Insights from our AI Strategy Workshop

According to insights from the recent Leading Resolutions’ AI Strategy Workshop, artificial intelligence is fundamentally reshaping IT operations, from predictive maintenance and service automation to entirely new operating models powered by autonomous “agentic” systems. And while there’s plenty of technical depth behind that, it can be summed up simply:

AI is rapidly becoming the best colleague you’ve ever had: efficient, tireless, and always available.

The AI marketplace is booming, perhaps too fast for comfort. Every week seems to bring new tools, platforms or “game-changers,” making it tricky for organisations to separate the genuinely useful from the digital snake oil.

Analysts from McKinsey and TechMarketView agree that AI is shifting from augmentation (helping humans) to straight-through processing, where intelligent systems don’t just assist but take full ownership of certain tasks. In sectors like manufacturing, finance, operations, and legal, AI could soon handle up to 50% of functional spend.

So what’s the catch? Choosing the right technology is like speed-dating with robots: a lot of potential, but with a few awkward conversations along the way and not all of them you’d want to introduce to your CIO.

Leading Resolutions’ consultants note three major hurdles for organisations diving into AI:

1. Market Knowledge: The tech evolves faster than most governance frameworks can keep up. Picking the right vendor isn’t just about features; it’s about longevity, security, and scalability.
2. Shadow AI: Employees love a free AI tool. IT teams, not so much. Uncontrolled “freeware” tools can often leak sensitive data and create governance nightmares.
3. Time to Value: Early AI projects can take longer to show results if organisations don’t plan carefully. The solution? Follow a structured readiness assessment, align business goals, and share best practices to avoid reinventing the wheel.

As the workshop reminded attendees, success with AI isn’t just about coding, it’s also about choreography.

One of the standout stories from the workshop came from an organisation in the plumbing and heating sector (yes, even boilers are going digital now). Their IT team faced the usual modern pressures: shrinking budgets, rising expectations, and an avalanche of data.

Their response was a complete reimagining of IT operations through AI. They built a new AI-embedded operating model centred on five principles:

• Observability everywhere: full-stack visibility across infrastructure, systems and services.
• Automation-first: reducing friction points and manual intervention wherever possible.
• Experience-driven delivery: measuring success through employee and customer experience, not just service levels.
• Business alignment: connecting IT performance directly to commercial results.
• AI engineering: embedding intelligent automation into every process.

The result was fewer tickets, faster resolution times, and far fewer late-night “all-hands” calls. AI didn’t just fix problems; it predicted them.

Two new stars of the AI universe made a splash in the workshop: Vibe Coding and Agentic AI.

• Vibe Coding is the natural evolution of low-code platforms, except you don’t drag and drop components, you just describe what you want. Think:

“Build me a leaver-tracking app for HR, with a clean corporate UI and manager approval flow.”

And hey presto, the system generates the code, interface, and logic. It’s like having a developer who instantly gets your “vibe”, rapid development powered by conversational intent if you will.

• Agentic AI takes things even further. These are autonomous systems that can plan, orchestrate, and execute multi-step tasks, not just respond to prompts. They call APIs, query datasets, and make decisions, all while staying governed and auditable.
  Imagine a digital operations manager who not only understands the problem but quietly fixes it while you’re still drafting the incident report. It’s automation with reasoning, autonomy with accountability.

Of course, none of this works without solid foundations. AI success depends on good data hygiene, consistent structures, reliable access, and strict governance.
The workshop emphasised that readiness isn’t a one-size-fits-all process, it depends on several must-haves:

• Clear data sovereignty policies (so your data doesn’t end up appearing in an unapproved cloud region).
• Security and access controls that align with InfoSec policies.
• Sanctioned AI platforms, to prevent employees from “experimenting” with sensitive data.
• Observability and guardrails, where every AI action is traceable, explainable, and auditable.

As one speaker put it: before you let AI drive the car, make sure you’ve installed seatbelts, headlights, and a good Sat Nav.

The next wave of AI innovation is neuro-symbolic AI, a hybrid model that combines the learning power of neural networks with the logical reasoning of symbolic systems. Think of it as giving your AI both creativity and common sense.

This blend could finally deliver AI systems that don’t just generate outputs but actually understand why they’re doing what they’re doing, making IT operations even more autonomous, transparent, and trustworthy.

AI isn’t about replacing people, it’s about replacing pain.

By automating the repetitive, predicting the unpredictable, and augmenting human expertise, AI allows IT teams to move from crisis management to continuous improvement. The goal isn’t just efficiency; it’s resilience, agility, and maybe even a bit of serenity.

As one consultant quipped during the session: “We’re not trying to make humans obsolete. We’re just trying to make Mondays survivable.”

Using AI in IT operations is no longer a futuristic idea, it’s the new normal. The organisations thriving in this new landscape aren’t just the ones that adopt AI fastest, but those that adopt it wisely.

With strong governance, the right partners, and a clear sense of purpose, AI will become less of a buzzword and more of a business advantage.

And as the technology evolves, from chatbots to autonomous agents to neuro-symbolic systems, one thing’s certain: the best IT teams of the future won’t be man or machine. They’ll be both, working together in perfect, algorithmic harmony. Exactly as has been the case with writing this article.

And who knows? It might even start writing better incident reports than we do.