Last month, Konica Minolta CEO Sam Errigo was interviewed by Keypoint Intelligence, and as always, the conversation offered a sharp lens into where our industry is heading. To me, one insight stood out above the rest. In a world filled with uncertainty, ranging from manufacturing constraints to tariffs and other external pressures, there was a clear distinction between what we can’t control and what we can. The focus was simple and powerful: the customer experience.
And at the center of that experience sits one critical function that continues to evolve for the better: service.
For decades, the customer value conversation around office copiers and printers have centered on speeds, feeds, and upfront costs. Organizations compared pages per minute, device fleets, and total cost of ownership, but often overlooked service, which is the most critical lever of all. Today, that paradigm is shifting dramatically. As AI continues to evolve, the real differentiator is no longer just the hardware but the intelligence that keeps it running.
Konica Minolta’s bizhub vCare platform stands as a gold standard in this transformation, illustrating how AI-driven service strategies can redefine customer value and fundamentally reshape cost structures. What we are witnessing is not simply incremental improvement; it is a stepwise evolution from human-led support to AI-augmented, and ultimately AI-led service delivery.
This evolution can be simplified and understood in three phases: Self-Heal, Assisted Intelligence, and Predictive On-Site Optimization—a journey from AI to human interaction that places service at the heart of business outcomes.
Phase One: Self-Heal – When Machines Fix Themselves
The first and arguably most transformative phase is self-healing service. Today, platforms like bizhub vCare already collect vast amounts of operational data consisting of terabytes of device telemetry across fleets nationwide. This data provides the foundation for the next leap: embedding AI directly into device components.
In a self-healing environment, the printer is no longer a passive piece of equipment. Instead, it becomes an active participant in its own maintenance. When something goes wrong, the device doesn’t simply generate an alert. It diagnoses the issue, communicates it to an AI engine, and triggers corrective action automatically. The machine effectively says: “I understand what’s wrong, I know the fix, and I’ve already addressed it.”
This is where the true potential of AI begins to materialize. There is no ticket, no waiting, and no service delay. The benefits are immediate:
From a cost perspective, this is transformative because service costs are no longer being driven by labor and dispatch. Inefficiencies will now begin to shrink. The printer evolves into an autonomous asset, dramatically reducing the need for human intervention and unlocking a new level of operational efficiency.
Phase Two: Assisted Intelligence – Smarter Humans, Faster Fixes
While self-healing represents a significant leap forward, there will always be exceptions where human expertise is required. Traditionally, service workflows are repetitive and inefficient. Technicians, whether remote or on-site, start from scratch, asking customers to repeat information or retracing diagnostic steps. This is not only time-consuming but also frustrating. AI eliminates this redundancy.
When the AI engine cannot fully resolve an issue, it escalates the case with context. Providing not just a simple alert, but also a complete and intelligent diagnosis. This includes a clear understanding of the issue, the data reported by the machine, the corrective actions already attempted, and why those attempts did not resolve the problem. This approach eliminates a longstanding inefficiency in traditional service models: asking questions that have already been answered. Instead, the technician is able to begin exactly where the system left off.
At this stage, the role of the technician shifts significantly. They are no longer troubleshooting from scratch, but rather executing targeted triage or resolution, often remotely, with precision and speed.
The impact is clear:
As we move deeper into the era of agentic AI, this phase becomes even more powerful. AI doesn’t just recommend the next step. It increasingly initiates the action, pushing service closer to full automation while still leveraging human expertise where it matters most.
Phase Three: Predictive On-Site Optimization – Precision Service in Minutes
The final stage redefines the role of on-site service. In traditional models, field technicians operate with uncertainty as they arrive on-site to diagnose, troubleshoot, and resolve in real time. With AI, that uncertainty disappears.
By the time a technician is dispatched, the problem has already been identified, all prior actions are fully documented, and a prescribed fix is in place. The technician arrives informed, prepared, and precise, eliminating the guesswork that has traditionally defined service calls. As a result, what once required an hour can now often be completed in as little as 15 minutes. This efficiency creates a powerful ripple effect across the organization: technicians can complete more calls in a single day, customers benefit from faster resolutions with minimal disruption, and businesses reduce both labor and operational costs. Ultimately, overall service productivity increases significantly. This is where AI and human expertise converge at their best while delivering high-impact outcomes in a fraction of the time.
Rethinking the Value Equation: Service as Strategy
What ties these three phases together is a fundamental shift in mindset: the true value of a printer is no longer defined by the device but defined by the service intelligence behind it. And in times of uncertainty, this becomes even more critical.
While factors like supply chains, manufacturing costs, and tariffs remain outside of our control, customer experience is not. Service is one of the few domains where organizations can actively differentiate, innovate, and improve, both consistently and measurably.
AI-powered platforms like bizhub vCare enable businesses to:
This is not just evolution, but a strategic transformation.
The Road Ahead: AI as the Service Standard
What feels cutting-edge today will soon become standard practice. This is exactly what I am seeing firsthand out in the field when it comes to customer service. Self-healing devices, AI-assisted diagnostics, and predictive on-site service are no longer future concepts; they are actively reshaping expectations across the industry in real time. Organizations that embrace this shift are realizing meaningful advantages, including a lower total cost of ownership, greater uptime and reliability, and more seamless, elevated user experiences. At the same time, those that hesitate risk remaining tied to outdated service models that are slower, more expensive, and increasingly out of step with what customers now expect as the new standard.
The future of print isn’t about better hardware. It’s about smarter service.
By leveraging AI across the service lifecycle, from autonomous self-healing to intelligent human augmentation, organizations can unlock unprecedented efficiencies while delivering exceptional customer experiences. In an unpredictable world, that clarity matters.
Because while we can’t control every external force, we can control how we show up for our customers. And with platforms like bizhub vCare leading the way, service is not only just support but a strategic advantage.
Watch the full Keypoint Intelligence interview here for more industry insights.
