Gain more control: making the shift to Intelligent warehouses

In this article:

• What an Intelligent warehouse is and the key features that define it
• The critical advantages managers can unlock by transitioning to an Intelligent warehouse
• Real-life use cases that show how AI systems are already transforming operations
• What’s next - the path toward fully Adaptive warehouses

The digitalisation journey for the warehouse operations reaches a new stage with the Intelligent warehouse. A key transition happened when warehouses went from Blind to Observable, meaning that fewer activities were handled manually and more technology was introduced, saving managers from significant known and hidden costs.

The next major milestone is represented by the integration of advanced analytics, AI and machine learning (ML) into warehouse workflows. The Intelligent warehouse enables predictive models, automations and optimisations that were not possible before. Artificial intelligence becomes a key component in insight generation, without eliminating human’s role in validating decisions and turning them into action. 

For the first time, warehouses can adopt a truly proactive approach, rather than simply reacting to problems as they occur.

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Key characteristics 

The Intelligent warehouse unlocks a new set of capabilities through its characteristics:

• Data-driven optimisations: Data is collected and analysed in real-time, through autonomous data-gathering robots that feed the information to AI-enhanced central platforms (digital twins). Low-value, time-consuming tasks are streamlined, supporting a more efficient use of resources - for example, AI tools “can unlock 7 to 15 percent additional capacity in warehouse networks by identifying additional daily spare capacity, understanding variability in resource availability, and evaluating opportunities to improve efficiency” according to McKinsey.
• Proactive decision-making: Artificial Intelligence helps warehouses move from being reactive to identifying, anticipating issues before they appear, based on intelligent data and insights. Predictive algorithms are used in the Intelligent warehouse to flag problems early, thus avoiding disruptions, unnecessary costs or even waste.‍
• Human-centric approach: It is important to highlight that even though AI is used increasingly more for data interpretation, humans remain the main decision-makers. AI powered platforms can make recommendations, suggest more efficient workflows, analyse data and compare it with previous scenarios or potential future trends, but managers are the one who make the final call. Technology augments people’s skills and know-how.‍
• Predefined rules and strategies: The algorithms follow predefined policies and parameters. Humans set up rules based on which AI’s recommendations will work, making sure there’s a complete alignment with the company’s business priorities and way of working. AI is just an optimiser, following a certain playbook.

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Main benefits of the Intelligent warehouse

Implementing these new tools yields important benefits for warehouse operators. 

First of all, by leveraging real-time high volumes of data interpreted with the help of AI, accuracy increases. 

Inventory is one of the central business pillars in warehousing, driving huge costs when managed improperly. AI and Machine Learning can be used to look at previous sales, seasonality and real-time market data to make predictions about demand and support managers in making better informed decisions. AI forecasting applied to supply chain management can reduce errors by up to 50%, which can translate into a reduction of lost sales and product unavailability by up to 65%.

Managers can see what’s happening in their units now and also plan for future outcomes. They now have a strategic asset in their stack, and the level of productivity and agility increases.

For example, in the cold supply chain, stock management is more sensitive due to the nature of the products. A global consumer goods company saw a 10% improvement in forecast accuracy and a 12% increase in sales by using tools like AI inventory systems to calculate optimal stock levels during periods when demand usually increases.

Another key advantage is the automation of repetitive, labor-intensive tasks, which frees people to focus on higher-value activities. For instance, autonomous robots can scan inventory more quickly, accurately, and frequently, while also reducing safety risks. The result is richer, real-time data that supports faster, more informed decision-making and contributes to a safer working environment.

Given the workforce shortages and market dynamics, scalability and flexibility are key game changers in the industry today. Using technologies that can be scaled without adding considerable lines of costs is a winning strategy. AI and ML can be adjusted to accommodate any changes, at a local, national or international level for the whole business. 

Intelligence transfer is facilitated across the network as Intelligent warehouses can share real-time insights, AI-driven best practices, and predictive models across the network, creating a collaborative system that learns and improves collectively. These AI-enhanced systems adapt rapidly to changing business needs and market conditions, supporting smart, scalable growth as operations expand. Just as importantly, they continue to learn and refine their performance over time, becoming smarter each day and laying the foundation for the next stage of evolution: the Adaptive warehouse.

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What does it look like in practice

While the benefits of Intelligent warehouses may sound theoretical, many organisations are already seeing tangible results: AI systems are reshaping operations for organisations around the world.

One of the most powerful examples is represented by AI digital twins that act as central points of truth for the entire space. Such a twin is more than a replica - it gathers data from sensing technologies around the warehouse and puts them together in a business-meaningful way. Thus, managers always have an up-to-date overview of stock level, space utilisation or bottlenecks - no more manual counts, or incomplete reports.

NFI, one of North America’s leading supply chain solutions providers, deployed this combination of robots & AI platform and the results speak for themselves:

• Over 80% reduction in manual effort for wall-to-wall and cycle count inventory checks
• Improved space utilisation and service levels
• Team redeployment opportunities unlocked,
• 2-month payback period achieved

Read the full case study here.

Other global operators have also seen results from implementing AI-powered systems in their warehouses. Amazon sees AI and robotics as playing “an important part in supporting our company-wide safety objectives” and estimated that its investment in robotics has led to a 25% reduction in fulfilling orders costs.

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Conclusion

The shift to AI-powered tools is happening fast because of its clear benefits. Reports estimate that the global AI in warehousing market will reach USD 45.12 billion by 2030 and that in 2025, 55% of supply chain leaders plan to increase investments in technology and innovation - with 19% planning to spend over USD 10 million.

Probably one of the most critical factors for successful AI adoption goes beyond costs and it’s more related to building trust. Warehouse staff and managers need to be confident that AI-performed activities are accurate and ethical and that their careers are safe. 

Transparency, consistency and collaboration are key in proving that AI can support growth, bring value and enhance people’s capabilities and free up time for them, not replace them. Organisations need to foster a culture of trust and innovation to lay the foundation for the next milestone. 

As we stated in the beginning of this article, transitioning to an Intelligent warehouse is a pivotal step on the journey towards an adaptive, autonomous warehouse. In this next stage, AI, robotics and AI agents work more independently, making decisions on their own and even executing tasks. 

Read more about the warehouse digitalisation journey from Blind to Adaptive in our most recent whitepaper.