The fashion industry is a fickle business.
Constantly changing aesthetic trends, volatile customer preferences and global economic shifts mean that staying relevant requires more than just a great garment and creative intuition.
In many ways, sustainability, customer satisfaction and profitability depend on flexible, resilient supply chains. Unfortunately, many supply chains are breaking under the weight of modern market demands and novel logistical and geopolitical challenges. Often, the result is a costly cycle of inaccurate forecasts, lost sales and excess inventory that ends up in landfills.
These are costly problems that directly influence profit potential. According to McKinsey & Company’s latest fashion industry report, 46% of fashion executives expect conditions to worsen in 2026.
Vertical AI and Machine Learning (ML) can help solve these problems. McKinsey’s research found that 35% of executives are already using this technology for online customer service, image creation, copywriting, consumer search or product discovery.
To make 2026 profitable, productive and competitive, the fashion industry must leverage Vertical AI to break the cycle of inaccurate forecasts, lost sales and excess inventory that ends up in landfills.
Here’s how.
- Anticipate the future rather than reacting to it.
The old adage says that failing to plan is planning to fail. In 2026, however, planning based on the past is a recipe for obsolescence. The era of long-lead planning based purely on last year’s performance is over.To remain profitable, retailers must identify shifts in consumer sentiment before they manifest as missed opportunities. Put differently, the fashion industry needs to look ahead, not behind, for the critical insights that solve this problem.
For example, predictive AI models can ingest large datasets, aggregating and analyzing them in real time to incorporate everything from social media sentiment to global search trends, providing a clearer, up-to-date picture of what’s up ahead.
Logility’s research found that 38% of fashion brands lack accurate demand forecasting. Real-time data that anticipates the future empowers brands to implement a more agile, forward-looking supply chain strategy that more accurately forecasts demand.
- Optimize inventory and replenishment.
Your inventory can be a source of excess cost or a competitive advantage. Too often, inefficient inventory management remains a primary driver of margin erosion.From raw materials to the final product, Vertical AI capabilities optimize every link in the supply chain. It navigates the many interconnected parts of the production supply chain, ensuring inventory levels are precisely calibrated, regardless of how intricate the network is.
The result is the right balance between adequate supply and overstock. Consequently, fashion brands can calculate optimal inventory levels and test various “what if” scenarios that can affect supply and demand.
This is great news for fashion retailers working furiously to keep up with shoppers’ tastes and expectations while also accounting for geopolitical conflicts, raw material constraints and, most recently, shifting tariff regimes.
- Leverage Vertical AI to manage dynamic digital twins.
The most sophisticated application of Vertical AI in the supply chain is the creation and management of a dynamic digital twin. This virtual representation of the physical supply chain allows leaders to simulate scenarios and test their impact on supply chain readiness and operational resilience.In practice, this means that fashion brands can identify and assess scenarios to uncover hidden vulnerabilities and mitigate risks in real time. For instance, they could use a digital twin to evaluate the impact of port closures or sudden spikes in raw material costs before they happen.
Apparel-specific intelligence captures seasons, styles and real-world workflows, providing a natural language interface to generate actionable recommendations, deploy AI agents to compress tasks from days to seconds, power role-based AI workspaces for context-aware insights and automate routine processes so decisions are faster, margins are safer and teams stay in sync.
When implemented and leveraged effectively, a digital twin helps brands produce only what the market requires and deliver the right product to the right consumer at the right time.
Securing a Competitive Edge in 2026
Fashion may be a fickle business, but the potential for profitability and impact is greater than ever for those who embrace the digital evolution. This year, existing challenges, such as rapidly changing consumer preferences, will continue to pressure fashion brands. At the same time, new obstacles, such as geopolitical conflicts and tariffs, will demand a new level of strategic agility.
Failure isn’t inevitable.
Vertical AI and machine learning offer the opportunity to reimagine supply chain planning and execution across the fashion industry value chain.
In 2026, the organizations that successfully navigate supply chain volatility will outpace the competition by 70%. They are poised to outgrow their competitors’ profit margins by 6%, create plans at 30% of the cost, and achieve 20% higher forecast accuracy.
That’s why the next move is to just get started. Experiment, learn, adapt and scale the innovations that will define your brand’s future.
Jonathan Doller is Senior Business Consultant at Logility, an Aptean Company. He has been part of the Logility team for over seven years and has spent over 25 years working with various supply chain and retail planning solutions from both an implementation and presales perspective. Doller is currently part of the Business Consulting team, helping organizations by aligning Logility’s solutions with complex supply chain challenges and demonstrating value while embracing the role of “trusted advisor.” Over the years, he has delivered industry webinars, represented the organization at major supply chain conferences and co-authored various articles and white papers focused on modern supply chain challenges and solutions.
