In this op-ed, 6one5 Retail Consulting CEO Bill Rooney argues that now is the time for Australian fashion brands to bring on artificial intelligence (AI).
In an industry driven by anticipating trends, fashion retailers have been surprisingly slow to adopt one of the most transformative business technologies: artificial intelligence. This reluctance is particularly pronounced in the Australian fashion sector, where a highly centralised, top-down management approach remains the norm.
The Australian fashion industry faces a unique structural challenge in AI adoption. Many retailers in the $20 million to $300 million revenue range operate with traditional decision-making frameworks where strategic initiatives typically require executive approval. While collaborative input is valued, final decisions often rest with a small leadership team – usually including the founder and key financial stakeholders – which can sometimes create bottlenecks for technology-driven innovation.
This established governance model may not always align naturally with the distributed information sharing and cross-functional collaboration that effective AI implementation thrives on. When strategic planning is centralised among a select leadership group, technologies that potentially redistribute decision-making capabilities may require thoughtful change management to avoid natural tension generated by AI structures.
As team members incorporate AI tools into their daily workflows, they can expand their capabilities, focus more time on creative problem-solving, and develop valuable future-facing skills. In an industry evolving as rapidly as fashion retail, proactive engagement with AI technologies is becoming increasingly important for individual career development and organisational competitiveness.
Successful AI implementation
The most damaging misconception about AI implementation is that it belongs exclusively to the IT department. Successful AI transformation requires participation across the organisation, from the sales floor to the C-suite.
Zara demonstrates the power of embracing AI comprehensively. Their implementation of AI-driven inventory management reduced excess stock by 30 per cent and increased full-price sales by 6 per cent. With only 15 per cent of revenue allocated to wages (compared to industry laggards at 25-30 per cent), Zara achieves over $350,000 in sales per employee.
H&M's success stems from its commitment to cross-functional implementation. Rather than creating an isolated AI team, H&M embedded AI specialists within each business function:
- Merchandising teams leverage AI for assortment planning, reducing markdowns by 40 per cent
- Store operations use AI to optimise staffing and layout, increasing conversion rates by 3 per cent
- Design teams utilise trend prediction algorithms, accelerating concept-to-store timelines by 25 per cent
Stitch Fix offers a compelling example of how AI can transform organisational culture by democratising data access, creating cross-functional teams, and establishing clear metrics to measure AI impact on customer satisfaction. Their stylists can effectively serve 5x more customers than traditional retail associates.
Australian success stories
The majority of Australian retailers have legacy systems that have limited AI integration capabilities. Despite this challenge, many have found success by adopting a ‘layer-on approach’ for immediate gains:
- Cotton On Group: While maintaining their core ERP system, Cotton On implemented specialised AI forecasting and allocation tools, reducing excess inventory by approximately 12 per cent across their Australian operations.
- Premier Retail (Just Group): The parent company of brands like Just Jeans and Jay Jays implemented a middleware solution to connect their legacy systems with modern AI inventory tools, delivering a 15 per cent improvement in full-price sell-through.
- City Beach: Successfully implemented an AI-powered demand forecasting solution that works alongside their existing systems, resulting in a 24 per cent reduction in markdowns.
- Retail Apparel Group (RAG): Implemented a third-party AI markdown optimisation solution while maintaining their legacy ERP, delivering an estimated $3.2 million in additional margin.
These examples demonstrate that Australian fashion retailers can achieve significant results using the layered approach to AI implementation, even when constrained by limited ERP capabilities.
Who should drive AI implementation?
This is a crucial question that gets at the heart of successful AI transformation.
While IT certainly plays a critical technical role, AI implementation that truly drives innovation should be primarily a leadership function rather than solely an IT initiative. Here's why:
- Strategic alignment - AI implementation needs to align with business objectives and organisational vision, which requires leadership direction to ensure technology serves strategic goals.
- Cross-functional impact - AI affects nearly every department and function, not just technology. Leadership has the broader perspective and authority to coordinate across silos.
- Culture change - Creating an innovative AI culture requires shifting mindsets, behaviours, and processes throughout the organisation - changes that need leadership sponsorship and modelling.
- Resource allocation - Leadership makes the decisions about budget, staffing, and prioritisation that determine whether AI initiatives get the resources needed to succeed.
- Risk management - The risks of AI (ethical, legal, reputational) extend far beyond technical considerations and require leadership oversight.
That said, IT should serve as a critical partner in the implementation, providing technical expertise, managing infrastructure, and advising on data architecture. The most effective model is a partnership through a dedicated cross-functional team that brings together business, technology, and data science perspectives.
Starting your AI fashion journey
The path forward doesn't require massive immediate investment or organisational restructuring:
- Start with high-impact, low-disruption applications - Inventory forecasting typically delivers immediate ROI while building organisational confidence.
- Focus on augmentation, not replacement - Frame every AI initiative as enhancing human capabilities rather than substituting them.
- Democratise AI tools - Everyone in the business should have access to AI tools and use them daily. Create reward systems to recognise productivity improvements.
For Australian founder-centric fashion retailers, embracing AI requires more than technological investment – it requires cultural change. The technology gap isn't just about competitive positioning – it's about survival. While AI implementation requires investment, the cost of inaction is far greater.
The question isn't whether AI will transform fashion retail – it's whether your organisation will lead that transformation or be transformed by it. The time to choose is now.
When is the best time to implement AI?
The timing question has a simple answer: now. Remember, it took just four years for the horse and buggy to be replaced by automobiles once production scaled. In today's digital landscape, market shifts happen exponentially faster. You're not being left behind by competitors; you're being outpaced by technology itself.