Generative AI and retrieval-augmented generation (RAG) have become essential tools for chemical technical sales teams.
Chemical Manufacturing
January 23, 2025
The industrial landscape is at a crucial juncture. Intensifying global competition, shifting market dynamics, and significant regulatory changes are causing chemical sectors to pivot.
So far, generative AI (GenAI) has been a powerful tool in helping many companies stay afloat and get ahead. Manufacturers, sales teams, and supply chain operators know the opportunities GenAI has to address the industry’s most pressing issues — but how can they capitalize on them?
From bridging expert knowledge gaps to optimizing product selections, GenAI is no longer just a “concept”. Now, it’s a necessary technology. For the best return on investment, though, chemical companies must correctly navigate generative AI adoption and implementation.
Let’s look at why your team needs GenAI to not only survive but succeed in the future-forward market. Team Nesh explains how AI can transform various chemical operations when selected and used properly.
Currently, one of the most worrisome challenges in the chemical industry is the rapid retirement of industry experts. With the loss of seasoned chemical professionals also comes a loss of technical, institutional, and process-specific knowledge.
Also known as “brain drain,” companies struggle to transfer their expertise among fewer team members who — in many cases — are already taking on additional tasks they might not be prepared for.
Simultaneously, the industry is experiencing an increase in products with a greater complexity of formulations. Plus, supply chain logistics become more intricate every year, and new tariffs under the Trump Administration will drive even greater shifts. Regulatory measures are also changing, forcing companies to be agile and keep up with new, environmentally-focused compliance strategies. Geopolitical factors also disrupt global competition, adding another layer of uncertainty.
Cost pressures are squeezing margins, compelling companies to find new ways to maintain profitability. According to a 2024 market report, AI in the chemical sector is expected to grow from $1.40 billion in 2024 to $12.5 billion by 2031—a nearly 800% increase—to potentially address these challenges.
Early adopters of industry-specific AI know the potential it has for everyday operations. In one example, the chemistry automation company Chemify uses artificial intelligence to upskill employees so that they can translate molecular chemistry tasks into computer coding.
Additionally, AI bridges the problematic knowledge gap companies face as experts retire. GenAI platforms like Nesh synthesize internal data into accessible insights for trainees. This also ensures cohesive information across multiple departments, making product messaging more aligned for technical sales teams. This use case becomes even more critical as the number of mergers & acquisitions rises.
When it comes to navigating regulatory changes, GenAI can be an invaluable assistant. With rapid analysis of new requirements and their implications, teams can use Nesh Sales AI to suggest products that meet a customer’s complex or evolving needs.
In global supply chain management, AI’s predictive models can help companies identify and mitigate potential disruptions, a critical capability in today's volatile geopolitical environment. Other AI solutions are singularly focused on predicting demand to ensure manufacturers are able to better allocate resources.
Despite its benefits, many chemical organizations still struggle to properly implement GenAI and its powerful use cases.
For one, the chemical industry is slow to adopt new technology. More specifically, there are common concerns that cause stakeholders to shy away from GenAI, including:
The good news is that barriers to GenAI in chemicals are surmountable with the right approach.
Successful adoption must start with identifying high-impact uses that align with your business objectives. Additionally, your team must vet and compare the best GenAI solutions to meet these uses while enhancing data security and supply chain compliance.
Need help finding and implementing the right GenAI solution for your chemical operation? Download our Generative AI Pilot Playbook.
It’s also important to build the right team workflow and infrastructure during GenAI adoption. This may involve partnering with AI experts or upskilling existing staff. Equally important is ensuring data quality and accessibility. GenAI's effectiveness relies heavily on the data it's trained on, so working with Nesh Sales AI experts is a wise move.
Change management is another factor to consider. Your company must foster a culture that embraces AI-driven innovation and provides adequate employee training. Buy-in is crucial if GenAI is to be implemented not only properly but also effectively.
Compared to other industries, the chemical sector has been slow to adopt Gen AI. The delay has already been too long. If you haven’t already gotten on board, the time to adopt is now.
Here’s why:
In chemicals, intellectual capital is a huge differentiator. Whether or not your company adopts AI now is bound to have lasting impacts on its position and growth.
In this pivotal time, generative AI adoption is the key to unlocking present stability and future success. From maintaining competitiveness to adapting to the challenges of a changing workforce, GenAI is the solution all chemical companies need to strengthen their operations and sales.
The benefits of chemical-focused AI adoption outweigh the challenges associated with implementing the right solution. To stay ahead, strengthen your team, and keep up with changing regulatory standards, learn how the Nesh Sales AI platform empowers chemical companies to thrive.
Contact Nesh to discuss the right AI solution for your company and set up a demo so you’re prepared for adoption that lasts.
Want to learn more about GenAI use cases for the chemical industry? Check out the fact sheet, The Future of Chemical Sales: 6 GenAI Use Cases.
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