Artificial intelligence tools and applications are changing the manufacturing industry.
Key takeaways
Strategies can provide significant insights and boost productivity when effectively designed.
Manufacturers must understand how to align AI to business goals and implement tools responsibly.
Artificial intelligence (AI) has rapidly become a key focus for business and IT stakeholders at organizations large and small across the manufacturing industry. This transformative technology has unleashed myriad advantages, ushering in unparalleled levels of efficiency, productivity and innovation for manufacturers across key business operations. For example, companies have begun to leverage AI for predictive maintenance, supply chain management, inventory management and defect detection.
According to a Manufacturing Leadership Council report on the future of manufacturing and AI, 57% of executives surveyed said they were experimenting with a range of small-scale AI pilot projects, demonstrating AI's increasing prevalence and application within the industry. Today’s AI tools and applications can provide significant value in many ways, delivering enhanced productivity and better insights that can support sustained success.
However, before you can start developing and implementing an AI strategy, you must understand what is truly possible with AI technology and how to align it to your business processes and goals. RSM’s new online guide provides critical insights into AI and how to successfully deploy an effective AI strategy, covering topics that include:
- What AI is and what it isn’t
- Common uses for AI solutions in the middle market
- The AI adoption continuum
- AI readiness
- Taking a responsible approach to generative AI
- Keeping up with evolving solutions
- Getting help on your AI journey
AI is a truly transformational solution, with undeniable potential to help your manufacturing organization work faster and smarter. But as with any new technology investment, capturing anticipated value is not a given and depends on several factors, including choosing the right tools and implementation approach. In addition, you must be aware of the risks that AI strategies can present—especially generative AI.
For manufacturers, AI’s potential to enhance predictive maintenance, optimize supply chains and improve quality control is only the start. Increased productivity, enhanced decision making and cost savings will drive broader adoption of the technology.
Katie Landy, principal, industrials senior analyst, RSM US LLP
Here are some considerations for the manufacturing sector:
How is AI used in manufacturing?
Notable use cases include improving predictive maintenance, optimizing supply chains, and enhancing quality control and defect detection.
What are the challenges of AI in manufacturing?
Some of the most pressing concerns around the use of AI include job displacement, data security and privacy, reliability, and ethical considerations.
What is the future of AI in manufacturing?
Manufacturers are expected to accelerate their use of AI in operations in the coming years, with levels of investment predicted to rise in 96% of companies, according to a 2023 report from the Manufacturing Leadership Council; however, understanding the technology’s implications will be an essential first step before adoption.
The AI market is moving quickly, and with new tools and applications emerging seemingly daily, it’s easy to start feeling overwhelmed. Read our guide to learn more about AI solutions and strategies, and how to leverage the technology’s vast potential for powerful results.
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