AI is dominating the conversation right now. Businesses are experimenting with it from using tools to draft product descriptions or manage customer queries, to fundamentally transforming processes and workflows. Yet, there are still some trying to work out where to begin.
The challenge is that AI is so often treated as a one-off project, which limits its impact and makes it harder for teams to adopt the technology effectively. Rather than taking a fragmented approach, the key to getting real value from AI is by embedding it into an organisation’s culture, building frameworks to guide AI use and considering AI as part of your broader business strategy.
By making this shift to build an AI-enabled culture, teams can work faster, leaders can make smarter decisions, and customers can experience smoother journeys.
But how do you move from pilot to practice? Here are three takeaways that can help any business turn AI into an everyday advantage.
Make AI a tool for everyone
The first step is to normalise AI across the organisation. This doesn’t need to be a big investment, but rather a gradual process to get your team testing and learning – from the top-down, as well as the bottom-up.
Leaders need to role model behaviour by showing they’re using AI themselves, while also recognising their teams are closest to customer problems and often generate novel solutions. Blending these perspectives and working cross-functionally is where real breakthroughs happen. At Shopify, for example, our CEO Tobi has made reflexive AI usage a baseline expectation. That signal gives teams permission to lean in, while initiatives like hack days and shared access to AI tools—whether you’re in engineering or in the go-to-market team—encourage diverse thinking and unexpected solutions.
It’s also vital to consider how these AI tools fit as part of larger systems. Adoption typically grows fastest when AI is embedded into your team’s existing workflows rather than bolted on as a separate platform. For instance, Sidekick, Shopify’s AI-powered commerce assistant, sits directly inside the Shopify platform so integration into existing workflows is seamless. It uses advanced reasoning capabilities and your business’ sales metrics, inventory and customer data to identify underlying causes of business challenges, recommend strategies and execute multi-step solutions.
The more teams see AI as part of their everyday toolkit, the faster it shifts from a one-off experiment to a cultural advantage.
Build frameworks and encourage collaboration
While getting your team learning and testing AI is a crucial first step, it also takes clear frameworks to ensure experimentation thrives without creating confusion.
A good starting point is to encourage staff to apply AI to repetitive, low-risk tasks that drain time and energy. Whether that’s triaging common queries, summarising customer feedback, or building routine reports, these early wins build confidence and free up capacity for higher-value work.
Just as valuable is creating ways to share what’s working. A prompt library gives teams a place to showcase effective prompts and use cases that others can build on. Informal catch-ups or cross-functional forums can also help surface ideas, spread best practices, and spark new approaches. Leaders play a key role here by setting the tone, showing how they’re using AI in their own work and giving teams a clear view of what “good” looks like in practice.
With AI developing at pace, it’s also important to remember that no one has all the answers, which is why effective AI adoption needs to be treated as a cycle: play, test, learn, share, repeat. Clear success markers, from faster ticket resolution, higher conversion to fewer markdowns keep the cycle focused on outcomes, rather than hype. If it works, scale it. If not, move on. This rhythm of testing and learning is how AI shifts from being a one-off experiment to a part of every day.
Amplify human impact, avoid the shiny
Throughout all of this, it’s important that AI amplifies rather than completely replaces human capabilities. Retail thrives on the human touch: designing authentic experiences, fostering community, and building trust. Meanwhile, AI can be helpful in taking on the time-consuming heavy lifting, from analysing data to generating responses to frequently asked questions.
The risk is getting distracted by novel use-cases. Gimmicks might grab headlines, but they rarely move the metrics that matter. A smarter approach is to consider where AI can make a strategic impact on business goals, and where it can’t.
For example, according to Shopify research, over half (55%) of Shopify merchants across ANZ expect to use AI for content generation such as product descriptions and social media captions in 2025. Conversely, merchants are taking a more measured approach in areas that rely heavily on human interaction. Take customer service: just over a quarter (27%) of local merchants intend to use AI to improve in this area this year. AI can handle common queries or surface information quickly, while people bring the empathy and trust that deepen relationships. The opportunity lies in finding the right balance—using AI where it drives efficiency, and giving teams more space to create the interactions that drive loyalty and growth.
Culture compounds
The journey from “Why AI?” to “Why not AI?” is a mindset shift, one that turns AI from an occasional experiment into an integrated way of working.
The outcome might be a few hours reclaimed each week through automation. It might mean sharper forecasting decisions that save millions in markdowns. The scale and impact looks different in every business, but the principle is the same. The earlier AI is made practical, transparent, and people-centred, the faster the benefits compound.
In the end, it isn’t about chasing every new tool or adopting every use case. It’s about using the resources around you to build the kind of culture that leaves teams more confident, customers better served, and businesses stronger.
James Johnson is Head of Enterprise ANZ at Shopify.