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Heiko Claussen, the Co-Chief Technology Officer at Aspen Technology, says industrial AI-based automation is deployed to tackle workforce challenges and boost efficiency
How did the industry and your company fare in 2024, and what were the key highlights?
Industrial AI adoption has accelerated in the past year, in line with its growth trajectory from Similarweb, which predicts that the global AI market is expected to be worth $407 billion by 2027. Organisations are seeing value in using it to enhance operational efficiency and sustainability.
In the energy sector, we’ve seen a significant increase in AI applications for forecasting renewable energy production, optimising grid operations, and improving overall efficiencies. Recognising AI’s potential, executives have shifted priorities over the past year. Companies are focusing on enhancing agility and operational resilience through Industrial AI, emphasising real-time guidance applications for decision-making amid market volatility. Moreover, Industrial AI-based Automation is deployed to tackle workforce challenges and boost efficiency.
What opportunities do you foresee for 2025, and how do you plan to leverage them?
Streamlining data management will be a key priority as AI adoption accelerates. The volume and complexity of data is growing exponentially. As companies prioritise AI applications and digital transformation initiatives, they will turn to OT data fabrics to streamline thousands of IT and OT connections and make data more accessible and actionable. OT data fabrics ingest diverse data that connects people, machinery, plants, logistics, and IT systems, enabling data scalability to unlock the potential of new opportunities like AI for years to come.
Additionally, Industrial AI will address workforce shortages by providing guidance and automation, bridging skill gaps as experienced workers retire. In the energy sector, AI will play a crucial role in managing grid complexity, allowing intelligent switching to maximise renewable energy use based on real-time needs.
What major challenges did you encounter in 2024, and how did you address them?
The growing cyber threat landscape was a significant challenge in 2024. Industrial companies typically have thousands of point-to-point connections, which are often chaotic and complex, making them difficult to maintain and secure. These connection points have become increasingly vulnerable to exploitation by bad actors.
To address this, companies engaged with technology providers that prioritize secure development principles and compliance with cybersecurity standards. Additionally, OT data fabrics were adopted to facilitate fewer, more secure connection points, enhancing industrial data management capabilities while mitigating security risks.
Another challenge involved workforce shortages and skill gaps, particularly as experienced workers retire. Industrial AI provided a solution by automating processes and offering operational guidance to maintain efficiency.
Which emerging technologies do you believe will be in high demand in 2025, and why?
In line with the ongoing global AI growth trajectory, I anticipate a significant acceleration in Industrial AI adoption in 2025 and beyond. Companies recognise AI as essential for operational efficiency, for example with predictive maintenance reducing downtime by forecasting equipment failures.
AI also guides the workforce, accelerating informed decision-making. The focus is shifting toward strategic applications that deliver tangible value and therefore profitability with minimal energy, driving broader adoption in the coming years. Industrial AI will gain attention for its energy efficiency benefits. By now, it’s common knowledge that AI has significant energy demands that are putting a strain on the grid and data centres. But, not all AI’s power demands are the same.
For example, Industrial AI, which combines domain expertise and engineering fundamentals with AI, is more narrowly focused on smaller models, which means it is more data efficient and requires far less power. In addition to its energy efficiency benefits, industrial companies are turning to Industrial AI for agility, guidance and automation, such as helping companies avoid unplanned plant shutdowns or enhancing operational decision support for users.
What will be your primary focus areas and strategic priorities for 2025?
Industrial data management will become a competitive advantage. With the need for companies to be increasingly resilient and efficient amid economic uncertainties, data has emerged as a key tool to gain a competitive edge. When companies can harness their data, they can find optimisation opportunities they may not otherwise recognize and support a more agile and resilient organisation.
The importance of this became clear during the COVID-19 supply chain challenges and the supply chain challenges we often still see today following extreme weather events and geopolitical uncertainty. In 2025, companies will prioritize data management tools that mitigate data complexity and siloes, instead making it easier to extract value from their data amid a changing global economic landscape.
Cybersecurity will also be a top priority in data connectivity architecture. Connection points across IT and OT data are critical for industrial companies to be able to take advantage of new opportunities like AI and make data-driven decisions based on a holistic view of the business.
However, point-to-point connections, of which industrial companies typically have thousands, are often chaotic and complex, making them difficult to maintain and secure. In 2025, engaging with technology providers that prioritize secure development principles and compliance with cybersecurity standards will be a top priority for industrial companies.
Are there plans to explore new markets or introduce new products/applications to your portfolio in 2025?
Utilities are expected to maintain a nearly perfect reliability record for the critical grid infrastructure they operate, often making them slower to adopt disruptive technologies like AI. In 2025, utilities will prioritize the adoption of AI algorithms that are specifically created to help the industry manage grid complexity with safety and reliability top of mind.
AI can help utilities recognize and learn from patterns within extensive grid data, such as forecasting for renewables to help make better predictions based on weather patterns and historic behaviour. With the right guidelines in place, AI will be a critical tool in helping utilities create efficiencies as they navigate the energy transition and manage an increasingly complicated grid.
Executives will embrace the disruptive power of AI to establish a competitive edge. While many industries have been conservative about data-driven approaches and AI in the past, 2025 will be the year companies prioritize fit-for-purpose AI investments that mitigate AI adoption concerns and drive tangible value. For instance, Industrial AI combines AI with domain expertise and engineering fundamentals for guardrails, robustness and trusted results.
It is uniquely equipped to accommodate the complex and essential requirements asset-intensive industries like oil and gas have for safety, reliability and environmental stewardship. In 2025, executives will gravitate toward AI they can implement confidently for competitive advantage with efficiency, optimization, and decision-making support.
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