AI & Emerging Technology
Applying AI where service operations actually break
This hub explores how AI and emerging technologies can improve service execution, decision-making, and customer outcomes. It focuses on practical use cases, readiness considerations, and cross-functional impact rather than isolated pilots or tool-specific features. The perspective is shaped by working with service organizations testing, scaling, and sometimes intentionally stopping AI initiatives based on data quality, process maturity, and change readiness.
Core AI Insights
Platform of Platforms: Why Individual Tools Are No Longer Enough
Discover how a “Platform of Platforms” approach transforms field service management. Learn why integrating planning, execution, quoting, and analytics under one connected architecture is key to service-led growth. Explore enablers, business benefits, and real-world use cases that show how unified platforms drive efficiency, revenue, and customer experience.
Quantum Computing in After-Sales Service
Quantum computing is beginning to reshape after-sales service in the industrial and automotive sectors- enabling smarter maintenance, routing, inventory, and materials innovation when integrated with AI, IoT, and enterprise systems. This article explores how early pilots are delivering value, what kinds of organizations should adopt, and how to determine when the quantum leap is truly…
AI Won’t Replace Customer Service: It Will Redefine It
AI, GenAI, and agenticAI are often hyped as replacements for customer service, but in reality – especially in after-sales and field service for manufacturing and automotive industries – they are enablers, not substitutes. These technologies cannot replace the human expertise, accountability, and customer trust required in complex, high-stakes service environments. The future of service transformation…
The Service Organization of 2030: Powered by AI, Led by Customer Value
By 2030, service will no longer be about fixing what’s broken – it will be about delivering continuous outcomes. For manufacturers and service leaders, this marks a profound shift. Customers won’t just buy machines; they’ll buy uptime, sustainability, and results. And in a decade defined by AI, intelligent products, and connected ecosystems, service will become…
How AI Can (Actually) Help After-Sales Service – Beyond the Hype
Discover how AI is revolutionizing after-sales in industrial manufacturing – from complaint triage and technician scheduling to predictive maintenance and customer companion bots. This in-depth guide explores business challenges, real-world use cases, and measurable KPIs, helping manufacturers unlock efficiency, revenue, and customer satisfaction at scale.
Featured Articles
Handpicked insights on the biggest shifts shaping after-sales and field service
Service Leadership in the AI Age: From Cost Containment to Force Multiplication
In the AI age, service leadership is being redefined by a paradoxical mandate: lower costs, shrinking workforces, and rising customer expectations. Move beyond the hype of “predictive” service to master Data Orchestration and Force Multiplication….
The 2026 Service Blueprint: From Predictive AI to Agentic Operations
2026 marks the end of AI experimentation and the rise of Agentic Execution. As assets become software-defined and margins shift to uptime, service leaders must master Industrial FinOps and ‘teleporting expertise’ to protect Customer Lifetime…
Why Service Revenue Remains Untapped (Even When Everyone Has a Strategy)
Service revenue remains one of manufacturing’s biggest untapped opportunities. Many leaders have the strategy, but execution falters due to data gaps, weak change management, and unclear ownership. This article explores why most initiatives stall, what…
