Product Information Management (PIM) blog for the Chemical Industry

Your AI Agents Will Be as Good as Your Product Data: Lessons from the Chemical Industry

Written by Christophe Cabarry | Dec 18, 2025 4:58:06 PM

Generative AI is transforming how companies  engage customers, automate support, and accelerate decisions.

At the same time, AI tools have become easier than ever to use, creating the perception that deploying AI agents or selection bots is straightforward. This often leads to the assumption that large language models already contain all the knowledge required, or that feeding them with unstructured documents and data dumps is sufficient. 

In reality, this only works for generic information available in the public domain. 
When it comes to recommending your products, the challenge is very different. 

An effective AI agent must rely on complete, accurate, and up-to-date product data, including detailed attributes, regulatory context, application knowledge, and sometimes internal or confidential information. Without structured and actively governed Product Master Data, AI agents quickly reach their limits. 

When AI HallucinatesIt’s Usually a Data Problem

Imagine a customer asking an AI assistant: 

“Which of your additives meet FDA food-contact requirements and work in solvent-free formulations?” 

If the underlying product data is incomplete, outdated, or inconsistently defined, the AI will try to compensate. This is how “AI hallucinations” occur, not because the model is unreliable, but because the data it relies on is. 

In the chemical industry, such errors are not trivial. 
Incorrect recommendations can lead to compliance risks, loss of credibility, and damaged customer trust. 

AI can only be as reliable as the product knowledge it is allowed to access. 

Why Data Quality Matters More Than Data Volume

Many companies assume that AI will “figure out” their data structure on its own. While modern AI models are indeed capable of detecting patterns, this does not replace the need for high-quality, well-governed data. 

What AI needs is not just more data — it needs the right data. 

That means ensuring that product attributes, compositions, and performance properties are: 

  • standardized across portfolios and regions, 
  • validated by experts, 
  • kept accurate and up to date over time, 
  • and governed as part of an ongoing product lifecycle. 

This is where Product Information Management becomes critical. 

Building a Reliable AI Foundation with ionicPIM

A PIM like ionicPIM provides the trusted data foundation AI agents require to operate safely and effectively in a regulated, performance-driven environment. 

ionicPIM enables companies to: 

  • Centralize technical, regulatory, and commercial product data 
  • Standardize attributes and taxonomies across product lines 
  • Maintain version control and traceability 
  • Ensure continuous data updates and validation 
  • Control access to sensitive or confidential information 

This transforms fragmented information into AI-ready Product Master Data, reliable, contextual, and compliant by design.

From Data Chaos to AI Confidence

With ionicPIM as your AI data engine, you can: 

  • Feed AI models with accurate, validated product data 
  • Guarantee regulatory context in every recommendation 
  • Significantly reduce the risk of hallucinated or misleading answers 
  • Ensure version control and full traceability for compliance 
  • Enable multilingual, 24/7 customer interaction

Instead of relying on generic, public sources, your AI agents now draw from your own verified product intelligence, making every answer as reliable as your internal experts. 

 

Turning AI Into a True Sales Support Enabler

When powered by structured Product Master Data, AI agents can: 

  • Instantly answer product selection or formulation questions 
  • Recommend relevant alternatives or equivalent products 
  • Retrieve and suggest the correct technical and regulatory documents 
  • Assist sales reps with data-driven product suggestions 

This transforms AI from a gimmick into a trusted digital colleague, supporting your commercial, technical, and regulatory teams in real time. 

Data First, AI Second

The chemical companies that succeed with AI will not be those that deploy the most chatbots, but those that invest first in product data quality, governance, and consistency. 

AI does not replace expertise, it amplifies it. 
But only if the underlying data is trustworthy. 

By putting Product Master Data at the core of your AI strategy, you ensure that innovation delivers real value: accuracy, compliance, and speed. 


Ready to Build AI Agents You Can Trust?

Discover how ionicPIM helps chemical companies prepare their product data for reliable, compliant, and scalable AI applications. Contact our experts. 

Explore the full use case: Enable AI Agents for Product Discovery.