Futureproofing Heavy Asset Industries with Cognitive AI

In today’s digital-first era, heavy asset industries in Asia-Pacific (APAC), such as oil and gas, energy, and manufacturing are looking for AI solutions to reach the heights of human-like understanding. Adoption of these technologies have incentivized business leaders with benefits like automating operational processes, reducing costs, and streamlining the business decision-making process. As a result, artificial intelligence (AI) solutions have cemented their status as irreplaceable tools for these industries.
According to IDC's Worldwide Artificial Intelligence Spending Guide, APAC spending on AI systems will rise from US $20.6 billion in 2022 to US $46.6 billion in 2026. This signals a strong receptibility for businesses to innovate their existing technology stack via the adoption of next-generation AI solutions. However, to leverage their full value, companies need to fully consider existing challenges within the industry.

Due to the weight and complexity of heavy asset industries, decision-makers typically have overcome adoption hesitancy. A prominent barrier to AI adoption, across all industries, is a lack of trust in the technology, its value, concerns about its biases, or fears about it replacing the workforce. Trust is more easily built with an AI solution that can emulate human reasoning to understand and resolve problems.

Business leaders are better able to derive meaning from these solutions and make pivotal decisions more strategically. This is where Cognitive AI truly shines.

The rise of Cognitive AI

To increase trust and adoption rate, organisations need to leverage Cognitive AI which functions as a “glass box” – providing clear audit trails explaining the reasoning behind recommendations, and showing the evidence, risk, and confidence behind decisions. This allows users to see how the AI system reached a potentially flawed decision, and makes it easier to correct the problem moving forward.

Cognitive AI is unique because human expertise and experience, combined with documented knowledge, are digitized and codified into a symbolic form that is machine readable and actionable in complex industrial scale systems and processes. For example, through Cognitive AI, highly regulated industries can easily achieve their energy transition goals and reduce operational and field constraints.

In addition, many sectors today, including energy, and oil and gas, face a technical skill gap, exacerbated by the aging population. Numerous training challenges also hinder the process of keeping the existing workforce up to date with digitalization processes, including: regulatory compliance mandates; training costs to an aging workforce; and the need to improve production rates while reducing environmental impacts and safety accidents. While AI can potentially bridge these gaps, including the distrust in AI, workers do not rely enough on AI to bridge this gap.

An example would be the oil and gas workforce, which are niche in terms of skills and knowledge. It is imperative to ensure that such skill gaps are bridged in this sector, where specialized workers with adequate experience to resolve issues within refinery processes are scarce. This is exactly where Cognitive AI can resolve real issues and challenges faced by the industry.

Beyond Limits’ hybrid AI solution is the differentiating factor to explain and keep humans in the equation. By implementing explainable systems that can emulate human reasoning to understand and resolve problems, decision-makers are better able to derive meaning from these solutions and make strategic, pivotal decisions.

As we journey into 2023, AI adoption will grow at a steady pace – 37% of SEA firms plan to adopt AI in the next 5 years, according to IDC’s Asia/Pacific Enterprise Cognitive/AI Survey. Based on this, we foresee sectors like manufacturing, which comprise 22% of the Southeast Asia economy, will pursue innovations via Industry 4.0 technologies which are predicted to expand manufacturing value by 35-40% over the next decade. As businesses see increasing value in technologies like AI, the way forward is to fully maximize the value of these leading-edge technologies combined with human expertise and knowledge.