AI for chemistry: how artificial intelligence transforms the chemical industry

The chemical industry faces major reliability, efficiency, and innovation challenges, as well as the need to become more sustainable. Companies are looking for new technologies to answer those needs, and artificial intelligence presents itself as a part of a solution. Let’s dive into the opportunities technology creates for the chemical industry.

Challenges among chemical companies

The chemical industry faces constant pressure to maintain reliable and efficient production while managing costs. Achieving stable and consistent output is essential, but traditional production cycles can be slow, particularly in sectors such as basic and specialty chemicals, agrochemicals, construction chemicals, and industrial gases. Prolonged processes can delay time-to-market and increase material waste, contributing to higher costs and environmental impacts. Additionally, the industry encounters high maintenance and research and development costs.

Businesses are rethinking how they use their workforce. Employees often spend a significant amount of time on repetitive tasks, such as generating reports or analysing data, which leaves less room for creativity and problem-solving. AI is helping to address this issue – not by replacing people but by supporting them. With a “human in the loop” approach, AI manages routine tasks and provides real-time insights. This allows employees to concentrate on decisions that require their expertise.

Sustainability is also on the radar, though it tends to take a backseat to the more immediate challenges of cost control and production reliability. Companies still need to reduce emissions and waste to meet regulatory requirements like the EU Green Deal or SEC climate-related disclosures. Still, these efforts must complement the drive for operational stability and profitability.

How does artificial intelligence address those issues?

AI helps the chemical industry tackle challenges by improving efficiency, reducing costs, and supporting better decision-making.

In production, artificial intelligence analyses data to identify inefficiencies, predict issues, and recommend adjustments. This cuts waste, ensures quality, minimises downtime, and speeds up operations. In research and development, AI processes large datasets to suggest optimal formulations, saving time and costs while accelerating product development.

The technology supports employees by presenting clear insights from complex data, enabling smarter, faster decisions. It also identifies bottlenecks, streamlines workflows, and helps meet sustainability goals by reducing waste and optimising energy use.

Implementation of AI in the chemical company PPG

An example of the successful implementation of AI solutions is PPG. The use of artificial intelligence in a chemical company was presented by Marta Golden during the AI Connect event.

PPG, a global leader in coatings and speciality materials, successfully introduced AI to address many of the mentioned issues. PPG has implemented AI systems to optimise their automotive paint production process, significantly improving efficiency. Traditionally, producing a batch of paint required up to eight production cycles, which consumed time, energy, and raw materials. With AI-driven tools, PPG could reduce this to just two cycles. The AI systems analyse data from previous batches, identify patterns, and provide precise recommendations to achieve the desired product faster. This change has accelerated production and reduced material waste, lowering costs and environmental impact.

AI has also assisted employees at PPG by simplifying tasks that used to require highly specialised knowledge, such as mixing precise pigment formulations for specific colours. With AI-powered support, specialists receive recommendations that relieve them from repetitive trial-and-error processes.

How does Spyrosoft introduce digital transformation in chemical companies?

At Spyrosoft, we understand that digital transformation is not just about technology – it’s about aligning innovations with the specific needs and concerns of chemical companies and their personnel.

Implementation phases of AI projects

We have developed a way of working for artificial intelligence implementations, which consists of five stages:

During the Discovery Workshop phase, we gather stakeholder requirements, identify AI opportunities, and research the competitive landscape. We set the stage for Proof of Concept by outlining necessary models, algorithms, and infrastructure while analysing existing business processes for AI enhancement.

At the Proof of Concept phase, we conduct rapid prototyping to assess the idea’s feasibility. Models are created using a subset of data, and an initial working prototype is developed to showcase its value. Wherever possible, we use our ready-made solutions – chemical industry-specific accelerators – or recommend technologies from trusted partners. This approach speeds up time-to-market and helps reduce overall project costs.

The Pilot phase introduces a Minimum Viable Product aimed at a specific business subset, such as a product or region. Full-scale models are built with complete datasets, and the solution is refined based on feedback to achieve business objectives.

During Deployment, we transition the Minimum Marketable Product (MMP) into production with fully operational front-end and back-end systems. The solution comes with full DevOps and processes to manage a scalable IT environment. We monitor KPIs to ensure the solution meets set expectations.

The Sustaining Adoption & Scaling phase engages the organisation to maximise the solution’s potential, focusing on continuous improvement, infrastructure maintenance, application support, and effective monitoring to ensure smooth operations.

Four strategic areas to implement AI

Our approach focuses on four key areas where digital tools powered by AI can drive meaningful change:

1. Production and operations

The chemical industry faces ongoing pressure to enhance efficiency, cut costs, and meet rigorous quality standards. Advanced AI-driven services like AI Batch Processing, Digital Twin, Predictive Maintenance, and Prescriptive Maintenance are transforming how companies address these challenges.

AI Batch Processing streamlines processes such as colour matching in coatings. Previously reliant on manual testing by specialists, one of our clients now uses AI to analyse input parameters, resulting in a 25% reduction in material waste and a 50% decrease in human input, enabling employees to focus on strategic tasks.

Digital Twin creates virtual models of production systems that gather data from sensors, optimising performance in real time. They can monitor energy use and support decarbonisation initiatives, improving operational efficiency and regulatory compliance.

Predictive Maintenance anticipates equipment failures by using IoT sensors and AI to monitor metrics like temperature and vibration. This proactive approach reduces unplanned downtime and minimises repair costs by identifying issues early.

Prescriptive Maintenance provides actionable solutions, such as adjusting operational settings or scheduling repairs, ensuring effective interventions and optimising resource use.

2. Research and development

For R&D departments, we offer the Formulation Assistant. This tool simplifies and speeds up the process of designing new chemical formulations. By leveraging AI, it predicts optimal chemical combinations, saving time and resources while improving product quality. It’s particularly valuable for companies looking to meet stringent quality standards or experiment with more sustainable materials.

3. Support functions

Our Chat Assistant supports employees in routine tasks such as generating reports, analysing data, and answering operational queries. This tool allows companies to support their workforce in day-to-day tasks or empower them to engage in more strategic and creative activities. It also provides immediate insights and reduces reliance on external systems, which helps companies save time and costs.

4. Marketing and sales

In the marketing and sales area, AI tools analyse market trends and customer behaviour to support decision-making. Whether it’s forecasting demand or optimising pricing strategies, AI ensures that sales teams can focus on building stronger relationships with clients rather than sifting through complex data sets.

Our role is to search for areas that can be improved with the help of artificial intelligence. We have pre-developed software components and products that we have successfully implemented in chemical companies. But we want to expand ourselves beyond selling off-the-shelf solutions. We treat each case individually and create customised solutions preceded by a thorough consultancy phase.

“Okay, but…” – most common doubts about AI implementation

We are not familiar with artificial intelligence technology

If your company is considering implementing AI solutions but is unsure of the best area to start, or if you feel your organisation’s technology readiness is not yet where it needs to be, we have the perfect solution. We offer tailored workshops designed to familiarise your team with AI technology and guide you on how to use it effectively, even in less strategic areas. Our Hyper Care service also provides ongoing support through weekly meetings with a dedicated Project Manager or AI Consultant. This ensures a smooth implementation process by collecting feedback, monitoring usage, delivering additional training for users, and planning the rollout of further functionalities.

I don’t want to introduce AI straight into critical areas

Digital transformation can feel overwhelming, so we often begin with less critical areas, such as employee support. For instance, implementing the Chat Assistant is a low-risk, high-impact way to demonstrate the benefits of AI to employees and build organisational confidence in the technology. Once a company is comfortable, we expand the transformation to more sensitive areas like production and R&D, ensuring a smooth transition.

With various hardware and software providers, our data is decentralised

We can develop a system that integrates data from multiple sources into a single platform, enabling companies to utilise it more effectively, manage production processes efficiently, and leverage data across various business areas. The final product often takes the form of web applications with features such as data visualisation or integration with large language models (LLMs), allowing users to access and analyse data seamlessly through AI-powered chat interactions.

My company has too little data, or the quality is too low

One of the most common fears we encounter is that companies believe they have too little data or that their data is of poor quality. We address this by helping them collect, clean, and organise their data to make it AI-ready. Our team ensures that the foundation for AI applications is solid so clients can achieve meaningful results.

I’m not sure how to handle the change management process

Another significant concern is the fear of organisational change. Many companies lack the internal expertise to manage such a transformation. We guide them through the process, offering change management services, including staff training, gradual implementation of new tools, and regular feedback sessions. This ensures that employees feel supported and empowered, rather than threatened by the new technology.

Moreover, we customise our tools to fit each client’s specific needs. For example, if a company requires additional information fields or features in their interface, we work closely with them to adapt the product. By listening to their feedback and tailoring our solutions, we make the transformation as seamless and effective as possible.

Spyrosoft’s background in AI solutions for chemistry

We have a track record of successful cooperation with several global chemical companies, proven by our client success stories. One of our proudest achievements is receiving PPG’s Excellent Supplier Award, which recognises our commitment to quality and innovation in their AI-driven transformation.

A team of specialists with expertise and degrees in AI, machine learning, data science, and chemistry bolsters our credibility. We stay at the forefront of artificial intelligence trends, having hosted the Connect AI, one of the biggest events in Poland on this subject. Our partnerships with leading technology providers, including AWS, Microsoft Azure, and NVIDIA, enable us to integrate advanced tools into our solutions.

We emphasise flexibility, working closely with clients to develop tailored solutions that meet their unique needs, earning us strong referrals across the chemical industry. Our commitment to quality and security ensures that our solutions are reliable and compliant with industry best practices.

Are you looking for a technology partner to help you start digital transformation?

If you are interested in solutions for your chemical company, visit our AI for Chemical Industry subpage or contact us using the form below.