Softeon’s Senior Solutions Consultant Eric Maldonado and Tryon Solutions’ VP of Sales James Ward teamed up with Chartered Institute of Logistics & Transport (CILT) to deliver a webinar, Growth Through AI and Automation in the Warehouse.
Warehouses are operating under unprecedented pressure. Rising labor costs, tightening service-level expectations, and ongoing disruption are forcing organizations to rethink how they run their operations. Incremental optimization is no longer enough.
In this webinar on 21 January, industry experts from Softeon and Tryon Solutions explored how AI-driven decisioning and modern automation are being used today as practical tools to improve resilience, scalability, and workforce effectiveness across warehouse operations.
Eric and James brought complementary perspectives spanning warehouse software, systems integration, and automation strategy.
From AI Buzzwords to Warehouse Reality
James opened the session by grounding the conversation in how far AI has come. While early AI applications focused on image recognition and recommendations, today’s AI capabilities are far more advanced.
Modern AI can:
- Analyze and summarize complex operational data
- Generate insights in real time
- Support autonomous decision-making through “agentic” systems
- Learn patterns and adapt as conditions change
AI is no longer theoretical for supply chains. It’s operational.
James also introduced the concept of agentic AI, where multiple AI agents work together. For example, this would be slotting, labour, and execution agents address warehouse challenges holistically rather than in isolation.
Where Generative AI is Delivering Value Today
Eric addressed one of the most common questions warehouse leaders ask: What does generative AI actually do inside a warehouse?
The answer: It accelerates human decision-making.
Rather than replacing people, generative AI focuses on the three areas where warehouse teams spend most of their time:
1. Training and Onboarding
With tools like SAIL Assist (Softeon AI Layer), users can ask natural-language questions directly within the WMS, such as:
- “How do I receive a damaged pallet?”
- “Why did this wave fail?”
Instead of relying on static manuals or tribal knowledge, the AI responds using live system configurations and workflows, getting new hires productive faster and reducing dependency on experts.
2. Exception Handling
When something goes wrong (i.e., a robot stops, an order misses cutoff, or allocation fails) AI can:
- Explain what happened in plain language
- Summarize root causes
- Recommend next best actions
Supervisors no longer need to dig through logs and dashboards to understand issues mid-shift.
3. Analytics and Insights
AI turns warehouse data into usable answers. Managers can ask:
- “Why did pick productivity drop yesterday?”
- “Which zones are causing congestion this week?”
The result is narrative, contextual insight backed by real-time data, not just charts.
AI, Forecasting, and Dynamic Labor Planning
Labor remains the single largest cost in most warehouses, and Eric explained how AI is changing both forecasting and labour planning.
Traditional approaches rely on historical averages and static schedules. AI-driven models, however, ingest far richer signals: SKU behavior, promotions, cancellations, returns, and even external factors like weather.
This enables:
- More granular demand forecasts
- Hour-by-hour, zone-level labor planning
- Real-time adjustments during the shift
Instead of firefighting, operations can proactively rebalance work, redeploy cross-trained staff, and avoid unnecessary overtime—improving both cost control and employee experience.
Is Automation Still a Differentiator?
James addressed whether warehouse automation is becoming table stakes. His view: automation has evolved.
Older automation systems were efficient but rigid, designed for a single purpose and difficult to adapt as business needs changed. Today’s automation is:
- Modular and extensible
- Often robotics and goods-to-person–based
- Designed to work alongside humans through co-bots and AMRs
- Integrated through modern APIs rather than brittle connections
This flexibility allows warehouses to scale and adapt without locking themselves into outdated designs.
AI-Driven Automation: Beyond Cost Reduction
Eric challenged the idea that automation is only about reducing labor. While cost savings matter, the real value shows up on the revenue side:
- Higher service levels→ better customer retention and contract renewals
- Increased throughput → more volume without adding buildings or headcount
- Fewer revenue leaks → fewer stockouts, mis-picks, and missed cutoffs
As Eric put it: Cost reduction improves margin. Revenue growth improves valuation. AI-driven warehouse automation delivers both.
Deciding What To Automate First
To maximize ROI, Eric emphasized starting with constraints, not technology. The most successful projects focus on:
- Where the operation breaks under pressure
- Where labor is most expensive or unstable
- Where variability causes the most disruption
By using AI to analyze live WMS, WES, robotics, and labour data, organizations can target automation where it delivers the greatest business impact.
Human-Robot Collaboration Safety
James addressed concerns about robots working alongside people. With modern technologies like LIDAR-based perception and AI-driven environment interpretation, robots can safely slow down or stop when encountering obstacles.
While incidents do occur, they are typically linked to poor training or unsafe practices, not the technology itself. When implemented correctly, co-bots and AMRs are already working safely in many warehouses today.
The Power of AI and Automation in the Warehouse
AI and automation are no longer future-state initiatives. They are practical, operational tools that help warehouses scale, adapt, and compete in an increasingly demanding environment.
When applied thoughtfully, with the right data, clear objectives, and a focus on people, AI turns the warehouse from a cost center into a true competitive advantage.
