The People Play Behind Bright’s AI Shift

When I look back at where Bright was 18 months ago versus where we are today, the numbers tell part of the story. 86% of our people using AI regularly. 75% reporting a meaningful improvement in productivity. 46 volunteers in our AI Champions Network. A four-level AI literacy framework, AI embedded into every job description and career pathway in the business. An AI-native product team being built from scratch.

But the numbers aren’t really the point. The point is that we built something that compounds. The interesting part isn’t what we built, it’s how we thought about it.

1. We started with culture, not tools.

The temptation when you’re trying to shift an organisation is to reach for the tool first. Buy the licence. Roll out the platform. Measure the logins. Declare victory.

We did the opposite. Before we asked anyone to change how they work, we asked ourselves a harder question: do our people understand why this matters, not for the business, but for them personally?

The answer, honestly, was no. We started there. At our company all-hands, we put AI on the main agenda, not as a product update, but as a genuine conversation about how work is changing and what that means for everyone at Bright. We’ve repeated that conversation at every all-hands since. AI isn’t in the footnotes. It’s in the room.

That decision to treat AI adoption as a cultural change, not a tech rollout turned out to be the most important one we made. Everything else followed from it.

2. We gave everyone access to the right tools — without friction.

You can’t ask people to change how they work and then make it hard to get started. One of our earliest decisions was to invest in a proper AI tool stack, not just one licence for the curious few, but tools matched to how different teams actually work.

BrightGPT, powered by ChatGPT, went to everyone. Sales got transcription and coaching tools. Marketing got on-brand AI assistance. Engineering got coding assistance. Support got AI-powered telephony and assistive tools. No one had to make a business case to access the technology relevant to their role.

Alongside the tooling, we established an AI team whose job is to bridge the gap between what the technology can do and how people practically apply it day to day. Not a helpdesk. A genuine enablement function, responsive, embedded, and accountable for adoption.

The principle was simple: if someone has to jump through hoops to try something, they won’t. We removed the hoops.

3. We built a skills development ecosystem, not a training programme.

Mandatory training has a ceiling. People complete it, tick the box, and go back to doing exactly what they were doing before. We’d seen that pattern elsewhere and didn’t want to repeat it.

Instead, we built multiple routes to build genuine AI skills designed so people could find the path that worked for them:

• Monthly sessions showcasing AI developments and real Bright success stories. Not lectures but demos from colleagues who’ve actually built something.

• AI Champions Network: volunteers from across every department who test tools, share practical insights, and act as the connective tissue between the AI team and the rest of the business.

• Learning resources: A 20-minute AI intro course created by our own AI team, plus external qualifications for those who want to go deeper.

• A live Teams channel where tips get shared, questions get answered, and peer learning happens in real time.

The build, share, inspire loop; demo what you’ve built, watch your colleagues want to build something too does more than any mandate or memo.

4. We built a shared language for AI proficiency.

At a certain point, “using AI” stops being a meaningful measure. You need to know what good actually looks like and so do the people you’re asking to develop.

We built an AI Literacy Framework with four levels that describe genuine AI proficiency in plain terms. Not abstract competencies. Concrete, observable behaviours:

• Awareness: Understands what AI is and how it will change how we work.

• Working: Uses AI tools regularly to get work done faster and better. This is our baseline expectation for everyone at Bright.

• Practitioner: Confidently weaves AI into workflows and helps teammates level up. For managers: actively driving adoption, not just participating in it.

• Expert: Creates tools and workflows that others use. They don’t just work with AI, they shape how the organisation does.

The framework gives managers something to coach against and gives individuals a genuine reason to progress.

When you give people a map of where they are and where they could go, most of them want to move.

5. Making it stick.

At a certain point you have to put the expectation in writing. We embedded AI competency into our career architecture and built it into our performance conversations. For new hires, AI isn’t an optional extra. It’s table stakes. We’re not asking people to be technical, we’re asking them to be curious, willing to experiment, and serious about using tools that make them better at their jobs.

The biggest risk with any transformation is that it peaks and plateaus. So, we built in mechanisms to prevent that. Quarterly AI pulse surveys track real progress and sentiment, not just logins. AI adoption is a standing agenda point in every HR Business Partner session making it every manager’s responsibility. And AI skills are now part of what good performance looks like across every role. Not a separate add-on. Just how we work.

The goal was never to run an AI adoption programme. It was to reach the point where AI adoption is just how Bright works.

The internal and external journeys are the same journey.

Everything we’ve built internally; the tools, the framework, the Champions Network, the culture of sharing directly informs how we think about AI in our products.

Oscar, the AI assistant built into BrightPay, exists because we believe AI should sit where the work actually happens. Not as a bolt-on. Not as a chatbot that lives in a separate tab. As a genuine part of how payroll gets done, for the accountants and payroll professionals doing it every day.

The discipline of changing how our own people work, the friction you encounter, the moments when someone gets their first real result and everything shifts, is exactly the same discipline required to change how our customers work. We couldn’t credibly build Oscar without having lived the journey ourselves.

If you can’t change how your own people work, you can’t credibly claim to be changing how your customers’ people work.

Where we go from here.

We didn’t start with a better plan than most organisations. We started with a culture that rewards curiosity and a leadership team willing to be honest about the urgency. The plan came later. The compounding followed from there.

If you’re at the beginning of this journey, the most useful thing I can tell you is: just start. The best time was a year ago. The second best time is today.

By Laura Murphy, Chief People Officer, Bright Software Group.

This content may have been developed with the assistance of AI tools. Content is reviewed by a member of the Bright team before publication. Guidance on legislation can be obtained from your industry body.