Automation & AI Articles

Colourful illustrated workflow diagram with connected nodes representing a custom Slack ticketing workflow

How to Build a Custom Ticketing Workflow Inside a Slack Channel

Most Slack-based support isn’t a service desk; it’s a search bar and good intentions, and every untracked request is a governance issue waiting to surface. Taylor Halliday walks through building a real ticketing workflow with two channels, Slack’s Workflow Builder, and an emoji status board, then lays out exactly which pains mean you’ve outgrown the hack and need a dedicated tool.
Abstract illustrated network of interconnected nodes overlaid on human silhouettes representing agentic AI governance and multi-agent systems

Agentic AI Governance: How Do We Govern What We Didn’t Design?

Agentic AI systems build responses nobody specified in advance, and traditional governance models weren’t built for that. Jon Stevens-Hall draws on complexity thinking, from Cynefin to LLM-as-judge testing, to ask what it takes to govern behavior that develops rather than behavior that’s designed, and why loosening control in the right places might be the only way to keep it.
Abstract illustrated stacked data layers in blue and red representing the AI agent data layer foundation for ITSM trust

Before You Trust an AI Agent, Trust Your Data Layer

Salil Kulkarni, CSIO at Virima, argues that when an AI agent gets overridden, the issue is rarely the model. It’s a data layer that’s stale, incomplete, or missing the context a human would have caught. Drawing on decades leading technology at Caesars, Las Vegas Sands, and in hospitality revenue management, he sets out four conditions a data layer must meet before an AI agent can be trusted to act.
Illustrated robot multitasking at a desk with documents and notes representing ITSM AI agent data overload

Your ITSM AI Agent Isn’t the Problem – Your Data Is

ITSM AI agent pilots that dazzle in the demo but stall in production are usually blamed on the AI model. The article’s author, a ten-year ServiceNow veteran, argues that the real issue is the CMDB beneath it: incomplete, duplicated, and poorly governed data that any AI agent inherits as its own weakness. Before offering four steps to close what he calls a skills gap, not a technical debt problem.
Robotic and human hands sharing a ship's wheel, representing human oversight of AI services

AI Is a Service Too: Why ITSM Still Matters in the Age of AI

AI may automate incidents, requests, and knowledge management, but it also becomes a service that requires governance, accountability, and human ownership. Discover why service management remains essential in an AI-driven future and why trust depends on more than intelligent technology.
Illustration of an old-fashioned balance scale weighing two people, symbolizing how service management measures the value of people

Service Management Still Doesn’t Value People Enough

James Finister has spent a career in service management and now works on AI ethics, and his argument is that the industry still doesn’t value people enough. In episode 11 of Conversations with Giants, he makes the case for governing AI honestly and early, designing work around the people you have, and remembering that SIAM is about relationships and trust, not just the contract.
Illustration of workers building a stone foundation labeled "Service Management Foundations" beneath towers reading "Scaled AI" and "Operations," representing the architecture needed for the intelligent enterprise

Service Management Architecture: The Missing Foundation for AI and the Intelligent Enterprise

AI can only be as effective as the service management environment that supports it. This article explains why service management architecture, rather than tools alone, provides the operational foundation needed for AI, Agentic AI, and intelligent enterprise transformation.
Abstract illustration of a digital service ticket moving through space, representing agentic AI automating IT service desk workflows.

Agentic AI in ITSM: 5 Ways Agentic AI Is Transforming the IT Service Desk

For 30 years, the ticket ran the IT service desk: submit, log, triage, resolve, close. Agentic AI in ITSM is retiring that model, executing fixes across systems rather than drafting them for a human to click through. There are five places IT leaders get this transition wrong, from inflated agentic claims to the governance gap most vendor decks skip entirely, and why the ticket itself may not survive the shift.
Two portraits set into vintage washing machine windows, illustrating AI and humanising IT

A Process Is Still a Conversation: Humanising Service Management

Simone Jo Moore has spent decades arguing that the human sits at the center of every IT process, every tool rollout, every supplier relationship. In her Conversations with Giants episode, she talks about AI as a creative muse and a way to clear the drudgery, why SIAM is a relationship problem at heart, and why she’s still waiting for the industry to drop the dogma and get more honest about the people doing the work.
Illustration of a chat window reading "Can I speak with a human please?" next to a smiling AI chatbot icon, representing employee experience with AI-supported IT chat

How IT Support Can Deliver Better Employee Experiences

IT support is usually measured by first-contact resolution and ticket counts, but rarely by whether employees got what they needed. Drawing on a SolarWinds webinar, Stephen Mann looks at why AI’s biggest value lies in preventing issues before a ticket exists, why channel choice counts for more than any single preferred channel, and why most metrics track IT service desk mechanics rather than the outcomes employees experience.
Illustration of an IT professional walking through an office full of robots, representing the always-on AI question of why human staff are still needed

Always-On AI in ITSM: Why Every Service Desk Employee Will Ask “Why Am I Needed?”

Always-on AI is transforming the IT service desk, but technology alone won’t determine its success. This article examines why organizations must address human purpose, psychological safety and governance alongside AI deployment – and why answering “Why am I needed?” may be the most important question of all.
Illustration of IT workers at old computer terminals facing a large AI creature made of cash, representing uncontrolled AI software spend in asset management

Asset Management Teams Are Being Asked to Govern AI Spend They Can’t See

AI software is the fastest-growing cost in most IT estates, and most teams have no real view of it. The Flexera 2026 State of ITAM Report bears that out: AI tracking is now the field’s biggest challenge, wasted AI spend is climbing, and FinOps is closing in on territory IT asset management used to own. The piece runs through the findings that count for asset and service teams, and what to fix first.
Olympic rings illustration with small AI robot agents standing beside them, representing agentic AI coordination in ITSM

What ITSM Can Learn from the Olympics in the Agentic AI Era

The Olympics demonstrate that success depends on teamwork, preparation, governance, and seamless coordination – not individual talent alone. Discover how these same principles help IT organizations deploy Agentic AI successfully through better context sharing, AI governance, continuous validation, and clearly defined AI responsibilities.
Two grain silos on a farm, each displaying a portrait, representing silos in IT service management

Simplicity, Service, and the Discipline of Asking Why

Christian Nissen spent four decades in IT service management and helped shape ITIL along the way. In his Conversations with Giants episode, he makes the case that the industry keeps isolating capabilities it should be reintegrating, that it has swapped service for product, and that the skills worth learning are older and plainer than newcomers expect. Here are the ideas practitioners can use now.
Confused robot surrounded by a question mark, representing AI operating without context in IT service desks

Beyond Intelligence: Why Context Is the Missing Piece in AI-Driven IT Service Desks

AI is transforming IT service desks, but not in the way many expect. The real limitation isn’t the intelligence of AI models, it’s the lack of usable context in most IT environments. Between CMDB accuracy, knowledge articles, service catalogs, and tacit expertise, AI is only as effective as the information it can access. Without strong context, even the most advanced AI just scales existing issues.