AI in Manufacturing: Top Concerns for COOs in 2025
Headed into ’25 we’re navigating the rapidly evolving landscape of artificial intelligence integration and adoption in manufacturing. COOs face unprecedented challenges and opportunities with AI a big bullseye.
Here’s what’s keeping manufacturing executives up at night and how they can prepare for the AI-driven future.
Top 5 AI-Related Concerns for COOs in 2025
- AI Governance and Risk Management
COOs are prioritizing systematic, transparent approaches to ensure sustained value from AI investments while managing the risks associated with large-scale deployment. As AI becomes intrinsic to operations and market offerings, rigorous assessment and validation of AI risk management practices and controls are becoming non-negotiable [2].
- Employee Enablement and Workforce Transformation
Planning internal AI roadmaps to enable employees to transform the workforce is crucial. COOs are focusing on upskilling their teams to adapt to AI-driven changes in the manufacturing landscape [2]. By involving employees, they focus on real productivity gains.
- Operational Efficiency and Process Improvement
AI is being leveraged to build knowledge management platforms that capture organizational know-how and data points, significantly improving operational efficiency [2].
- Ethical and Responsible AI Practices
Ensuring the ethical and responsible use of AI across the organization is a key concern for COOs. This includes addressing potential biases and maintaining transparency in AI decision-making processes [2]. (See HR hiring for specific ethics concerns)
- Cost Management and ROI
COOs are grappling with price unpredictability and other cost concerns related to AI adoption. The focus is on outcomes and return on investment, ensuring that AI initiatives deliver tangible business value [2]. See AI calls – how much should it cost to ask an AI question? What is the value of it vs. traditional non AI research?
Now that we have five ways you can use AI, lets jump into three real world use cases manufacturers have already applied in the field.
Three Cutting-Edge AI Use Cases in Manufacturing
- Predictive Maintenance
AI-powered predictive maintenance is revolutionizing equipment upkeep. For instance, PepsiCo’s Frito-Lay plants implemented AI-driven predictive maintenance, resulting in minimized unplanned downtime and an increase in production capacity by 4,000 hours [1].
- Generative Design
Generative design is transforming product development. Airbus leveraged AI to cut aircraft aerodynamics prediction times from 1 hour to 30 milliseconds, enabling engineers to test 10,000 more design iterations in the same timeframe, significantly boosting innovation capacity [1].
- AI-Powered Digital Twins
Digital twins combined with AI are enhancing predictive maintenance and design customization. Rolls-Royce utilized this technology to improve aircraft maintenance efficiency, leading to a 48% increase in time before the first engine removal [1].
Many in the tech space think manufacturers are usually behind in leveraging the latest technology. I see a more cautious bank like approach whereby savvy manufacturers were waiting for other verticals to go through the early pain, watching and learning their mistakes / success with ’25 as the implementation year.
Call to Action for COOs in 2025
As manufacturers rocket into 2025, COOs must take proactive steps to harness the power of AI in manufacturing or get left behind competitors:
- Develop a Clear AI Strategy: Align AI initiatives with overall business objectives and create a roadmap for implementation.
- Invest in Workforce Development: Prioritize upskilling and reskilling programs to prepare your workforce for AI-driven manufacturing processes.
- Implement Robust AI Governance: Establish transparent frameworks for AI risk management and ethical use of AI technologies.
- Foster a Culture of Innovation: Encourage experimentation with AI technologies while maintaining a focus on tangible business outcomes.
- Collaborate with AI Experts: Partner with AI specialists and technology providers to stay at the forefront of manufacturing AI advancements.
By addressing these key concerns and embracing innovative AI use cases, COOs can position their organizations for success in the AI-driven manufacturing landscape of 2025 and beyond. The time to act is now – seize the AI opportunity and transform your manufacturing operations for the future.
Citations:
[1] https://research.aimultiple.com/manufacturing-ai/
[2] https://www.pwc.com/us/en/tech-effect/ai-analytics/ai-predictions.html
[3] https://www.techtarget.com/searcherp/feature/10-AI-use-cases-in-manufacturing
[4] https://www.youtube.com/watch?v=X3JvjK46A-4
[5] https://www.techbriefs.com/component/content/article/52344-the-state-of-ai-manufacturing-2025
[6] https://www.ptechpartners.com/2024/12/17/practical-ai-implementation-for-2025/
[7] https://www.snowflake.com/en/blog/ai-manufacturing-2025-predictions/
[8] https://sloanreview.mit.edu/article/five-trends-in-ai-and-data-science-for-2025/
