How non-technical teams can learn to embrace AI

Many organisations are struggling with workplace AI adoption. How to effectively deploy it, allow it and enable it to optimise productivity while avoiding any potential risks.

The reality for most companies is that many staff will be using LLMs to assist them with their work, whether it is sanctioned or not. In the case of AI, it's critically important for companies to think about how to bring these capabilities into the light so that everyone can benefit.

The potential for AI to benefit non-technical team members is significant. Technical and non-technical staff are using AI for productivity gains, from content drafting and support with deep research to progress tracking, automating tasks and reducing toil. We're even seeing AI used as a coaching tool to help with professional development planning.

Bringing AI solutions into an organisation that lacks experience with such tools can be daunting, but it doesn't need to be. For companies at the early stages of adopting AI for productivity gains, straightforward generative AI tools like Gemini, Claude and ChatGPT are great places to start. 

At Eagle Eye, for example, we also use a tool called 'Glean', which is an enterprise AI solution that connects all of our digital tools and data to provide instant Eagle Eye contextualised information for employees in a secure way. It reduces time spent searching for the right information, helps us generate personalised content and can build out automations.

How to overcoming the barriers

There are several things organisations can do to help their non-technical teams who are short on time get something out of AI. For us, as well as adopting tech solutions that are tailor-made for office productivity, we're focused on encouraging experimentation and proactive engagement with AI.

We recognise there's often a stigma around AI use for some companies. This fear stems from concerns around security and risks, lack of knowledge of the tools and their capabilities, and the ultimate fear of being replaced. But we see AI as our collaborator, not a threat or replacement for people.

A lack of leadership communication on the topic can lead to teams feeling insecure about what they can leverage AI for; many might question, for instance, if it's 'cheating' to use AI to accelerate tasks and output. 

In such cases, it is really important to remember that leadership's role is to set the mandate, ensure there is structure around it to cover risks, and encourage safe experimentation and sharing wins.

One of the ways we've helped our teams grasp and benefit from AI is to identify champions. These are people with a curiosity for exploring AI solutions who can help lead the way for others who are less technical. 

AI is moving fast, so through our champs we can focus on continuous learning, knowledge-sharing and relatable use-cases that demonstrate the possibilities. With our champions guiding the way, we're building confidence within teams to find a starting point. 

One of the great things about the currently available LLMs is they can help people to further develop their AI skills, all they need to do is ask for it!

Then, staff can take the examples from their peers and start to think about what might be related to their roles. Don't forget, with so many vendors now embedding AI functionality into productivity tools, it's often easy and accessible to get started. Many daily enterprise systems, for example, now have AI assistants, such as Slack and Google workspace giving people tools at their fingertips.

At Eagle Eye, we've also encouraged this exploration through an internal hackathon to give people the opportunity to build cool things and show them off. This has not only been fun, we've also discovered potential innovations to bring to our day-to-day work. 

It is also helping to highlight the power of what's possible to others in the company who might have previously been less engaged with AI. 

Our hackathon involved teams from across the company taking on various use cases and seeing how AI can be used to solve daily challenges. This collaborative learning hits all departments, leans into our champions and those early adopters to lead the way and share back success to educate the business.

Real Examples of Impact

Our early quick wins using AI demonstrate what's possible when you start small and build momentum. 

Product and engineering teams have used AI to quickly build prototype UIs, helping teams to collaborate and conceptualise ideas in a matter of minutes, not days. The experimentation is iterative. Through the innovation, our customers' user experience is transformed with a smoother UX and 65% reduction in clicks to set up functionality in our platform. 

This initiative isn't a magic wand, it still requires human interaction and multiple iterations, but it shows the gains to be made from allowing this experimentation, starting small and growing as we go to increase our speed to market and value to customers.

Additionally, our QA team has leant into AI tools for testing, and early trials are showing significant reduction in time to test as well as improved accuracy. The team has been picking up new skills and gaining confidence as they go. 

Meanwhile, our HR team is using AI for data insights. AI is a powerful tool to analyse information much more quickly than even our most data-savvy team members. The result is we can get information more quickly and rather than spend time in analysis mode. We can move to action from our insights with greater velocity and validity.

Leveraging technical expertise, adopting the right solutions for the right users, identifying champions who are really interested, and running activities to research, explore and demonstrate AI's potential has worked really well for us.

While Eagle Eye does have a built-in advantage when it comes to recognising the benefits and value that AI can bring, highlighting champions to help those less inclined to play with AI, deploying easy-win tools or solutions, and demonstrating what's possible is something most companies can do to uplift staff engagement with AI.

You don't have to overhaul everything to get started with AI. Leveraging the right mix of tools, peer champions, and providing teams with freedom to experiment with ongoing learning whilst sharing successes, you can help everyone unlock value from AI.