At Versantus, we've been experimenting with various forms of artificial intelligence for many years now, from heuristics for fighting spam to natural language processing and conversational interfaces for Amazon Alexa. Some of those felt like science fiction at the time, but compared with the Large Language Models (LLMs) we have now in the form of ChatGPT, CoPilot and Gemini, they seem basic and clunky.
So while the current trendiness of AI can make it feel like an over-hyped tech bubble, there's no doubt in our mind that this is something else, and it's worth paying serious attention to.
We've been talking to many organisations over the past two years, and the leaders we speak to are excited, concerned, desperate and confused — often all at the same time. The common questions they're asking are:
- What do I need to know about AI?
- How can I use it in my organisation?
- How can I roll it out safely and cost effectively?
- What does the future hold?
We can't necessarily answer the last one, but the first three can be answered in the same way: Get started now. Start to introduce AI tools across your organisation, find ways to experiment, engage your teams and allow them to learn and fail, and gradually identify how to integrate it into your everyday work.
Getting started is sometimes as simple as getting started
There’s an old saying:
“The best time to plant a tree was 20 years ago. The second-best time is today”
Well, today is the best time to plant your AI tree!
It's important with any new technology to consider the impact introducing it will have on your organisation: the people, processes, finances and legal frameworks it operates with. Rushing in without thought can be risky, and the larger your organisation is the harder it might be for you to adapt quickly.
But we believe that LLMs and similar tools will give your people the ability to work in ways you couldn’t previously imagine, and that starting to develop skills in these tools today will give you compound benefits that a slower adopter will struggle to catch up with. Each experiment, each small success, and even each failure you learn from builds a foundation for greater efficiency, smarter processes, and cultural readiness. By starting now, you don’t just gain an early advantage — you create a widening gap between you and those who hesitate, one that compounds daily until it becomes a lasting competitive edge.
Practical tips for introducing AI to your organisation
AI is a commercial imperative
The first and most important point: this isn’t optional. If you want your organisation to remain competitive, to scale effectively, and to be seen as a leader in your field, AI adoption must be driven from the top. Senior leaders can’t sit on the fence — they need to actively sponsor experimentation and adoption. This isn’t about if you should use AI, but how quickly you can adapt it to create an advantage.
Identify and eliminate low-value work
One of AI’s most immediate benefits is freeing people from repetitive, low-value tasks. Think about the areas in your business that consume time but don’t add much to the bottom line:
- Drafting first versions of documents and reports
- Summarising meetings or interviews
- Scheduling and admin tasks
- Searching across scattered systems for information
These are perfect places to begin experimenting. Even partial automation here gives your teams more energy for creative, strategic, and client-facing work.
Help your people become more T-shaped
AI won’t replace specialists, but it will make multi-skilled teams even more effective. Encourage individuals to use AI to broaden their capabilities outside their core expertise. A designer can use AI to speed up copywriting. A developer can use it to generate test cases. A project manager can use it to analyse survey data. Over time, your people become “T-shaped”: strong in their main discipline, but supported by a broader set of skills powered by AI.
Provide the right tools
Don’t expect people to experiment with free versions of AI tools. Invest in licences for ChatGPT, CoPilot, or other enterprise-ready systems. These come with better features, enterprise-grade security, and the assurance that your company’s data isn’t being used to train public models. It also sends a clear message: we’re serious about this — you have permission to explore.
Make failure safe
If people feel they’ll be judged harshly for failed experiments, they won’t take risks. Create a culture where experiments — even those that flop — are celebrated for what they teach. Share stories of both successes and failures, and frame failure as progress: you’ve found one more thing that doesn’t work, which gets you closer to something that does.
Build connections and conversation
AI adoption thrives on shared learning. Encourage your teams to talk to each other about what’s working and what isn’t. Set up Slack channels, Teams chats, or regular “show and tell” sessions. A quick lunch-and-learn where one person demos how they saved two hours using AI can inspire a dozen others to try something similar.
Run hackdays and workshops
Structure matters as much as culture. Organise regular hackdays or workshops where teams step away from their normal tasks and dedicate time to experimenting with AI. Give them real problems to solve, access to the right tools, and permission to think creatively. These events not only generate ideas but also accelerate skills adoption.
Bring in external expertise
Finally, don’t do this alone. External consultants can provide training, frameworks, and hard-won experience from other industries. They’ll help you avoid common pitfalls, move faster, and bring a fresh perspective. Engaging experts early ensures your teams build on solid ground rather than reinventing the wheel.
Want to know more?
We’ll be talking more about this at our upcoming free webinar, Versantus Presents. We'll share practical examples, frameworks we’ve developed, and the pitfalls to avoid.