The manufacturing industry is evolving as disruptive technologies make wholesale changes to standard operating procedures, especially in industrial maintenance.
In this exclusive interview, Giada Volpin, global product manager at ABB Electrification Services, describes her work with a new generation of technical leaders using advanced analytics and machine learning to lead a “silent revolution” in industrial maintenance.
Volpin discusses the “enormous shift” in maintenance, including the role AI and AR are already playing, successes in preserving and transferring tribal knowledge, and why manufacturers need to rethink industrial talent.
David Mantey: What is the “silent revolution” in industrial maintenance?
Giada Volpin: We’re witnessing an enormous shift in how industries approach equipment maintenance, moving from a reactive “fix it when it breaks” approach to a more proactive and predictive strategy that’s often powered by AI and real-time analytics. At ABB, we’re seeing this revolution unfold through our digital solutions that can predict and prevent up to 70% of potential issues before they arise. Through a more predictive approach to maintenance, we can help customers extend the lifecycles of their assets and reduce industrial electronic wastage.
What makes this revolution “silent” is that it’s happening behind the scenes through the integration of smart sensors, cloud computing, and advanced analytics. While the physical infrastructure of industrial maintenance may look largely unchanged from a layperson’s perspective, the way we monitor, maintain, and optimize industrial infrastructure is being completely transformed.
The era of fixed maintenance schedules is giving way to intelligent, data-driven decision-making, where assets themselves signal when attention is needed.
DM: How are manufacturers using AR and AI to bridge the gap between traditional industrial operations and advanced predictive technologies?
GV: Manufacturers are taking a cautious but practical approach to bridging operational technology with advanced predictive capabilities. The caution is understandable, as integrating new technologies into critical operations requires careful consideration of reliability, cybersecurity, and existing workflows.
However, AR can be an effective gateway for the adoption of these technologies, particularly in knowledge transfer and maintenance. For example, experienced team members can guide colleagues through complex procedures remotely using AR, while AI-driven insights help identify potential issues before they cause downtime. The result is a measured integration where digital capabilities enhance, rather than replace, human expertise.
DM: What is the best way to get stakeholders to buy in to using new technology? What is the ROI?
GV: Stakeholder buy-in comes from demonstrating clear business value and simplicity of use while minimizing operational disruption. The most successful implementations start by identifying specific painpoints where new technologies can deliver measurable improvements, and then to approach implementation strategically, by choosing applications that complement existing workflows while delivering clear efficiency gains.
For example, enabling remote technical support can reduce up to a third of customer site visits by field service engineers, which translates to enhanced time and cost efficiencies while supporting sustainability goals by curtailing unnecessary emissions. It’s my experience that early wins in daily operations typically build the confidence needed for broader technological transformation.
DM: How can these new tools help generational knowledge transfer between colleagues?
GV: These emerging technologies are transforming how technical knowledge is shared in real-time across organizations. For example, when a piece of equipment needs maintenance, rather than flying in a specialist, local teams can receive immediate technical guidance in over 120 languages through our Remote Assistance Solution, RAISE. This service consists of real-time AR-enabled on-screen annotations, digital overlays, and live message chats through smartphones, tablets, or supported wearables.
Additionally, our training solutions help capture expert knowledge and convert it into standardized learning modules that ensure valuable institutional knowledge isn’t lost when experienced employees retire or change roles.
DM: Why do manufacturers need to rethink industrial talent?
GV: The manufacturing sector faces a pivotal shift in its talent landscape. While traditional mechanical and electrical expertise remains crucial, operating a facility in 2025 means we need people who possess a broader blend of capabilities spanning digital systems, data analytics, and predictive technologies to stay on the pulse.
The scale of this challenge is significant – a 2025 Deloitte study on the manufacturing industry indicates that 1.9 million manufacturing jobs could go unfilled over the next decade, with roles requiring higher-level skills projected to grow the fastest. With the cost of replacing a single skilled worker ranging from $10,000 to $40,000, manufacturers need to fundamentally rethink their approach to talent.
It’s key to adopt a workforce strategy that recognizes both the evolving nature of industrial and technical work, and the investment needed to develop and retain people with an expanding skill set. The future of most organizations depends on their ability to attract and nurture talent that can bridge traditional expertise with digital capabilities.