After 12 years of steady expansion, AI adoption across the materials and chemicals industry has reached a significant turning point.
The Citrine Platform user community has grown by 276% year over year. AI is no longer merely a “nice to have”; it is quickly becoming an essential business capability. To stay competitive, organizations must implement AI faster and more efficiently than their competitors.
Having completed more than 100 enterprise engagements, the Citrine team understands which approaches succeed and which commonly fail. The organization does more than offer software; it supports teams in applying AI to achieve measurable business results through effective change management, strategic alignment, and practical hands-on guidance.
Cumulative registered users of the Citrine Platform. Image Credit: Citrine Informatics
What Successful Companies Do
1. They Create the Right Governance Structure
Meaningful transformation depends on high-level strategic support and effective implementation. Successful digital transformation is distinguished most clearly by the combination of executive sponsorship from the top and consistent execution throughout the organization.
Executive Steering Group
This group makes sure the program has transparent business goals, budget, and visibility. They deal with roadblocks, discuss strategic importance, and measure outcomes. AI initiatives often stall due to misaligned priorities or resource constraints without this layer.
Tiger Team
This is the hands-on, cross-functional group responsible for turning the work into reality.
The team works closely together, meets frequently, and builds momentum. They run pilots, learn quickly from the results, and scale what works.
2. They Select the First Projects Carefully
AI initiatives do not all deliver the same value. The first project establishes expectations and influences how employees view the technology.
Successful organizations select initial use cases that are:
- High business value enough to matter
- Feasible with available data, equipment, and people
- Scalable to future applications
These early successes help create internal advocates. They strengthen confidence and demonstrate that AI is not simply a science experiment; it is a useful tool for improving productivity.
By comparison, teams that begin with excessively ambitious or disconnected projects may lose momentum before achieving visible results.
3. They Move Into the Lab Quickly
Many teams spend too much time searching for the “best model”. However, the greatest value comes from enabling faster experimental decisions with greater clarity and confidence. AI does not eliminate experimentation; instead, it helps direct and speed up the process.
The Most Successful Customers
- Aim to reduce the number of experiments rather than remove experimentation entirely.
- Give priority to moving recommendations into the laboratory quickly.
- Apply experimental results to improve and adjust models over time.
This cycle > model > experiment > learn > improve is where competitive advantage arises.
A “good enough” model that informs an actual decision is more valuable than a “perfect” model that never moves beyond the laptop.
Organizations considering how to expand AI across product development can benefit from the lessons learned through more than 100 enterprise engagements and avoid common implementation challenges.
Hear Directly from Successful Customers
Upscaling AI Company Wide
Saint-Gobain: 34 projects onboarded in 22 entities in 18 months. Video Credit: Citrine Informatics
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Dorfner: Expanded adoption across the broader group. Video Credit: Citrine Informatics
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Syensqo: Innovating patentable polymers. Video Credit: Citrine Informatics
This information has been sourced, reviewed, and adapted from materials provided by Citrine Informatics.
For more information on this source, please visit Citrine Informatics.