A powerful example of the new reality in manufacturing is unfolding in the HVAC industry. Data centers powering GenAI applications require innovative cooling infrastructure on a scale that was unimaginable even two years ago. HVAC manufacturers are impelled to rethink how they engineer, produce, sell, and service equipment - all simultaneously. This is not an isolated phenomenon. Across the manufacturing industry, organizations face a stark reality: transform their operating model now, or risk obsolescence.

The convergence that changed everything

Manufacturers have traditionally been conservative in adopting new technology. However, the past five years have brought about changes that would have previously occurred over decades. The prevalent paradigm was shattered during the pandemic as businesses were forced to reinvent overnight — shifting to remote operations, digitizing critical workflows and fast-tracking cloud adoption simply to maintain continuity. Since then, the pace of transformation has only intensified.

Over the past 18 months, GenAI has acted as an accelerator. Naturally, the worldwide GenAI spending is expected to reach $644 billion in 2025. This investment reflects a fundamental shift — AI is no longer experimental technology but an imperative for reshaping manufacturing value streams.

At the same time, geopolitical tensions, supply chain fragility, sustainability mandates and competition moving at software speed have created perfect storm conditions. The organizations thriving in this environment share one common trait, which has become the defining competitive differentiator — the ability to adopt capability-led operating models rapidly.

The breaking point of functional silos

For decades, manufacturing organizations structured themselves around discrete functions like engineering designed products, manufacturing built them, supply chain sourced materials, sales sold outputs and aftermarket teams managed service. These fragmented models, which once supported stability and scale, have now become a structural barrier to competitiveness.

Today, this model creates competitive liability. Engineering teams that design products without input from manufacturing create costly production challenges. Supply chain leaders struggle to plan effectively without insight into engineering specifications or production capacity; aftermarket service teams hold valuable field data but rarely loop insights back into product development. This creates a significant value gap — especially given that the aftermarket contributes 25–30% of total revenue but drives more than 50% of profits for manufacturers. When that intelligence is trapped in functional silos, organizations lose opportunities for new revenue models, predictive maintenance and service-led differentiation.

The consequences are measurable. Executives now prioritize supply chain and manufacturing cost management, with 65% rating these areas as particularly important, compared to 52% for labor overheads. Yet siloed organizations struggle to address these priorities holistically. One HVAC manufacturer building everything from scratch now needs platform-based thinking and modular design to meet data center demand — but their functional silos prevent the cross-domain collaboration required.

The capability-led imperative

The path forward requires a fundamental shift in how manufacturing organizations operate. Instead of structuring around functional silos, leaders must realign their business around capability-led value streams — end-to-end workflows that span the full lifecycle of a product: “Plan → Make → Sell → Service → Decommission.” In this model, each capability becomes a center of coordinated intelligence, investment and orchestration, enabling faster decision-making, agility and measurable return.

A capability-led operating model breaks down traditional barriers. Engineering, manufacturing, supply chain and aftermarket no longer operate as disconnected departments; they work as an integrated system, where decisions are informed by shared data and real-time insight. Investment is allocated based on the impact of the enterprise, not departmental budgets. Most importantly, intelligence is embedded into every capability, tailoring optimization to its unique needs. Consider three high-impact capability examples:

• Supply chain transformation: Context-aware and self-modifying systems use predictive forecasting and dynamic demand signals to optimize flows and reduce risk.
• Aftermarket as a revenue engine: Predictive maintenance, intelligent service delivery and lifecycle analytics transform service from a cost center into a profit accelerant.
• New product development and R&D: GenAI accelerates product design cycles with simulation and digital twin integration, while field service insights continuously fuel innovation.

The emerging vision is a modular, composable manufacturing enterprise — built on platform-based product development and plug-and-play technology. This architecture enables manufacturers to reconfigure rapidly as markets shift, scale personalization profitably and unlock sustained competitive advantage by directing investment into capabilities that matter most.

AI as the intelligence layer

AI, notably GenAI, functions as the intelligence layer enabling capability-led transformation. This is not automation — it is augmentation and adaptation. In a capability-led model, AI enhances performance where it matters most:

• Supply chain: Predictive demand modeling and autonomous planning
• Manufacturing: Real-time quality inspection and adaptive production
• Service: Intelligent field service support and predictive maintenance
• Design and R&D: Generative concept creation and accelerated engineering cycles

But the power of AI cannot be unlocked in isolation. Without connected data and a unified digital thread, AI becomes fragmented and ineffective. That foundation is what we explore next.

The path forward

Capability-led transformation represents a strategic imperative, not an option. The winners will be organizations that move fastest to break down functional walls, structure around value streams and embed intelligence into every capability. However, vision alone is not enough — execution requires a solid foundation.

In our next article, we explore the operational backbone that makes this model real — the digital thread, unified data ecosystems and AI orchestration powering transformation across the manufacturing value stream.