Davos 2025’s Roadmap to $4.4 Trillion - Collaboration for the Intelligent Age
Unlocking Generative AI’s Potential in Manufacturing
Davos 2025 kicks off this week in Switzerland which is always a bellwether for global economic priorities. This year, under the theme “Collaboration for the Intelligent Age,” leaders from across industries converge to discuss how emerging technologies—especially generative AI—are transforming business landscapes. For the global manufacturing sector, the stakes couldn’t be higher but the initial enthusiasm and flurry of activity in 2023 is giving way to second thoughts and recalibrations as companies realize that capturing gen AI’s enormous potential value is harder than expected.
McKinsey & Company’s latest insights on generative AI, shared in the lead-up to Davos 2025, underscore the magnitude of the opportunity. They estimate a potential $4.4 trillion value unlocked by just generative AI. To realize this promise, organizations must “rewire” NOW across six core dimensions:
Strategy: Aligning AI with Business Goals
Talent: Building an AI-Ready Workforce
Operating Model: Reimagining Processes
Technology: Modernizing Infrastructure
Data and AI: Harnessing the Right Assets
Adoption, Scaling, and Sustainability
Here, we’ll explore what this means for marketing organizations, manufacturers and how C-suite executives worldwide can lead their organizations into this new era.
Strategy: Aligning AI with Business Goals
Generative AI is not just another shiny tool; it’s a transformative enabler. Manufacturers must integrate AI into their strategic frameworks, ensuring alignment with overarching business objectives. Think of it as your company’s new secret weapon—like your coffee machine, but for data-driven decisions.
Key Actions:
Focus on value-driven applications: Use generative AI to optimize supply chains, enhance product design, and streamline production processes.
Leverage scenario planning: Anticipate how AI adoption will reshape market dynamics and competitive landscapes. (Hint: Probably faster than your current strategy meetings.)
Prioritize cross-functional collaboration: Break down silos between R&D, operations, and sales to maximize AI’s potential.
Beyond these steps, strategy formulation must consider the evolving regulatory landscape. As AI continues to reshape industries, governments worldwide are implementing frameworks to ensure ethical AI use. Manufacturers should proactively engage in these discussions to align their AI strategies with emerging standards.
Future Focus: Generative AI can also unlock new business models, such as product-as-a-service or mass customization. By leveraging AI to predict customer preferences, manufacturers can design personalized offerings that enhance customer satisfaction and drive revenue growth. And if nothing else, it might finally end those endless strategy meetings—or at least make them shorter. (A win for everyone!)
Considerations for the Marketing Organization: Marketing departments should leverage AI to refine customer segmentation, create more personalized campaigns, and predict market trends. Align marketing strategies with the broader organizational goals by utilizing AI-driven insights to communicate the brand’s innovative edge.
Talent: Building an AI-Ready Workforce
In the age of AI, the workforce needs to be more tech-savvy than ever. Sure, AI can crunch numbers, but it still needs humans to interpret results and, occasionally, tell it to take a chill pill.
Key Actions:
Upskill and reskill: Offer training programs to equip employees with AI literacy and data analysis skills.
Recruit specialized talent: Focus on hiring data scientists, AI engineers, and domain experts who can bridge the gap between technology and manufacturing. (Bonus points if they also know how to explain it to the marketing team.)
Champion inclusivity: Build diverse teams to ensure AI solutions are robust and unbiased.
To fully harness the potential of talent, organizations must also address cultural barriers. Fear of AI replacing jobs remains pervasive, and it’s up to leadership to calm nerves. A good start? Remind everyone that AI can’t attend client dinners or negotiate contracts—yet.
Long-Term Vision: AI readiness isn’t just about technical skills. It requires fostering creativity, adaptability, and critical thinking—human traits that complement AI capabilities. After all, AI might handle the numbers, but it still needs humans to bring the charm and the coffee.
Considerations for the Marketing Organization: AI proficiency is now essential for marketers. Train your team to use AI tools for tasks like content creation, campaign analysis, and customer journey mapping. Additionally, foster a culture where creativity and technology coexist, ensuring that your brand’s voice remains human-centric even in an AI-driven environment.
Operating Model: Reimagining Processes
To harness generative AI’s potential, manufacturers must rethink their operating models. Translation: Less paperwork, more automation, and, hopefully, fewer meetings.
Key Actions:
Streamline operations: Use AI to automate repetitive tasks, such as quality control and inventory management.
Adopt agile practices: Empower cross-functional teams to experiment and iterate quickly. (Finally, a use for all those sticky notes!)
Enhance decision-making: Integrate AI insights into boardroom discussions and strategic decisions.
A responsive operating model powered by AI also enhances resilience. Manufacturers can use AI to simulate scenarios and develop contingency plans for disruptions. And for once, the “supply chain” in your morning meeting agenda might be less stressful and more innovative.
Considerations for the Marketing Organization: Redesign workflows to incorporate AI tools that automate repetitive tasks, such as email marketing and A/B testing. Embrace agile marketing practices to quickly adapt campaigns based on AI-driven insights and feedback. Collaboration with operations teams can also ensure alignment on customer-facing messaging.
Technology: Modernizing Infrastructure
Generative AI thrives on robust technological foundations. In other words, if your company’s tech stack was last updated when floppy disks were a thing, it’s time for an upgrade.
Key Actions:
Upgrade legacy systems: Transition to cloud-based platforms that enable real-time data processing.
Ensure cybersecurity: Protect AI systems from cyber threats with robust security protocols. (No one wants their predictive maintenance system predicting the wrong things!)
Embrace interoperability: Integrate AI solutions seamlessly across existing systems and platforms.
Adoption also demands attention to edge computing, especially for manufacturers with decentralized operations. Edge computing enables real-time AI processing on factory floors, reducing latency and reliance on centralized systems. Think of it as AI’s version of multitasking—but better.
Considerations for the Marketing Organization: Marketers must ensure their tech stack integrates seamlessly with AI tools, enabling real-time data analysis and personalized customer engagement. Advocate for investment in platforms that support advanced analytics, customer data platforms (CDPs), and marketing automation tools to stay ahead of competitors.
Data and AI: Harnessing the Right Assets
Data is the lifeblood of generative AI. Or, as marketers like to call it, "pure gold." High-quality data enables predictive analytics, empowering manufacturers to identify trends and optimize operations. And remember, nothing makes an organization happier than accurate data—it’s like catnip for those quarterly reports.
Key Actions:
Centralize data management: Create a unified data lake to eliminate silos.
Focus on quality: Implement rigorous data-cleaning protocols to ensure accuracy and reliability.
Adopt ethical practices: Establish governance frameworks to ensure data privacy and compliance with global regulations.
Considerations for the Marketing Organization: Data is the foundation of effective marketing. Prioritize clean, accessible, and actionable data to power AI-driven campaigns. Establish clear governance policies for customer data to maintain trust and compliance while utilizing insights to deliver highly targeted marketing strategies.
Adoption, Scaling, and Sustainability
Successful adoption of generative AI requires a clear roadmap for scaling solutions and ensuring long-term sustainability. Manufacturers must think beyond pilot projects to achieve enterprise-wide transformation. But don’t forget: sustainability isn’t just a buzzword—it’s a necessity.
Key Actions:
Start small, scale fast: Focus on quick wins to demonstrate value, then expand initiatives systematically.
Embed sustainability: Use AI to optimize energy consumption and reduce waste in manufacturing processes.
Measure impact: Track KPIs to evaluate AI’s contribution to financial and operational goals.
Considerations for the Marketing Organization: Start small by testing AI-driven marketing initiatives, such as predictive analytics for lead scoring or AI-generated content. Scale successful campaigns and measure impact using KPIs aligned with business goals. Sustainability should also be a focus, ensuring that marketing efforts reflect the organization’s commitment to green practices.
Looking Ahead: A Call to Action for C-Suite Leaders
As Davos 2025 unfolds, the dialogue around technology and generative AI will shape the future of manufacturing. For C-suite leaders, the time to act is now. By rewiring strategy, talent, operations, technology, data, and adoption practices, manufacturers can seize the $4.4 trillion generative AI opportunity while addressing the profound implications for the workforce and society at large.
Companies looking to score early wins with gen AI should move quickly. But those hoping that gen AI offers a shortcut past the tough—and necessary—organizational surgery are likely to meet with disappointing results. Launching pilots is (relatively) easy; getting pilots to scale and create meaningful value is hard because they require a broad set of changes to the way work actually gets done.
Let Davos 2025 be a turning point—not just for increased value creation, but for decisive actions that drive collaboration, innovation, and sustainable growth in the intelligent age. And if marketing departments are reading this, take heart: all this AI might mean fewer late nights and more time doing what you do best—growing your brand and products to accelerate profitable ROI for your company!
About the Author
Shayne De la Force is a globally experienced Chief Marketing Officer, bringing over two decades of operational C-Suite leadership in marketing strategy, advanced manufacturing, and international market expansion. With a career spanning six continents and multiple manufacturing industries, he now drives transformative results for B2B manufacturing clients globally as an independent CMO. Shayne specializes in helping businesses accelerate decision-making and adapt to market challenges with speed and precision. Through The CMO Syndicate, he provides immediate, proven expertise to drive profitable growth, reduce risk, and position organizations for long-term success. Shayne can be contacted at: shayne.delaforce@cmosyndicate.com