AI won't fix your strategy problem
AI has become increasingly difficult to ignore across the design industry, but not everyone is responding to it the same way. A small group of early adopters are already investing in a range of tools focused on increasing output at a lower cost. A larger group, by contrast, are continuing to test new tools as they come to market, often influenced by what competitors are doing. Some are bringing in specialists to help navigate integration challenges, while others are still holding back, wary of what it means for design authorship.
That dynamic isn't unique to design. 2026 ‘The State of AI in the Enterprise’ research found a similar trend nationally. Around two thirds of Australian respondents plan to increase AI investment in the next financial year, well below the 84 percent recorded globally. Only 12 percent of Australian leaders say generative AI is already transforming their business or industry, compared with 25 percent internationally.
“AI adoption should follow business strategy, not drive it”
In a recent masterclass at Melbourne Business School, Professor Jon Whittle, author of 'AI for Business' and a leading Australian AI expert, took a holistic view of what it takes for businesses to move from experimentation to business-wide adoption. One issue raised was that many organisations are investing in the technology without being clear about what they're trying to achieve. Instead, AI adoption should follow business strategy, not drive it.
For design businesses, the key takeaways below provide a practical way to think about where AI fits, how it should be used and what needs to be in place to support it.
Five takeaways
1. Start with the problem, not the tool
Before investing in AI, ask yourself what problems you're trying to solve across your systems and processes, and how they connect to your strategy. Then ask if AI is the right solution. If it is, concentrate on the few areas where you're likely to get the best return, rather than introducing AI everywhere without knowing why.
2. Faster doesn't always make it better
A poor process with AI added is still a poor process, just faster. Whittle calls this the "efficiency trap," and it can mean missing out on an opportunity to do things differently. AI won't improve the outcome if the underlying process is broken, outdated or ineffective. Review each process first, then decide where AI can help. And if it saves time, decide where that time is reallocated.
3. Be sceptical of the hype
You don't need to become an AI expert, but you do need enough of an understanding to challenge what you're being told. If someone says a tool will save you 30% of your time, improve your profitability, transform your business or that AI search has overtaken SEO, ask what evidence that claim is based on, especially if it doesn't reflect the nuances of your profession.
4. A thinking partner, not the decision maker
Whittle warns against handing over your thinking to AI. He makes a valuable point about tacit knowledge. AI can't access experience that hasn't been documented. That could be how you approach a design problem, handle a client relationship or manage marketing and content creation. If it's not your area of expertise, a generated response may sound convincing even when it's wrong. Instead, use it to challenge your ideas and explore options, but make the important decisions yourself.
5. AI adoption isn't just about technology
This one's the most obvious point, and still the easiest to overlook. The evidence presented suggests that adoption barriers have little to do with the technology itself, and much more to do with human, social and organisational factors. In practice that means someone needs to own how AI is introduced and used across the business, understand where people are ready or unsure, and provide the leadership, training and support needed to do it well. That's a strategic responsibility, not a technical one.
Every business is different
There's no single approach to AI that suits every design business. What works for a competitor may not work for you. The tools you choose, how much you invest and how quickly you get onboard depend on what you want your business to achieve.
That's why strategy needs to come first. AI can help solve an issue, automate a repetitive process or further improve what you're already doing well. But it can't make that decision independent of you, or the people helping you run your business.
AI won't fix your strategy problem. It will just highlight what's missing, faster.