3 Steps to Make Your IFS Cloud AI-Ready in 2025

AI is Reshaping Enterprise Systems

AI is reshaping how enterprises run their business systems, and IFS Cloud is no exception. With the introduction of IFS.ai and emerging Agentic AI capabilities, the platform is moving from being a traditional ERP to becoming an intelligent enterprise engine.

But to unlock that potential, your IFS Cloud environment must be AI-ready, meaning your data, configurations, and integrations are optimized to support automation and learning. Without that foundation, even the most advanced AI models will struggle to deliver accurate or actionable insights.

Here are three steps every IFS customer should take in 2025 to prepare their environment for the AI-driven future.

Step 1: Clean, Governed, and Structured Data

AI is only as smart as the data it learns from. "Garbage in, garbage out" - before deploying IFS.ai or any intelligent automation, organizations must focus on data quality and governance. Clean, consistent, and structured data enables AI models to make reliable predictions and automate decisions effectively.

How to prepare your data for AI in IFS Cloud:

• Audit your data before migration: Identify duplicates, outdated entries, and incomplete records. Pay special attention to master data such as customers, suppliers, and assets
• Use the ProV Accelerator: This proprietary tool simplifies data transformation during migration, helping you move from legacy IFS versions (8, 9, 10 or FSM) to IFS Cloud faster and cleaner
• Establish governance frameworks: Define ownership, validation rules, and data standards. Build a single source of truth across departments to prevent inconsistencies

If your enterprise plans to use IFS.ai or machine learning for process predictions, service optimization, or analytics, this step is non-negotiable.

Pro Tip: Poor-quality data not only reduces AI accuracy but can also increase migration costs and project delays. Make your data clean once, and AI will take care of the rest.

Step 2: Configure for Evergreen, Low-CRIM Operations

IFS Cloud is designed to be evergreen, constantly upgradable without the heavy lift of reimplementation. However, this only works if your system avoids excessive CRIMs (customizations, reports, integrations, and modifications).

The fewer the CRIMs, the better your chances of staying agile, upgrade-ready, and AI-compatible.

What to focus on:

• Adopt standard processes wherever possible: Resist the temptation to replicate outdated workflows. Standardization allows IFS.ai to identify and optimize processes automatically
• Leverage low-code workflows: Replicate familiar user interfaces and automate business processes without custom code
• Automate with built-in tools: Use IFS Cloud's business process automation and workflow management to minimize manual steps and enable end-to-end AI orchestration
• Prioritize change management: Ensure users are trained to input clean, structured data and adopt new AI-enabled functionalities

Result: A simplified, standardized IFS Cloud configuration that evolves with each release, setting the stage for continuous AI learning and optimization.

Step 3: Integrate Intelligence Across Your Ecosystem

AI readiness is not just about what happens inside IFS Cloud. True intelligence comes when the system connects seamlessly with your broader technology ecosystem, from CRM and HR to service and operations platforms.

Integrated systems allow AI models to learn from diverse data sources, detect cross-functional patterns, and deliver insights that span your entire business.

How to achieve integration intelligence:

• Implement hub-and-spoke integrations: Simplify data exchange between IFS and other enterprise systems such as ServiceNow, Salesforce, or Workday
• Centralize data with a warehouse strategy: Create a unified data lake for historical and real-time data, enabling IFS.ai to perform predictive analytics and AI-driven queries
• Adopt API-driven communication: Move away from manual file exchanges and leverage APIs for faster, more secure data transfer
• Ensure visibility across functions: Integrate service, finance, and operations data so your AI models can detect dependencies and suggest optimizations

Outcome: A connected enterprise where every system contributes to a single, intelligent data fabric, allowing IFS.ai to deliver meaningful predictions and process improvements.

Bonus: The Quick AI Readiness Self-Check

Before starting your AI journey in IFS Cloud, answer these questions:

• Is our master data consistent, accurate, and properly governed?
• Have we minimized customizations and standardized key workflows?
• Are our integrations modern, automated, and low-maintenance?

If you answered "no" to any of these, your IFS Cloud system is not AI-ready yet. Start with data cleansing and process optimization before configuring AI modules or integrations.

Why IFS.ai Changes Everything

IFS.ai introduces GenAI and Agentic AI capabilities that allow IFS Cloud to understand context, automate repetitive decisions, and assist users in real time.

Use cases include:

• Predictive maintenance and service scheduling through IFS FSM and PSO
• Automated financial reporting and invoice matching
• AI-driven recommendations for supply chain planning and resource allocation

However, these results depend on clean data, evergreen configurations, and intelligent integration - the very steps outlined above.

The Road Ahead: Partnering for Success

Making your IFS Cloud AI-ready is not a one-time project. It is an ongoing evolution that requires strategic data management, process alignment, and technical expertise.

At ProV International, we help enterprises move from legacy IFS versions to cloud-based, AI-enabled environments using:

• ProV Accelerator for faster and cleaner data transitions
• Comprehensive upgrade, implementation, and AI configuration services

Our goal is simple: To help you turn IFS Cloud into a smarter, self-learning system that drives real business outcomes.