How are industrial manufacturers exploring the use of generative AI within their operations? What use cases are they prioritizing? Where do they see the greatest barriers to adoption? These were among the questions KPMG explored through an industry survey in March 2023 and June 2023. The findings affirm that the industrial manufacturing sector is advancing at pace—suggesting that organizations should act aggressively to gain first-mover advantage.

The upside of GenAI

In March 2023, 67% of industrial manufacturing executives selected generative AI as the top emerging technology. By June, more than three-quarters (78%) agreed with that sentiment—and they’re doing more than talking about generative AI. In March, 10% were planning to develop homegrown solutions. By June, 65% reported developing such solutions, with 43% investing in off-the-shelf and 51% in custom off-the-shelf solutions.

When asked about how their organizations are likely to apply generative AI, industrial manufacturing leaders pointed to optimizing production schedules and identifying inefficiencies in the production process (76%), managing inventory (69%) and forecasting raw material prices (51%).

Balancing the risks

In the most recent survey, 80% of industrial manufacturing executives said they expect generative AI to have a positive impact on the workforce. More specifically, 95% agreed that generative AI will enhance employees’ creativity and thoughtfulness, with 78% believing it will reduce burnout and improve productivity. 

But they also acknowledged potential downsides. In the most recent wave, executives cited cybersecurity, lies and misinformation, and bias/inaccuracy as the top three risk management concerns. Yet nearly three-quarters (73%) indicated that they’re highly confident in their organization’s ability to address and mitigate risks related to generative AI. Forty-three percent said they have a mature responsible AI governance program in place.

What to do next

As your industrial manufacturing organization moves forward with generative AI opportunities, consider these six actions to jumpstart your agenda:

1. Address data availability, quality and integration. Start by assessing and addressing shortcomings in your data. To take full advantage of generative AI, you need a reliable data infrastructure that is customized for the business and can be trusted by all stakeholders. 
2. Identify and pursue early use cases. As you bolster your data foundation, keep moving ahead with identifying and experimenting with discrete generative AI use cases. Aim for tangible quick wins that naturally build momentum. Consider targeting the highest-value use cases—those that will have a direct impact on revenue, costs, risk, or other important outcomes.  
3. Prepare the workforce. In tandem with efforts to assure data quality and identify use cases, pay attention to the impact generative AI will have on your workforce. Build a plan for upskilling workers and forming a data culture. In the KPMG survey, industrial manufacturing leaders indicated that they expect more positive outcomes for some functions than for others. Be mindful of these differences when crafting change management and communication plans.
4. Address talent gaps. The survey found that compared to other sectors, industrial manufacturing leaders foresee the greater need to hire or train people for generative AI. Among the most-cited skills gaps: algorithm development and optimization, as well as data acquisition and preprocessing. These are areas where it may make sense to seek outside help.
5. Develop a generative AI strategy. Finally, create a broad strategy that weighs costs against revenue opportunities and risks and creates a framework for responsible use, including a generative AI working group that leads to executive-level buy-in.

How is your organization evaluating and pursuing generative AI opportunities—whether to transform existing operations or power your transition to smart manufacturing? How do your experiences and perspectives compare to those shared in the surveys? Review Getting a head start with generative AI in industrial manufacturing to dive deeper into the findings and analysis.