Scaling for success: Integrating AI across the asset lifecycle for maximum ROI
Posted: September 25, 2024
Hello, I'm Jeremy Wilbert. In our final roundtable discussion, we’ll explore how to scale the advanced AI tools you’ve built on a solid data foundation. Integrating AI across the entire asset lifecycle—and your global footprint—can deliver scalable, sustainable results. This comprehensive approach ensures maximum ROI and continuous improvement in industrial operations.
A comprehensive asset reliability and performance strategy that incorporates AI throughout the asset lifecycle is crucial for achieving long-term success. By leveraging AI from design and production to maintenance and decommissioning, your organization can optimize every stage of the asset lifecycle.
Integrating AI enterprise-wide makes sense. But how do you do it?
Naturally, you don’t want to reinvent the wheel. Successful AI implementation requires seamless integration into existing workflows and processes. When you use an open and neutral information platform, you can seamlessly integrate data management, modeling, AI, analytics, and visualization across your organization.
As you’ll see, the benefits quickly compound from there. Your teams will be empowered to discover new opportunities for value creation—you can even drive new revenue streams—and you can leverage your data ecosystem to accelerate digital transformation.
The power of an open, agnostic approach
An open and agnostic approach, like the one CONNECT uses, ensures that AI solutions can work with various systems, reducing the need for complex coding bridges and enabling smooth adoption. While it may be tempting to adopt a trendy new product, remember that many solutions that claim to use groundbreaking generative AI technology effectively become point solutions if they aren’t built on reliable data. If you can’t integrate and scale them effectively down the road, your early ROI has diminishing returns as times goes on.
You want a set of solutions that not only delivers fast ROI, but also sets you up for future success. With this in mind, you should look for solutions that use an open ecosystem approach and deliver fast ROI, scalability, and quick deployments across your global fleet—even if new sites won’t be built for a decade. In practice, an open, agnostic data-sharing ecosystem means you can scale your AI solutions effortlessly to deliver significant benefits across different operations and geographies, in both the short and long term.
Look for end-to-end, scalable AI solutions:
Solutions like AVEVA™ Flex and CONNECT make it especially easy to harness the power of AI to enhance operational efficiency and reliability. Because they’re flexible SaaS solutions, you can implement them across multiple sites, when and where you need them, and reap the cascading benefits of consistent and sustainable improvements.
Integrating AI throughout the asset lifecycle offers numerous benefits, including improved reliability, reduced downtime, and optimized performance. By utilizing AI at every stage, companies can ensure continuous monitoring, predictive maintenance, and efficient operations.
Key takeaways:
- Comprehensive strategy: Implement AI across the entire asset lifecycle for maximum impact.
- Seamless integration: Ensure AI solutions integrate smoothly into existing workflows and processes—and set you up for long-term gains down the road.
- Scalability: Leverage scalable AI solutions to deliver consistent and sustainable results across multiple sites.
Integrating AI across the entire asset lifecycle is essential for achieving scalable and sustainable results. By adopting a comprehensive reliability strategy and leveraging scalable AI solutions, companies can maximize their ROI and ensure continuous improvement. Thank you for joining our roundtable series on industrial AI. We hope these insights help you navigate the evolving landscape and harness the full potential of AI for your operations.
