Accelerating commercial resilience in the chemical industry with generative AI

Over the past 18 months, chemical companies have grappled with stagnant or declining revenues. Internal challenges like fragmented customer data and high turnover in sales teams, compounded by external factors like inflation and supply chain disruptions, have stymied growth. For instance, year-over-year volumes dropped by up to 10% for diversified players and 8% for specialty players in early 2023.

McKinsey identifies a pressing need for chemical companies to transition from passive "order takers" to proactive "hunters." This involves leveraging advanced analytics and Gen AI to rejuvenate customer acquisition, retention, and cross-selling strategies. Companies that embrace these technologies and align their operations accordingly can experience substantial uplifts in sales performance.

Harnessing gen AI to drive revenue growth

Generative AI is a game-changer for marketing and sales functions. Companies using AI tools have reported a revenue increase of 3–15% and a return on investment (ROI) boost of 10–20%. Despite these promising figures, the chemical sector has been slow to adopt sales technologies like customer relationship management (CRM) systems, often resulting in a disconnect between strategic insights and frontline execution.

The report illustrates how Gen AI can enhance the entire customer lifecycle. For example, AI tools can streamline lead validation, prioritize high-potential opportunities, and generate personalized marketing materials. One specialty chemical company, leveraging Gen AI, identified and activated new prospects, building a growth pipeline three times larger than its addressed revenue base. Within a year, the company achieved revenue growth of 10–20% for targeted product lines, underscoring the tangible impact of AI-powered strategies.

Mobilizing sales teams

To bridge the gap between insights and execution, McKinsey advocates for the establishment of "win rooms"—centralized, cross-functional teams designed to empower frontline sales with actionable insights. Unlike temporary crisis management setups, modern win rooms are envisioned as permanent operational models that drive consistent growth.

Successful win rooms operate on a framework of iterative improvement, combining customer opportunity qualification, action planning, performance management, and tailored training. For instance, these teams prioritize opportunities based on granular analytics, develop customer-centric value propositions, and maintain feedback loops to refine strategies. By integrating Gen AI into their processes, win rooms enhance decision-making and accelerate revenue realization.

Key components of an effective win room include:

1. Opportunity Qualification: Using AI to identify high-value customer segments and critical opportunities.
2. Action Planning: Translating insights into executable plans while emphasizing a bias for action over perfection.
3. Performance Management: Establishing frequent touchpoints and cross-functional collaboration to align on priorities.
4. Sales Support Teams: Bringing together experts from marketing, data science, and operations to optimize decision-making.
5. Tailored Training: Building organizational capabilities to ensure sustained adoption of insights-driven practices.

Sustaining growth through strategic alignment

While win rooms offer a robust framework for immediate results, sustaining growth requires integrating these practices into broader organizational processes. McKinsey emphasizes the importance of consistent performance reviews, cross-functional collaboration, and capability-building programs. Regular executive engagement, coupled with clear KPIs tied to CRM standards, ensures alignment across teams and prevents regression to outdated practices.

One notable example is a global specialty chemicals player that used a win room to identify $500 million in new customer opportunities, achieving a 65% increase in pipeline opportunities and a 60% rise in deal closures. By embedding these practices into its commercial operations, the company fostered a culture of continuous improvement and accelerated its growth trajectory.

A blueprint for the future

The McKinsey report concludes with a roadmap for chemical companies aiming to harness Gen AI's potential. The suggested approach includes:

1. Data-Driven Assessments: Identifying growth drivers like customer churn and cross-selling opportunities.
2. Pilot Implementation: Testing win room strategies in high-potential business units before scaling across the organization.
3. Capability Building: Developing the skills, mindsets, and behaviors necessary for sustained impact.

By following these steps, chemical companies can transform their commercial operations, achieve near-term revenue acceleration, and build a strong foundation for long-term growth.

Conclusion

As the chemical industry navigates a complex and dynamic landscape, generative AI and insights-driven strategies offer a compelling path to growth. McKinsey’s report provides a detailed blueprint for leveraging these tools to address industry challenges and capitalize on new opportunities. Chemical players that proactively adopt these practices can position themselves as leaders in an increasingly competitive market.