integration. While the idea of fully autonomous systems tempts us with the promise of efficiency and innovation it also demands vigilance. Building robust AI systems isn’t about surrendering control but exercising it wisely.

So we don’t need to build those castles on quicksand after all. We have the power to create a much firmer middle ground that combines the strengths of agentic AI and human expertise.

For more information contact Stef Adonis, Helm, +27 11 482 8684, [email protected], www.helm.africa




Share this article:
Share via emailShare via LinkedInPrint this page

Further reading:

Looking into the future of machine vision
Omron Electronics IT in Manufacturing
Artificial intelligence (AI) is driving a significant transformation in all areas of industrial automation, and machine vision is no exception. Omron’s AI-powered machine vision systems seamlessly integrate state-of-the-art algorithms, enabling machines to analyse and interpret visual data meticulously.

Read more...
Driving digital transformation in the truck industry
Siemens South Africa IT in Manufacturing
Tatra Trucks, a leading truck manufacturer in Czechia, has adopted the Siemens Xcelerator portfolio of industry software including Teamcenter software for product lifecycle management and the Mendix low code platform to help increase production volume and strengthen its ability to manufacture vehicles that meet specific customer requirements.

Read more...
Opinion piece: Digital twins in manufacturing – design, optimise and expand
Schneider Electric South Africa IT in Manufacturing
Digital twin technology can help create better products, fast. It can also transform the work of product development. This strong statement from McKinsey reinforces how far digital twins have come in manufacturing.

Read more...
Asset tracking is key to driving operational excellence and sustainable growth
Schneider Electric South Africa IT in Manufacturing
Asset tracking plays a critical role in the success of industrial businesses. By effectively managing and monitoring assets, companies can optimise their operations, ensuring that resources are used efficiently. This leads to improved productivity and reduced costs.

Read more...
Siemens democratises AI-driven PCB design for small and medium electronics teams
Siemens South Africa IT in Manufacturing
Siemens Digital Industries Software is making its AI-enhanced electronic systems design technology more accessible to small and mid-sized businesses with PADS Pro Essentials software and Xpedition Standard software.

Read more...
Predicting and preventing cyber-attacks with AI and generative AI
IT in Manufacturing
The speed at which cyber threats are evolving is unprecedented. As a result, companies need to implement state-of-the-art technology to protect their data and systems.

Read more...
Real-world lessons in digital transformation
IT in Manufacturing
Synthesis has helped businesses across multiple industries with their digital transformation by solving their unique integration challenges.

Read more...
Enhancing cyber security for industrial drives
Siemens South Africa IT in Manufacturing
The growing connection between production networks and office networks as part of IT/OT integration and the utilisation of IoT have many benefits for industrial companies. At the same time, they also increase the risk of cyber threats. Siemens ensures that your know-how and plants are protected at all times.

Read more...
Immersion cooling systems for data centres
IT in Manufacturing
The demand for data centres in Africa is growing. The related need for increasing rack densities brings with it escalating cooling requirements.

Read more...
Transforming pulp and paper with automation and digitalisation
ABB South Africa IT in Manufacturing
The pulp and paper industry in South Africa is undergoing a significant transformation from traditional manual processes to embracing automation technologies. Automation in pulp and paper mills aims to improve various production stages, from raw material preparation to final product creation.

Read more...