Are Industrials Ready for the Next Wave of Generative AI Innovation?

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 to advance rapidly.

Nick Santhanam, Gaurav Batra, Nidhi Arora
April 30, 2024

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 to advance rapidly. With proven capabilities on the market, 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, 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.

Gen AI Surged in 2023

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.

Investors’ attention brought major 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. Five start-ups—Anthropic, Cohere, Runway, Adept, and Character.AI—reached valuations of $1 billion or more, signaling robust growth and investor confidence.

Race of the Tech Giants

Big tech companies made 2023 the year of partnerships. By far the biggest was Microsoft and OpenAI’s collaboration. It began with a $1 billion investment in 2019 and was solidified by a $10 billion extension by Microsoft in 2023, bringing OpenAI’s valuation to $29 billion. The deal has grown to include exclusive licenses, a top-tier supercomputer, and the Azure Cloud Service.

Since then, industry leaders like Google, Salesforce, Oracle, SAP, Amazon, and IBM have intensified their involvement in gen AI with significant investments and partnerships. The stage is set for the companies with the deepest pockets to win by investing in advanced tools and technologies.

Entering the Next Phase of Growth

Gen AI is entering its next phase of growth, characterized by tech advancements, accelerated performance, and monetization shifts. For example, in just a few years, OpenAI’s ChatGPT chatbot evolved rapidly. 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. The progress in AI performance has outpaced expectations, and experts anticipate human-level performance sooner than previously thought.

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.

Adoption in Industrials Sector

Leaders in many industries are 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.

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 engagement with gen AI is significant are financial services; business, legal, and professional services; and health care. The industrial sector is not far behind. Leading companies like General Motors, Georgia-Pacific, BMW, Rockwell Automation, and Siemens have showcased diverse applications: enhancing customer services with AI chatbots, optimizing manufacturing processes, and improving human-machine collaboration. By partnering with tech giants and leveraging their advances, industrial firms can implement tailored gen AI solutions without significant tech investments of their own, focusing instead on collaborations within the tech ecosystem to drive innovation and efficiency.

Altogether, nearly 30 gen AI use cases for the industrial sector across functions can unlock the technology’s transformative potential and efficiency. The largest share of 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.

Rising to the Challenge

Gen AI’s potential is great, but as with any technology, being an early adopter poses risks. Companies must prepare to meet challenges in data security, accuracy, biases, errors, and limitations. Success can enable a seamless transition to the future of business.

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.

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, companies that ride on the shoulders of the tech giants can capture this opportunity without big investments or major overhauls of internal systems and tools.

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