Explore how genAI systems enhance growth opportunities for the chemical testing equipment industry.
Sales AI
December 19, 2024
The chemical industry is quickly changing — and growing. In the quickly evolving market, we’re seeing an increase in Generative AI (GenAI) as a practical technology across all chemical sectors. AI is no longer an out-of-reach tool or a hype machine that people either fear or marvel at. Instead, the world is watching a shift toward strategic AI adoption, focusing on applications that deliver tangible value.
Where is GenAI going in 2025? Specifically, how is it going to impact the chemical industry?
In this article, Team Nesh explores some current trends and developments that are likely to impact the future of GenAI in the chemical sector. Our CTO, Colin Harman weighs in.
In early 2024, generative AI systems were exciting but elusive. As the technology has matured, developers and users have become more pragmatic in their approach.
Colin Harman, CTO of Nesh, notes: "GenAI is here — and it’s about how you will use it. I’d say that the tech is somewhat mature. It's more about usage and adoption now." Companies are now focusing on how to effectively integrate GenAI into their operations rather than simply acquiring the technology for novelty’s sake.
Illustrating this point, a McKinsey report from May 2024 revealed that the energy and materials industry (which includes chemicals) saw the biggest increase in GenAI adoption. The year prior, energy and materials respondents scored the lowest on a survey for “industries already regularly using generative AI tools.”
While it’s good that chemical companies are now implementing AI, GenAI’s maturation has led to increased skepticism among companies that attempted implementation but were not impressed. Now, stakeholders only want to invest in AI if it makes sense. Chemical companies are reevaluating their AI budgets and prioritizing solutions that address specific business challenges rather than implementing GenAI indiscriminately.
Additionally, retrieval-augmented generation (RAG) is now everywhere. Harman observes, "If a company has a mature IT team that develops their own stuff, then they've probably considered or experimented with doing a RAG solution." The widespread adoption of RAG is enabling chemical companies to leverage their vast repositories of data more effectively. In that case, GenAI is enhancing internal decision-making processes and operational efficiency.
The chemical industry is moving away from the approach of trying to use GenAI for everything. As Harman points out, "People have a much better idea of how to use GenAI better now. It’s less about using AI everywhere, and it's more about common use cases."
Companies are now identifying specific areas where GenAI can provide the most significant impact, such as:
By focusing on targeted applications, chemical companies can gain more substantial returns on their AI investments.
Already, GenAI is an integrated feature in existing chemical industry software — it doesn’t have to be bought as a standalone product. This shift is making AI more accessible and user-friendly for chemical professionals who may not have specialized AI expertise.
For example, platforms like HubSpot are offering GenAI tools as part of their offering, claiming to serve as “AI-powered experts” throughout the service. For chemical teams, Nesh provides AI-based sales tools using enterprise data and advanced manufacturing knowledge to support your team at every step of the value chain.
Sales, marketing, and business development teams in the chemical industry are at the forefront of GenAI adoption. These departments are leveraging tools like Nesh Sales AI to:
The success of these commercial applications is driving wider adoption of GenAI across other departments in chemical companies.
That said, it's still crucial to balance out AI assistance with human expertise. As the complexity of chemical research increases, the role of experienced scientists in interpreting and applying AI-generated insights becomes even more relevant.
Overarchingly, the AI model landscape is likely to be dominated by a few key players in the coming year. OpenAI and Anthropic are the most well-known models that will likely continue. The focus for chemical companies should be on selecting GenAI solutions based on their specific needs and use cases rather than getting caught up in the nuances of different AI models.
To thrive in the AI-driven future, chemical companies will benefit from:
Moving forward, the chemical industry stands on the brink of a new era powered by generative AI technology. By focusing on strategic implementation, targeted use cases, and AI-savvy industry software like Nesh, your team can harness the full potential of GenAI.
Want to learn more about the trends impacting the chemical industry in 2025? Check out our blog post, 10 Chemical Industry Trends Shaping the Future in 2025.
Explore how genAI systems enhance growth opportunities for the chemical testing equipment industry.
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