The promise of AI in supply chain is very compelling and to transform this potential into real value, people must be able to understand it, trust it, and effectively use it. That’s what makes usability a critical enabler of AI adoption and value.
As AI becomes more embedded across supply chain planning, usability and explainability have become inseparable. A solution may have powerful algorithms and advanced functionality, but if teams cannot understand why an AI-generated recommendation has been made, they may hesitate to act on it.
Conversely, when AI is intuitive, transparent, and easy to interact with, it becomes a true partner in decision-making.
Usability Is More Than an Intuitive Interface
Usability is often associated with the ability to navigate software; how intuitive and configurable it is, and how easy it is for users to accomplish tasks. These each remain essential; however, in an AI-enabled planning environment, usability goes deeper. It’s also about making advanced capabilities accessible and understandable to the people using them.
This is particularly important as supply chains adopt innovations such as probabilistic planning, Multi-Echelon Inventory Optimization (MEIO), agentic AI, and more. Teams need to really understand the outputs to make decisions with confidence, which is why explainable AI is a critical part of usability.
Explainability helps users understand the context, reasoning, and factors behind recommendations, turning complexity into actionable insights.
Partner with a Top Vendor Consistently Recognized for Usability
The importance of usability is reflected in independent industry recognition. John Galt Solutions has been named a Leader in the 2026 Nucleus Research Enterprise Supply Chain Planning Technology Value Matrix, marking the sixth consecutive year that Nucleus Research has recognized the company as a Leader.
Notably, the Atlas Planning Platform once again achieved the highest placement in Usability.
Independent peer reviews and customer feedback can also provide valuable insights into how a solution performs in real-world environments. At John Galt Solutions, customer feedback reinforces this focus
We are proud to have earned an overall peer rating of 4.9 out of 5, including strong marks for capabilities, ease of use, deployment, and customer service.
As one of our customers said:
“My overall experience with the Atlas Planning suite has been extremely positive. The ease of use provides low barriers of entry for a new user. The system is intuitive, but not complicated. It's very comprehensive and we are able to understand exactly what is happening at a detailed level.” - Manager of Forecasting & Delivery Optimization, Consumer Goods
Making AI More Usable Through Explainability
The Atlas Planning Platform combines AI, machine learning, intelligent workflows, and explainable recommendations together in an end-to-end supply chain planning platform designed to keep planners engaged in the decision-making process.
One important aspect of usability is the ability to interact with AI using natural language. Instead of requiring users to understand complex models, conversational interaction makes it easier to explore information, ask questions, and understand recommendations and insights.
This makes advanced capabilities more approachable for a broader range of users. For example, Galt AI, John Galt Solutions’ agentic AI platform, helps make MEIO more understandable and actionable. MEIO can deliver significant value by balancing inventory across multi-node networks, but the complexity of optimizing inventory across finished goods, components, raw materials, and locations can make the process difficult to adopt. With contextual, conversational explanations, supply chain teams can better understand inventory recommendations, why those recommendations have been made, and where opportunities and risks may exist.
More than an AI-generated answer, Galt AI delivers guidance with the context needed to understand and evaluate it.
The same principle applies to ensemble forecasting, where multiple forecasting models are combined to generate a prediction. When different models identify different patterns, peaks, and valleys, planners can understandably question why a particular outcome has been prioritized.
Through GenAI explainability techniques, Atlas helps reveal the logic behind ensemble outcomes, providing greater clarity around the patterns, trends, and models contributing to the forecast, creating a more transparent relationship between teams and technology.
Trust is fundamental to usability. When users understand the technology and its outputs, they are more likely to use it. This leads to positive results and increased confidence, driving further adoption and enabling organizations to get more value from their investment.
Keeping Humans in the Loop
Explainability also plays a critical role as supply chains move toward agentic AI. AI agents can process vast amounts of demand and supply data, identify anomalies and trends, run experiments, and generate recommendations. But the goal is not to remove humans from the decision-making process.
Atlas emphasizes human-in-the-loop controls, allowing agents to present explainable recommendations that planners can review, approve, or override before actions are executed.
This creates a balance between machine speed and human judgment. AI can take on more of the analytical workload while people retain oversight of important decisions.
In the words of other Atlas customers:
“Very easy to configure. There are so many options and ways of working. The ability to create hierarchies and organize data is very important. Ease of use is a key feature. Using across the global supply chain and global locations. The application supports multiple business units and processes within our organization.” - Supply Chain Planning Analyst, Sporting Goods
“The product is extremely easy to use and highly configurable for specific business needs. Additionally, we are able to leverage the automation features to achieve dynamic results without the need for ongoing manual intervention or maintenance.” - Director of Delivery Operations & Demand Planning in Consumer Goods
Democratizing AI Through Better Usability
From natural-language interaction and contextual insights to explainable recommendations and human-in-the-loop controls, the Atlas Planning Platform embeds the principles of usability, explainability and trust into the core of AI-powered supply chain planning software.
Let us show you how the Atlas Planning Platform empowers companies like yours with intuitive, powerful AI capabilities to elevate your planning strategies.
