2025: AI as a strategic enabler in omnichannel supply chains
As e-commerce sales continue to expand, with 80% of participants reporting ongoing growth, organizations are increasingly turning to automation and AI-enabled technologies to manage the rising complexity of omnichannel operations.
From inventory allocation across multi-node networks to meeting customer expectations for speed, convenience, and personalization, companies are leveraging AI to enhance forecasting accuracy, optimize inventory, and improve fulfillment operations. This year’s results indicate that AI tools are becoming more deeply embedded in core operational processes, emerging as foundational to how omnichannel supply chain operates and compete.
For the past four years, the Massachusetts Institute of Technology (MIT) Center for Transportation & Logistics (CTL) has conducted an annual study to determine how omnichannel is transforming retail supply chains. This year’s study—based on a survey of 647 supply chain professionals—examined how companies are evolving their omnichannel strategies, managing operational complexity, and leveraging AI-powered tools and emerging technologies to address their most pressing challenges.
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Executive Summary
The Rising Complexity behind eCommerce Growth
As eCommerce matures, omnichannel supply chains are entering a new phase of operational complexity. In our fifth annual survey of 647 supply chain leaders, 81% report ongoing eCommerce growth, and nearly the same proportion are implementing omnichannel distribution strategies, a 10% increase over the previous year. What was once an optional channel strategy has now become a competitive necessity.
The Shift to Profitability
This year’s findings reveal a clear inflection point: companies are moving from building baseline capabilities to optimizing omnichannel profitability. Rising customer expectations for speed and personalization are intensifying cost-to-serve pressures, particularly in inventory positioning and returns management. To manage this, AI-enabled technologies have transitioned from experimental tools to the foundational backbone of the enterprise.
The Operational Backbone
Unlike prior years focused on demand planning, 2025 reveals AI is now deeply embedded in core operations:
- Warehouse & Inventory Management: Optimizing allocation across fragmented networks.
- Transportation & Fulfillment: Enhancing end-to-end visibility and execution.
The Future State
Omnichannel supply chains are evolving from digitally enabled networks into intelligently orchestrated ecosystems. The next wave of competitive differentiation belongs to organizations that embed AI not as an isolated project, but as the primary engine to orchestrate the end-to-end supply chain.
The primary shift in 2025 is clear: the industry is moving from building capabilities to optimizing for profitability.
Key Findings: Impact of eCommerce
Between 2023 and 2024, while consistent growth in sales was perceived, the positive sentiment decreased slightly, aligned with post-pandemic normalization.
During 2025, however, growth perception increased sharply, with 81% of respondents reporting this.
The Trend:
Growth in eCommerce remains the prevailing trend with 81% of respondents reported ongoing sales growth through this channel, driving increased focus on visibility and automation to manage its corresponding operational complexity.
The Profit Squeeze:
As eCommerce matures, with cost-to-serve and returns rising meaningfully, from 38% to 42% and from 33% to 40% year-over-year respectively, the goal moves from expansion to operational efficiency and profitability.
The Reach:
When observing eCommerce impact in the supply chain, distribution and logistics, inventory management, and order fulfillment all stand at 60%, while sustainability jumped from 27% to 48% in a year. Today, eCommerce pressure has reached every corner of the supply chain operations, including sustainability.
Key Findings: Omnichannel Strategy & Implementation
This year’s results show a 10-percentage-point increase in respondents already implementing an omnichannel strategy (rising from 50% to 60% year-over-year), while those declining to implement it dropped from 33% to 22%.
Among those yet to implement a strategy, the leading barrier is a lack of information on omnichannel execution (27%), followed by financial constraints and product type considerations, both at 23%.
The Challenge:
Integration of online and offline remains the number one challenge. Among respondents, 51% cite channel integration as their top strategic challenge, up from 44% from last year, followed closely by fulfillment decisions at 50%.
Pain Points:
No single bottleneck. Pain points are spread across operations. Inventory positioning, demand planning, and logistics costs are all at 53%.
Orchestrating Channels:
Physical stores remain deeply embedded in fulfillment strategies. Click&Collect in-store, curbside, and traditional in-store options each sit at around 54-55%, showing that omnichannel continues to be about orchestrating channels, not replacing physical retail.
Key Findings: Role of AI & Technology in Omnichannel
AI is now embedded across key areas, including customer experience, demand forecasting, warehouse, inventory, and transportation management, among others. It is no longer viewed as a tool to fix individual pain points, but as a broader enabler of core omnichannel operations.
The result is a technologically interconnected system capable of handling higher SKU complexity, faster replenishment, and real-time promises.
AI Expansion:
AI is expanding from targeted tools to a systemic enabler across business operations. Its highest impact is seen in customer experience (64%), demand forecasting (63%), warehouse management (61%), and inventory management (60%). Each function relies on different tools: LLM chat and GenAI copilots lead for customer experience, while Random Forest and Deep Neural Networks lead demand forecasting.
Automation Acceleration:
Investment in automation is accelerating. AMR relevance rose from 50% to 63% within a year, and multi-shuttle relevance jumped from 14% to 56%, showing a shift toward automated, goods-to-person fulfillment models.
Personalization Explosion:
AI-driven personalization continues to expand. Marketing campaigns (69%), product recommendations (66%), and customer segmentation (66%) lead the adoption.
Conclusion: Key Takeaways
AI Impact:
First, AI is evolving from isolated applications to a systemic enabler of end-to-end supply chain orchestration. While early use cases focused on optimizing narrow functions like demand forecasting, enterprises are now embedding AI across the entire value chain to synchronize the omnichannel experience from end to end.
Automation is Critical:
Second, eCommerce continues to introduce significant operational complexity and volatility. In this context, flexible automation technologies such as autonomous mobile robots (AMRs) are becoming critical to adapt to changing demand patterns, while AI provides the intelligence needed to optimize performance across omnichannel supply chains.
Human Intervention:
Finally, competitive advantage will increasingly depend on organizational capabilities. As AI becomes embedded across forecasting, inventory management, and fulfillment, companies must invest in upskilling their workforce to understand, manage and leverage these tools effectively. The ability to combine technology, data, and human expertise will define the next generation of high-performing omnichannel supply chains.
