March 22, 2023 Industries Embracing Generative AI

How different sectors will use this new technology to improve predictive maintenance, discover efficiencies and optimize supply chains.

Attributed to: Matt Edic, Chief eXperience Officer at IntelePeer

As labor shortages and supply chain issues plague different industries, business leaders continue to search for innovative and automated solutions to alleviate workplace challenges. And although traditional AI is a staple of various sectors, especially manufacturing, companies are starting to recognize the incredible potential of generative AI, made particularly popular by wildly successful models like ChatGPT.

Unlike traditional AI models, which typically monitor data and detect patterns, generative AI synthesizes statistical data to generate an entirely “new” or curated result. And while people can use ChatGPT to create funny poems or stories, savvy enterprises keep identifying sophisticated use cases for this burgeoning technology. From automotive and manufacturing to pharmaceuticals and logistics, different industries are embracing generative AI for its ability to enhance predictive maintenance, discover new efficiencies for design and processes and optimize supply chains.  

Enhance Predictive Maintenance

In a manufacturing setting, equipment failure can be expensive – in fact, it is three to ten times higher than scheduled maintenance costs. Moreover, the unplanned downtime from equipment failure costs manufacturers $50 billion yearly. Alternatively, manufacturers can augment their predictive maintenance solutions with generative AI to ensure equipment longevity and minimize downtime. These models can analyze massive amounts of data generated from IoT sensors installed in critical machinery and anticipate when assets will fail, allowing manufacturers to intervene and prevent disasters to production and performance.

What’s exciting about the potential of generative AI in predictive maintenance is that generative AI could provide a more comprehensive report to managers detailing how often certain parts might break or the availability of replacement parts in the factory. Rather than only notifying staff that the equipment needs servicing, it would formulate a plan underlining the issue within a broader context.

Discover New Efficiencies for Design and Processes

By now, most are familiar with AI image and art generators that can take a prompt and create multiple pieces of impressive artwork in seconds. With the same level of skills, it would take a human artist several hours or days to make something similar. When applied to processes and designs in the working world, these same capabilities can accelerate many arduous procedures and discover new efficiencies to old problems.

Many industries, such as manufacturing, automotive and aerospace, can use generative AI to design parts curated to parameters, goals or requirements. Most notably, automakers wanting to make their cars more fuel efficient might use generative AI to help design lighter vehicles. Another industry expected to make considerable use of generative AI is pharmaceuticals. In fact, Gartner predicts that by 2025, 30% of new drugs and materials will be systematically discovered via generative AI techniques. With these powerful solutions, pharma brands can significantly reduce costs and shave years off drug discovery timelines. Companies can even “invent” new designs unthought of by humans.

Additionally, in the engineering sector, experts can leverage generative AI to create design alternatives, reduce material waste – i.e., maximizing every square inch of sheet metal – and optimize product performance. Generative AI can also help engineering businesses find bottlenecks, forecast production times and rework or redesign existing processes or models rapidly.   

Optimize Supply Chain Management

In industries with complex and delicate supply chains, such as material handling, manufacturing, transportation and logistics, generative AI can be a tremendous boon, improving delivery times, reducing process latency and minimizing logistics expenses. Recall that AI can process an enormous amount of real-time data and generate detailed results for supply chain operators, enabling them to make much more proactive and informed decisions.

Generative AI solutions can identify inefficiencies, chart faster routes and predict imminent trends by analyzing data from IoT sensors and other sources, like satellite maps, real-time traffic data and weather forecasts. Moreover, generative AI can help supply chain operators reduce fuel consumption and boost delivery times. Ultimately, generative AI will enhance supply chains, empowering companies to provide excellent customer service.

Will Generative Replace People and Other Types of AI

Regarding the elephant in the room, generative AI will not replace humans – at least not in the way many believe. Like any tool, generative AI will replace various tasks, especially time-consuming and repetitive ones, but it will not outright eliminate the need for human intuition and empathy. Nevertheless, enterprises embracing generative AI must undergo restructuring to maximize their technology and people’s effectiveness.

Similarly, businesses must dispel the notion that generative AI is the end-all intelligence solution. While generative AI is superior in various use cases to other forms of AI, leaders need to look at deployment on a case-by-case basis. Indeed, generative AI is one of many flavors of AI that companies can use in conjunction to overcome ongoing and future challenges.

Matt serves as the Chief Experience Officer. In this role, he and his team ensure the highest level of support in customer interactions.

Previously, Matt served as Senior Vice President, Customer Experience and Vice President, Enterprise Sales and Business Development for IntelePeer. Matt brings to IntelePeer more than 20 years of leadership experience and a strong passion for serving customers, continuous improvement, and teamwork. Prior to IntelePeer, Matt worked for NexTone, JP Morgan Chase & Co., and Qwest Communications. He holds a Bachelor of Science in Computer Science from the United States Naval Academy in Annapolis, Maryland.

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