_{1. What motivated your organization to participate in this year's Global AI Awards?}

_{VitalityAI represents the culmination of a multi-year applied AI roadmap for VitalEdge, from standing up our internal AI Labs, to launching our Copilot-powered Insights Agent in December 2025, to the March 2026 launch of VitalityAI itself. Submitting to the Global AI Awards was a chance to put that work in front of a broader AI community and show what's possible when AI is purpose-built for a specific, historically underserved industry rather than adapted from a generic horizontal tool.}

_{2. Could you give us an overview of the AI solution or breakthrough you submitted for consideration?}

_{We submitted VitalityAI, our AI platform embedded directly into dealer workflows for the heavy equipment industry. VitalEdge is the leading global provider of dealer management software in this space, supporting 4,300 dealer rooftops across 20 countries with 40+ OEM integrations through our e-Emphasys ERP and IntelliDealer DMS platforms. VitalityAI connects data from those systems, plus our Integrated Rental and OEM-connected sources, into a shared intelligence layer.}

_{VitalityAI Agents are aligned to specific dealership functions to optimize uptime and availability, rental fleet optimization, inventory, end-customer engagement, and finance Every recommendation comes with explainable context, so users see not just what the system suggests but also why. It runs continuously, without anyone needing to open a separate app or initiate an analysis.}

_{3. How did your team collaborate to develop and refine this AI innovation?}

_{VitalityAI was shaped through close, ongoing collaboration with dozens of dealer customers throughout development — their day-to-day workflows directly informed both the agent architecture and which use cases we prioritized first. That customer-first approach is really what drove our "human-centered" design principle: the goal was always to deliver insight inside the systems dealers already use, not another tool to learn. Internally, that meant building with continuous feedback loops rather than developing in isolation and delivering a finished product at the end. This keeps the customer-collaboration narrative (a genuine strength worth featuring) while avoiding anything that reveals headcount, org structure, or internal process mechanics.}

_{4. What impact do you expect your AI work to have on the broader AI community or society as a whole?}

_{The heavy equipment industry runs on institutional knowledge — expertise built up over decades by technicians and service managers that historically walked out the door when someone retired or left the company. Stephen Wheeler of ASCO Equipment put it well: VitalityAI takes expertise built over 40+ years and makes it accessible to an entire team in real time. That's the broader contribution we're most proud of — showing that agentic AI can democratize expertise within an industry, not just automate tasks, and scale junior technicians' capability rather than concentrate knowledge in a few senior people.}

_{5. Were there any notable challenges during the development of this AI solution, and how did you overcome them?}

_{One challenge inherent in this industry is that dealer data has historically resided in fragmented systems, requiring manual reporting. We addressed that by building VitalityAI as a shared intelligence layer across ERP, DMS, and rental data rather than a bolt-on reporting tool, so agents share a common data foundation instead of working in silos.}

_{6. How does your organization nurture a culture that drives continuous AI innovation?}

_{Security and governance are built into how we develop, not layered on afterward — every release goes through defined testing, validation, and structured review before it ships, with role-based access and least-privilege principles guiding how we build. That same rigor extends to how we innovate: VitalityAI grew out of a deliberate, multi-year roadmap — AI Labs, then the Insights Agent, then the full VitalityAI platform — rather than a single one-off launch.}

_{7. What advice would you offer to teams or companies aiming to make meaningful contributions in the AI space?}

_{Build with your customers, not just for them. VitalityAI's agent architecture and use cases were shaped directly by feedback from the dealers who'd actually use it — that's a large part of why adoption has been smooth: it surfaces inside the systems teams already use daily, with no separate login and no workflow disruption.}

_{8. What are your organization's long-term goals in AI, and how do you plan to advance the field moving forward?}

_{We see VitalityAI's agentic architecture as a foundation rather than a finished product — the model of orchestrated agents sharing a common intelligence layer is designed to expand as we add new agents and data sources.}

_{9. Are there any emerging AI technologies or trends your team is particularly excited about right now?}

_{Agentic AI generally — the idea of AI systems that operate continuously and proactively rather than waiting to be queried — is central to how we built VitalityAI, and we think that shift from reactive tools to always-on, coordinated agents is going to keep reshaping how industries like ours use data.}

_{To dive deeper into Vital Edge Technologies award-winning work, visit their website at https://vitaledge.com/}