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On this episode of The Chemical Show, Victoria Meyer talks with Kendall Justiniano, Founder & Managing Director of Growth Arc Advisors, about the state of AI in the chemical industry. Kendall argues that the “exploratory phase” is over, and the focus must now shift to achieving real business value. They discuss why many companies remain stuck in experimentation mode and what it takes to move beyond isolated pilots to deliver ROI.
The conversation covers key ingredients for effective AI use: governance, connected systems, and building internal expertise. Victoria and Kendall explore practical barriers like security and data silos, outline where ROI is taking shape in commercial and document-heavy processes, and examine how companies can build context-rich systems for long-term competitive advantage.
Topics covered this week:
- AI Maturity Curve: Why the exploratory phase has ended?
- Adoption vs. ROI: Where chemical companies are seeing returns—and where they aren’t
- Generative AI beyond chat prompts: Building connections with data systems
- The governance imperative: Data access, security, and responsible experimentation
- Commercial Applications: Sales, marketing, and procurement as major opportunity areas
- Context Layers: Embedding company know-how into AI workflows for differentiation
- Measuring and validating AI performance as systems evolve
Killer Quote: “We’re the ones doing the cross-system scanning—and that’s where your AI is going to live. It’s going to live right next to us.” — Kendall Justiniano
Other links:
AI Series by Kendall Justiniano
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Unlocking ROI with AI in Chemicals | Insights from Kendall Justiniano
Artificial intelligence has shifted from trend to expectation across the chemical industry, but are companies seeing the impact they envisioned? In this episode of The Chemical Show, Victoria spoke with Kendall Justiniano, Managing Director of Growth Arc Advisors, about how chemical and materials organizations are using AI, what’s limiting progress, and how leaders can move beyond experimentation toward actual business results.
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Moving Past the Hype: Where Chemical Companies Stand with AI
AI adoption has been swift, at least in theory. According to Kendall, most chemical companies introduced some level of AI integration last year, but actual uptake and tangible business outcomes still lag behind adoption rates. Victoria Meyer pointed out that while use cases are discussed frequently, the true integration rate within organizations is surprisingly low, sometimes just over 10%.
This doesn’t reflect a lack of curiosity. Many companies have rolled out AI tools, introducing document search and chat-based user experiences. But, as Kendall explained, staying at the chat prompt level isn’t translating to large-scale impact or meaningful ROI. The next step requires companies to dig deeper and connect AI to real business challenges.
Why ChatGPT Isn’t Enough: The Limits of Surface-Level AI
Most employees have interacted with generative AI, using tools like ChatGPT, Copilot, or Claude, but those efforts often remain surface level. True value emerges when organizations connect AI platforms with their core operational data: CRM, ERP, customer files, supply chain records, etc.
When AI can access and analyze interconnected datasets, it quickly uncovers inefficiencies, generates insights, and helps automate complex, cross-functional tasks, things that would otherwise require significant human effort. But to reach this potential, chemical companies need both thoughtful data integration and a clear strategic vision.
Governance and Expertise: The Path from Experimentation to Impact
As companies push AI further into their organizations, governance and expertise become essential. Making system access available to AI introduces new risks, especially with sensitive internal data. Balancing the drive to innovate with the need for oversight ensures AI is deployed safely, responsibly, and with business alignment.
Strategic AI deployment also requires blending business process expertise with technical AI knowledge. Kendall noted it’s not enough to have AI specialists alone. Companies need experienced team members who understand workflows, data structures, and daily operational needs working closely with AI architects to ensure projects address real challenges and don’t remain theoretical. Those who can connect multiple steps and identify automation opportunities will uncover the biggest benefits.
The Winning Formula: Three Critical Success Factors
Several strong themes prevail when it comes to unlocking value from AI in the chemical industry:
- Clear Governance: Define objectives, control access, and set responsible boundaries for AI deployment.
- Connected Data Systems: Integrate AI tools with a range of business systems to enable stronger analysis and more powerful automation.
- Contextual Layering: Develop AI solutions tailored to your organization’s unique processes and culture. AI should sit alongside your business, not just inside a generic software tool.
Without these foundations, AI risks being seen as an interesting experiment, rather than a true lever for business performance.
Where the Value Lies: Practical Use Cases for AI in Chemicals
Where can chemical and materials companies get the highest return on their AI investment?
Kendall points to two major focus areas:
- Unstructured Data Transformation: Using AI to convert contracts, emails, and order documents into structured data especially in procurement and commercial activities.
- Sales and Marketing Content: Automating the transformation and customization of presentations, proposals, and campaigns, supporting sales teams and reducing time-to-market.
These repetitive, information-heavy tasks are where AI can create time savings, boost output quality, and deliver measurable ROI today.
Continuous Evolution: Keeping Systems and Skills Current
AI and its applications are evolving rapidly. As Victoria noted, companies need to continually review their workflows and ensure they are keeping up with system improvements, tool upgrades, and new approaches. Design processes to be adaptable and keep updating as the market advances.
To get past the exploratory phase, AI must become a deeply integrated, continually improving part of the organization customized to your way of business, tightly governed, and regularly enhanced. Companies that embed these AI-enabled strengths will create a lasting competitive edge.
It’s no longer about experimentation. Now, it’s about delivering tangible business value and the chemical companies that act decisively will lead the way.
About Kendall Justiniano:
Kendall Justiniano – Founder and Managing Director, Growth Arc Advisors LLC
As the Founder and Managing Director of Growth Arc Advisors LLC, Kendall Justiniano helps chemical clients find untapped growth opportunities through his team’s expertise in marketing & sales, value growth and strategic transformation. With over 30 years of leadership experience, Kendall is a seasoned chemical executive who has worked across multiple sectors at Fortune 100 and global companies, including Dow, Avient Corporation, and most recently as Vice President of Marketing at W.R. Grace. Known for keen strategic assessment, and results-oriented execution, Kendall’s mission at Growth Arc is to help chemical executives navigate the new realities of today’s challenging business climate.