How IFS’ industrial customers are approaching AI use cases

IFS customers are looking to AI use cases that solve practical issues to save money, put intelligence in the hands of front-line workers and analyze maintenance issues in the field.

Here's a look at vignettes from a set of IFS customers at IFS Unleashed 2026 in Orlando.

William Grant & Sons

Badri Narasimhan, Chief Technology and Business Growth Officer, used IFS and its Nexus Black unit of forward deployed engineers to nail down manufacturing issues at its distillery using AI and then worked through multiple processes.

Narasimhan said the company's approach with AI was process first. William Grant & Sons was focused on process and business results first then using AI as a tool. He noted three applications of AI.

• Distillery maintenance. At a large Scotch distillery in Girvan, William Grant & Sons was losing batches and wanted to improve equipment maintenance. Nexus Black worked with operators and maintenance crews on its Resolve AI help tool for frontline workers. Using Resolve, operators could describe an issue and get guidance on their device. Knowledge from the worker was captured for future reference. William Grant & Sons is still gauging the returns on the project, but early indications are promising.
• Procurement. Narasimhan said procurement was another key target for AI tools. The distiller was looking for savings it could capture within the first fiscal year. Nexus Black built a tool in three weeks to identify opportunities in procurement and found $10 million in potential savings. "We were able to find a little bit more than the $10 million, but the question was how much you can capture in a year," he said.
• ERP migration and reporting. William Grant & Sons moved to IFS Cloud and faced a report migration risk of three human days per report. Using AI, the company was able to migrate a test of 48 reports in 30 minutes.

Cadillac Formula 1

Chris Green, CIO of Cadillac F1, decided to build on IFS as the team scaled up. Green noted that Formula 1 teams rely on data.

Cadillac F1 has been using IFS Intelligence for about five weeks as of IFS Unleashed 2026. Green said the following use cases were scoped out for IFS Intelligence.

• CIO analysis and budgeting. Green said he is using natural language questions to explore cost-center data to support planning, forecasting and budgeting. The idea is to save time without asking a team for reports.
• Finding and correcting manufacturing data issues. Since Cadillac F1 is early into its first season, the team is working through how to structure its data. Green said some data should have been serialized for financial reporting, race car safety and engineering processes. Green said he is using IFS Intelligence to identify parts to apply better classification rules.
• Retrospective transaction correction. Cadillac F1 is testing where it can use IFS Intelligence to auto correct data. Given histories have 20 to 50 shop orders, Cadillac F1 is expecting major time savings via automation. "We believe we’ll be able to use IFS Intelligence to reverse those transactions for us. So go back, reverse everything out, correct the data at source, and then play all the transactions back in," said Green.
• Natural language requisitioning for parts, goods and services. This process is still on the drawing board but planned.

EightGroup

EightGroup CIO Mo Dawood said the technical services company focused on workforce and job analysis and used Resolve for frontline engineers. EightGroup is a fast-growing technical services company focused on building maintenance including elevators, HVAC systems and facilities management.

Dawood outlined the following AI use cases:

Workforce and job analysis. EightGroup analyzed engineer job histories to identify strengths and development opportunities. those insights informed development and examined causes for repeat visits. The company is focused on improving its first-time fix rates. "We analyzed the engineers, and we analyzed what jobs they’d done, what they were good at, what jobs needed improvement, where their strengths were, and then off the back of that, we could work out a learning and development profile for them," said Dawood.

Resolve for frontline engineers. Resolve was deployed within two weeks and summarized job history for context. Engineers tweaked the summaries to train the models and add context.

Photo-based data capture. Engineers on electrical jobs had been manually recording fuse and wire details and checking against PDFs. Now they take a photo and use AI to extract details. The time savings worked out to about 24 minutes per engineer.

Overall, EightGroup's Dawood estimates that saving 15 minutes per engineer amount to one million hours saved annually as the company scales.

Kodiak Gas Services

Kodiak Gas Services CIO Pedro Buhigas said the company is scaling its AI agent workforce using IFS Loops to run ERP workflows. Key points:

• The company went live with IFS Loops in August 2025 and its first agent was in production in a few weeks.
• Buhigas said the agent helps technicians and supply chain employees find the right part, locate it in inventory and procure it if needed. Kodiak has seen an 85% efficiency gain for transactions processed by the agent.
• Kodiak is using AI agents because it is constrained by its ability to hire, train and retain workers. The plan is to use AI agents to fill in key gaps.
• Buhigas said it chose IFS Loops over building its own agents because the ERP process orchestration, permissions, auditability and guardrails are preintegrated. "When you think about these ERP-centric processes, where you need business process orchestration, permissions, auditability, traceability—you know the guardrails of a process—building all that from scratch is quite complex, and it’s not where we want our teams to spend their time," said Buhigas.