Generative AI (gen AI) had a groundbreaking year in 2023. Tech companies developed new tools, user adoption broadened dramatically, investor interest took funding to new levels, and technology continued its rapid advancement. With proven capabilities on the market, plenty of use cases have emerged across functions and sectors—including use cases that can be transformative for the Industrial sector.

Now it is up to Industrial companies to assess whether they are prepared to ride this wave of gen AI adoption and use. Many are still investigating and experimenting with this technology, but now is the time to begin capturing its benefits. While practical applications long seemed distant, they are now at hand, and the costs to get started are falling as the global technology giants make great strides in gen AI learning models and platforms.

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Generative AI Surged in 2023

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Gen AI experienced a meteoric rise in 2023, with growth in adoption, investments, and executive enthusiasm. Compared with other major tech products, ChatGPT, DALL-E, and Midjourney reached one million users much faster. Since then, they have sustained daily use by millions, showcasing their widespread appeal.

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Investors’ attention led to significant funding increases. The top five gen AI deals in 2023 gave companies a staggering $13 billion. Far in front was the landmark deal between OpenAI and Microsoft. In this environment, five start-ups—Anthropic, Cohere, Runway, Adept, and Character.AI—reached valuations of $1 billion or more, signaling robust growth as well as investor confidence.

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While some major deals have occurred, the gen AI space still harbors ample room for growth, with many companies in the early stages (Exhibit 1). Based on data from CB Insights, 78% of 360 gen AI start-ups remain in early-stage funding—seed, angel, pre-seed, and series A—or lack any equity backing.

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Exhibit 1

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The commitment of investors was not lost on business leaders. Executives in key industry sectors, including technology, consumer goods, and Industrials, have publicly expressed their interest in the transformative nature of gen AI. For example, Nvidia CEO Jensen Huang told CNBC, “Every application that exists will be better because of generative AI.”

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Race of the Tech Giants

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Big tech companies made 2023 the year of partnerships. . Far and away the biggest was Microsoft and OpenAI’s collaboration to which Microsoft committed $29 billion. The Microsoft-OpenAI partnership began with a $1 billion investment in 2019 and was solidified by a $10 billion extension by Microsoft in 2023. The deal has grown to encompass exclusive licenses, a top-tier supercomputer, and the Azure Cloud Service.

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Since then, most industry leaders like Google, Salesforce, Oracle, SAP, Amazon, and IBM have intensified their involvement in Generative AI with significant investments and partnerships (Exhibit 2), setting the stage for an arms race where the companies with the deepest pockets to invest in advanced tools and technologies will likely emerge as winners.

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Exhibit 2

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Entering the Next Phase of Growth

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Gen AI is entering its next phase of growth, characterized by technology advancements, accelerated performance, and monetization shifts. A key example of the advancing technology is OpenAI’s ChatGPT chatbot. In just a few years, ChatGPT has rapidly evolved. The GPT-4 large language model it employs now boasts more than 100 trillion parameters, paralleling the complexity of the human brain’s neural connections.

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The progress in AI performance has outpaced expectations. Experts anticipate human-level performance sooner than previously thought (Exhibit 3). Accounting for factors such as regulation, investment levels, and management decision making, MGI estimated ranges of adoption times of gen applications that could achieve median or top-quartile levels of human performance.  For some capabilities, such as natural-language generation, median performance was already possible in 2017. For others, such as creativity and logical reasoning, median performance was achieved by the time of the 2023 estimates.

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Exhibit 3

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Given the practical value of the technology’s new capabilities, gen AI has moved from business models based on free accessibility to monetization strategies. Github, Copilot, Synthesia, and other platforms have shifted from their initial offers of free access to subscription-based models.

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Adoption in Industrials Sector

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Leaders in many industries are now identifying relevant use cases. The degree of gen AI adoption varies according to function and industry sector—including a plethora of opportunities for Industrials. Across functions, IT is making the most use of gen AI and is expected to be the leader in fully integrating gen AI into critical functions. In addition, notable shares of employees in supply chain, manufacturing, marketing, advertising, sales, and product development expect to embrace gen AI by 2025.

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By industry, the technology, media, and telecom sector has the greatest usage of gen AI and the highest expectations for full integration in the future. Other sectors where there is significant engagement with gen AI are financial services; business, legal, and professional services; and healthcare. The Industrial sector is not far behind. Leading companies like General Motors, Georgia-Pacific, BMW, Rockwell Automation, and Siemens have showcased diverse applications of Generative AI, from enhancing customer services with AI chatbots to optimizing manufacturing processes and improving human-machine collaboration. By partnering with tech giants and leveraging their advancements, Industrial firms can implement tailored Generative AI solutions without significant technology investments of their own, focusing instead on strategic collaborations within the tech ecosystem to drive innovation and efficiency.

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Altogether, nearly 30 gen AI use cases for the Industrial sector across functions can unlock the technology’s transformative potential and efficiency (Table 1). The largest share of these use cases is in sales and marketing, followed by support functions (IT, finance, and human resources). In addition, manufacturing and supply chain each have five use cases for Industrials. Together, these use cases are helping Industrial companies move faster, serve customers better, improve quality, increase revenue, and lower costs.

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Table 1

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Rising to the Challenge

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The potential of gen AI is great, but as with any technology, being an early adopter poses some risks. Swift growth and adoption can bring immense rewards, but companies must prepare to meet challenges in data security, accuracy, biases, errors, and limitations. Success can enable companies to make a seamless transition to the future of business.

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Some companies have already experienced the impact of these risks, and many have developed responses. Their experience suggests paths for risk management at other Industrial companies. For example, many companies are implementing guidelines for writing prompts, continuously monitoring and improving gen AI performance, and seeking legal advice on risk mitigation.

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The challenges are real but surmountable. After a groundbreaking year in 2023, gen AI is ready for businesses to begin reaping its benefits. Industrial companies that are prepared to ride this wave of gen AI adoption and use can enjoy a first-mover advantage. Furthermore, as mentioned earlier, capturing this opportunity does not require big investments or major overhauling of internal systems and tools, as companies can ride on the shoulders of the tech giants.

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