Once the domain of companies able to supply the requisite resources and infrastructure to support AI, rapid commoditization has made the technology accessible to enterprises of all sizes. AI is fast becoming just one more tool to solve business problems.
AI in 2024 and beyond
Adoption of AI is increasing year over year, with Forbes projecting that market size for AI will reach a staggering $407 billion by 2027, up significantly from its estimated $86.9 billion revenue in 2022.
Enterprises anticipate big returns on their investment, with 64% of companies expecting productivity to increase with AI, reflecting a growing confidence in AI’s potential to transform the business.
A recent Gartner survey reflects the perceived value of AI within the enterprise, with 75% of corporate strategists seeing AI and analytics as critical to their success over the next two years.
The promise of generative AI
Generative AI produces text, images, and other media using generative models. These models learn patterns and structure from input training data, generating new data with similar characteristics. While traditional AI is primarily used to analyze data and make predictions, generative AI creates new data based on its training data.
This distinction was demonstrated during a recent use case presentation. In the example, a maintenance technician working on a machine needed product information and guidance on how to perform the maintenance work.
A predictable result would be for the AI engine to draw from product manuals and other documentation. However, generative AI provided a more nuanced response by also tapping into data from previous maintenance work that had occurred on the machine.
With generative AI, the technician received factual and anecdotal information in seconds so the work could proceed immediately.
The value of AI to the enterprise
We see the same rapid adoption underway with IFS customers, with many leveraging AI that is already integrated within existing IFS solutions. Other customers are opting to implement IFS.ai, our AI technology for industrial settings. Here are a few examples.
AI embedded in IFS solutions
IFS solutions include AI-powered analytics that deliver meaningful operational insights, improving efficiencies—and the bottom line—across the operation.
Customer proof point: Preventive and predictive asset maintenance
Predictive asset maintenance is a perfect example of AI integrated within IFS Enterprise Asset Management. These AI capabilities are powered by data generated from enterprise assets, IoT devices, and other sources, allowing our customers to easily manage preventive and predictive maintenance models.
 | Holmen produces and sells timber as well as wood, paper, and packaging products. The company relies on IFS EAM to support its preventive maintenance model, providing data collection, insight, control, and stability—and securing its production capabilities. |
“We will use IFS Business Connector alongside sub systems and solutions including AI and ML to support connected machine and improve predictive maintenance. For example, we see AI could collect data externally, and then flag the need for maintenance on a specific object in a few months’ time, automatically generating the work order. IFS will be the center of information for our digitalized mills,” stated David Lyrén, Technical Manager at Holmen.
Read the full customer story or download the executive brief for more information.
AI capabilities with IFS.ai
IFS.ai is purpose-built for industrial use, supercharging organizations and transforming the business. Our leading AI technology allows our customers to deliver when it really matters.
Customer proof point: Agile growth and expansion
 | CDF Corporation, a global leader in semi-rigid and flexible liquid packaging for a variety of markets, has been an IFS customer since 2007. The company rolled out IFS.ai into its Cheer Pack North America unit to support its industrial automation solution that incorporates robotics. |
IFS.ai helps robotize materials movement, freeing human workers to focus on advanced tasks and helping to reduce Cheer Pack’s labor shortage. The technology also allows the company to offer its customers aggressive deliver times with confidence, based on the available-to-promise functionality within IFS.ai.
“One of our greatest challenges is lot traceability. Our original production line system didn’t allow us to trace material to the level our customers wanted. With the agility of IFS.ai, we were able to switch to a shop-order system that allows us far greater traceability. We can meet all our customers’ needs now,” stated Alex Ivkovic, IT Manager at CDF Corporation and Cheer Pack North America.
Read the full customer story for more information.
Next steps with IFS
These are just two examples of IFS customers benefiting from AI via IFS technology. The results? Interactive user experiences, automated processes, and powerful analytics that inform important business decisions to ensure the success of the enterprise today and into the future.
For a sneak peek at what lies ahead in 2024, read the IFS Predictions 2024: Enterprise Asset Management post.
SOURCE: Mortensen, J. (2024, February 26). Democratizing Access To Artificial Intelligence For All Enterprises. IFS Blog. https://blog.ifs.com/2024/02/democratizing-access-to-artificial-intelligence-for-all-enterprises/
