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AI is changing how software gets built. AI can now handle many coding tasks much faster, opening up new possibilities for how teams work and what they can deliver. But writing code and engineering software aren't quite the same thing.

Behind every working application are decisions about architecture, integration, testing and maintenance. And as AI takes on more of the implementation work, those decisions don't disappear.

Bobbi has officially arrived in South Yorkshire. This October, South Yorkshire Police launched Bobbi, a new 24/7 agentic solution designed to help around 1.4 million people access policing information and support online. Infomentum has been proud to work alongside the force to deploy Bobbi and bring the new service to life, marking an exciting milestone for everyone involved.

I’ve wanted to go to Dreamforce for a decade. Salesforce Marketing wasn’t exaggerating - it was unforgetable (as was the Cabernet Sauvignon).  Without sounding as middle aged as I am, I literally felt like I was living in the future. 

Driverless cars dropping us off at dinners. Robots walking through the conference. An agentic business development representative more efficient and competent than I’ve seen in more than a decade of sales experience. Then there’s Dreamforce itself. Tens of thousands of people across the campground. 1,600 sessions to choose from. Gwen Stefani opening the keynote. And then Dreamfest.

So yes, there was a lot going on and I’ve finally gotten round to my wrap up!

Having recently wrapped up an IT service management (ITSM) implementation for a large police force built on Agentforce IT Service, I’ve been thinking about what comes next. Not just for the force, but for organisations in general. ITSM has traditionally focused on making it easier for IT teams to manage requests, resolve issues and keep services running. But the need for simple, well-managed services doesn’t stop at the IT desk.

Artificial intelligence (AI) has spent the last few years making promises. Now, with the emergence of agent-based AI, it's starting to deliver them.

For most organisations, AI adoption has followed a similar pattern: a chatbot here, an automation there, maybe a co-pilot bolted onto an existing tool. Useful, but also somewhat limited. These are instruments that respond when prompted. What they don't do is take initiative, hold context, or carry a task through from start to finish. 

That changes with AI agents.

When people talk about the future of IT Service Management, the conversation almost always revolves around AI.

AI agents. Automated resolutions. Predictive insights.

But there is a less glamorous topic that deserves just as much attention: Asset Management. After all, an AI agent can't fulfil a hardware request, recommend sourcing options, or automate lifecycle processes if it doesn't know what assets exist, where they are, or whether they're available.

In my experience working with public sector organisations, one of the biggest challenges isn't a lack of technology - it's a lack of visibility.

Last night’s Digital Revolution Awards brought together organisations tackling real, practical challenges with technology. For our team, it was a brilliant evening to be part of.

It was great to reconnect with familiar faces, meet some new ones, and see first-hand the impact being made across so many different sectors. Moments like that are a good reminder of how much meaningful work is happening in this space.

And while we’ll try to stay modest about it… it made the night all the more special to be named winners of the ‘Excellence in Salesforce’ award for 2026!

As more organisations explore how AI can actually work inside Salesforce, Agentforce is quickly becoming a favourite. Unlike generic AI chatbots, Agentforce uses an organisation’s own internal knowledge base, including files, CRM data, case records, and process logic, to deliver answers that are accurate, contextual, and trusted. This allows you to build conversational experiences that feel natural to users while drawing on the full depth of your operational knowledge.

For this article, I wanted to go beyond the theory.

Every public sector leader I speak to wants to unlock the promise of artificial intelligence (AI). The ambition is clear: to deliver services faster, give staff back precious time, and improve experiences for citizens. The challenge is that budgets are tight, scrutiny is high, and no one wants to waste money on the wrong investment.

That tension often leads to the question… how much should we actually spend on AI?

When people reach out to the police, it’s often at a moment of vulnerability, when something has happened that has shaken their sense of safety and left them unsure what to do next. They may feel anxious, overwhelmed, or uncertain about whether they are using the right channel, sharing the right information, or even raising the right issue at all. At the same time, forces are managing rising volumes of calls, messages, and digital contact under sustained pressure, yet every interaction still represents a person looking for reassurance and support. Meeting these moments in a way that feels timely, confident, and compassionate has become one of the most important challenges facing UK policing today.

But a more supportive, intelligent approach is beginning to take shape.