Vimal Kapur, the CEO of Honeywell, has a unique perspective on the advent of Artificial Intelligence (AI), its impact on various industries, and where he believes the real value lies. Despite popular belief that AI is primarily a tool for productivity, Kapur paints a different picture – that the AI payoff will come from safety and reliability, not just productivity.
First, it’s essential to understand Kapur’s background and his firm, Honeywell, that has entrenched itself deeply into various sectors, notably including aerospace, building technologies, and industrial safety solutions. This diverse portfolio places Honeywell at the intersection of several ongoing technological transformations, particularly AI.
Against the backdrop of the prevailing narrative that AI and related technologies are here to boost productivity and cut down on human labor, Kapur brings in a refreshing perspective. His contention lies in the fact that while productivity improvements are tangible and easier to measure, they are not the whole story. The real impact, according to Kapur, will be realized in the safety and reliability domains.
The core of Kapur’s argument is based on how AI technologies are built and function. Machine learning, a subset of AI, for instance, learns from data and makes predictions based on it. This technology can quickly identify patterns that humans would usually miss and predict possible errors before they occur. In industries like aerospace or industrial safety solutions where one mistake can result in serious repercussions, AI’s ability to predict and mitigate errors can bring a huge difference.
Anomalies get identified in real-time, systems can be maintained proactively rather than reactively, and costly – possibly fatal – accidents can be avoided. So, while productivity benefits are a welcome outcome, Kapur believes that these safety and reliability enhancements bear the real fruits of AI’s potential.
Take, for example, Honeywell’s own offerings in these areas. The company introduced the Honeywell Forge, an enterprise performance management software, the benefits of which are not only limited to honing productivity but extend to enhancements in safety measures and reliability of operations. To realize the significance of improved safety and reliability brought about by AI, one only needs to look at the expenses associated with industrial accidents and system failures, which far outweigh productivity-related losses.
In the future, Kapur sees companies investing more in AI for its ability to improve the reliability and safety of their products and services rather than just looking at it as a tool to enhance productivity. For example, in a factory setting, AI could not only be used to automate certain processes but also to enhance worker safety by identifying potential risks and hazardous situations in real time.
It is therefore not surprising that Honeywell has been investing heavily in AI capabilities. According to Kapur, the time is ripe for organizations to start viewing AI through the lens of safety and reliability and to begin integrating this perspective into their strategies going forward.
In the end, Kapur’s belief underscores an important aspect of AI’s value proposition – that the technology’s most compelling benefits may not come from productivity, a commonly highlighted area, but from safety and reliability – areas that shape the very foundation of many industries. It underscores that the future of AI goes beyond productivity enhancements; it resides also in creating safer, more reliable and sustainable industrial ecosystems.
