AI Works in Demos. But Can It Survive Production?
AI looks great in a demo. The real test is production. In this week's Zero Ticket Minute, Ian explains why success isn't about what AI can do. It's about what it can reliably resolve.
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Escaping the AI Tokenomics Trap in Enterprise IT
AI adoption has accelerated faster than most organizations expected. What started with chatbots has quickly evolved into AI systems capable of making decisions across enterprise environments, with the promise of faster service and more efficient teams. But many organizations are discovering an unexpected challenge: as AI usage expands, costs become harder to predict. Most AI platforms operate on token-based pricing models.
Inside the Buyer's Decision: Governance, Trust, and Production-Ready Agentic AI
Why do so many AI pilots succeed in testing but fail to reach production? In this webinar, Resolve and IT leaders from RisePoint explore one of the biggest challenges facing enterprise AI adoption today: trust. While organizations are investing heavily in AI agents and automation, many initiatives stall before deployment due to governance concerns, compliance requirements, risk management, and lack of operational visibility.
Why ITSM Still Isn't Solving Tickets (And What Comes Next)
Most ITSM platforms make it easier to submit tickets. They don't make it easier to resolve them. As we said in our webinar: "A better front door without backbone orchestration is just a faster handoff." The future of IT isn't faster ticket creation. It's autonomous ticket resolution powered by AI, automation, and orchestration.
Are AI Agents Your Next Security Risk?
What happens when AI agents get employee-level access? In this week's Agents of IT, we discuss AI identities, agent governance, and why "YOLO" is not a security strategy.
AI Agents Are the New Employees: The Identity & Security Crisis Enterprise IT Must Solve
As AI agents become more autonomous, enterprises face a new challenge: How do you secure a workforce that isn't human? In this episode of Agents of IT, Fran Fernandez, Zach Austin, and Ian Coppock explore the growing identity and security challenges surrounding Agentic AI. From permissions and governance to digital identities and access controls, the team breaks down what enterprise leaders need to know before deploying AI agents at scale.
8 IT Infrastructure Automation Use Cases to Prioritize
IT infrastructure automation sounds simple enough on the surface, right? You take repetitive infrastructure work, turn it into automated workflows, and give engineers more time for higher-value problems. This may seem easy, but in practice, it gets more interesting. Modern IT environments are spread across cloud platforms, legacy systems, identity tools, ITSM platforms, monitoring systems, network devices, and business-critical applications.
Shadow AI: Your Newest Employee?
Shadow AI sounds harmless... Until nobody knows what your AI agents are accessing. In this week's Zero Ticket Minute, we’re sharing why Shadow AI is growing inside enterprises and why AI needs guardrails, not just speed.
What Is Enterprise Service Management (ESM)? Explained
Enterprise service management (ESM) applies the proven model of IT service management, catalogs, workflows, self-service, and SLAs, to the whole business: HR, facilities, finance, and more. Here is what it is and how it works. What is enterprise service management, and how is it different from ITSM? In this explainer we define ESM, show how it works across departments, clarify how it builds on IT service management, and cover the mistake most teams make: copying IT ticket forms instead of orchestrating work across teams.
Agentic AI Governance: 5 Controls Enterprises Need for Safe Automation
The promise of agentic AI is dead simple to understand. Instead of waiting for a human to draft every instruction, an AI agent can interpret a goal, take action, and work across systems until the task is done. For IT teams, that motion sounds like the next logical phase of automation. That promise is real... but it’s also where the risk starts. Traditional automation followed instructions. Agentic AI, by contrast, pursues outcomes. That difference turns the entire governance model on its head.