Digital technology solutions are fast becoming a trusted part of site management in the global quarrying and aggregates sector.
The aggregates, asphalt, and ready-mix concrete sectors are entering a period of rapid transformation driven by artificial intelligence (AI) and intensifying pressure to deliver materials in an efficient and sustainable way.
For decades, dispatching was dominated by manual processes and legacy software. But today’s operating environment, marked by complex delivery constraints and regulatory demands, requires a fundamentally new approach.
AI business software provider INFORM showcases how operators who modernise stand to gain operational, financial, and environmental advantages.
Legacy dispatching
It is essential to understand the limitations of the systems still used by many producers. Legacy dispatching tools, often based on spreadsheets or basic heuristics, were not built for the complexity modern planners face. Balancing truck capacities, driver availability, haul distances, loading times, customer windows, and unpredictable traffic requires evaluating millions of scenarios in real time. Legacy tools cannot do this.
As a result, dispatchers are forced to rely on reactive, manual planning.
When conditions change, and they always do, schedulers must recalculate routes, shift orders, and update timelines by hand. This reactive posture leads to inefficiencies, including low truck utilisation, oversized fleets, and inconsistent service quality.
These hidden costs accumulate daily; meanwhile, companies that adopt AI-powered scheduling often see double-digit improvements in loads per truck, on-time performance, and logistics unit cost.
Simulation studies comparing legacy plans with AI-generated ones routinely reveal striking differences in fleet efficiency and cost per tonne delivered. Many organisations hesitate because they fear disruption or underestimate the financial upside. But the biggest risk is the cost of staying with systems that can no longer keep up.
Fortunately, modernising is far simpler than many expect. AI-based planning tools integrate smoothly with existing enterprise resource planning (ERP), scale, telematics, and weighbridge systems. Implementation can be phased and simulation studies allow producers to quantify the benefits before committing. INFORM has said, for most organisations, the business case quickly becomes undeniable.
Planning
Once organisations move beyond legacy tools, the true value of AI becomes clear. Unlike generic AI models, INFORM’s advanced transport optimisation for aggregates logistics is built on operations research, machine learning, and mathematical algorithms engineered specifically for multi-constraint planning.
These systems analyse countless permutations of fleet, order, and routing data long before the first truck leaves the yard. They automate the most intensive aspects of planning while giving dispatchers full visibility and control. Instead of spending the day firefighting, dispatch teams focus on communication, service quality, exception management, and continuous improvement.
According to INFORM, one European producer, producing 580,000m³ of ready-mix concrete annually, achieved nearly 25 per cent productivity gains and saved €2.2 million annually after implementing INFORM’s AI-based dispatch software. That’s nearly a 23 per cent drop in logistics costs. Gains of this magnitude are no longer the exception, according to INFORM.
AI also improves upstream processes. When order takers have real-time visibility into feasible delivery slots, they avoid overpromising and reduce unnecessary strain on the fleet. Rather than replacing planners, AI augments their capabilities, handling computation while humans apply judgment. This combination of mathematical rigour and human expertise produces resilient transport plans that withstand real-world volatility.
The driver shortage
Driver scarcity continues to threaten delivery reliability across Europe and beyond.
The issue is not limited to licensing numbers. Many licensed drivers have left the profession due to difficult working conditions, unbalanced hours, and compensation that is misaligned with the demands of the job. As experienced drivers retire, younger generations are not entering the profession in sufficient numbers.
While autonomous trucks fuel speculation about long-term solutions, they remain years away from widespread use in open-road construction materials logistics.
However, limited autonomy is gaining traction in controlled environments such as mines and quarries, where repetitive haul cycles and defined routes create ideal conditions for automated haulage.
In the near term, the most realistic and impactful tool for mitigating the driver shortage is AI-powered optimisation.
By improving utilisation and reducing empty mileage, AI helps producers deliver the same, or greater, transport volume with fewer active vehicles. Fewer trucks needed means fewer drivers required. This efficiency relieves pressure on the workforce without compromising service reliability.
Importantly, AI also strengthens dispatcher–driver collaboration.
Planning automation frees dispatchers to focus on supporting drivers, thereby improving communication, streamlining operations, and ensuring safer deliveries.
Electrification
Alongside AI, electrification is reshaping the future of aggregates logistics. With the European Union’s strengthened CO2 reduction targets, fleet decarbonisation is shifting from optional to inevitable. Early pilot programs have demonstrated the viability of battery-electric trucks for short-haul aggregate and ready-mix deliveries, especially in urban zones where diesel restrictions are expanding.
Yet electrification introduces a new layer of planning complexity. Unlike diesel trucks, electric vehicles (EVs) require dispatchers to consider:
- Battery range and charging time
- Charger availability and depot grid capacity
- Weather impacts on energy consumption
- Route elevation and load weight
- Time-of-day energy pricing
- These factors directly influence truck selection, scheduling, and routing.
Traditional systems cannot incorporate these variables dynamically, making AI indispensable for managing mixed diesel EV fleets. AI can optimise where EVs should be deployed, when trucks should charge, how many chargers each depot requires, and how charging aligns with delivery cycles.
These insights help producers avoid bottlenecks, minimise energy costs, and plan charging infrastructure strategically.
With electrification accelerating, dispatching will only become more complex. AI is emerging as the critical tool for ensuring sustainability goals can be met without sacrificing profitability or service reliability.
A path forward
Aggregates supply chains are becoming more dynamic and data-driven each year.
INFORM has said AI-powered transport planning, paired with electrification readiness and enhanced human-machine collaboration, offers the most practical and profitable path to navigating this transition.
For producers still relying on outdated dispatching systems, the message is clear: modernisation is no longer a luxury. It is operationally essential.
According to INFORM, the companies that act now will lead the industry into a new era of efficiency, sustainability, and competitive advantage. Those who wait
may discover that the greatest risk is standing still.
Enhanced capabilities
CheckProof has launched its new risk assessment capability through its platform and app. According to the Swedish SaaS company, the integrated addition simplifies and strengthens safety management. The tool enables organisations to replace manual, disconnected safety processes with a fully digital, traceable, mobile-first solution, allowing teams to proactively identify, mitigate, and monitor risks across their operations.
“Many teams still rely on annual paper-based risk assessments. Our platform allows everything, from large-scale project risk assessments to quick ‘Take 5’ checks, to be managed seamlessly in one place,” CheckProof chief executive officer Håkan Holmgren said.
Holmgren said this addition will give teams a faster, more consistent way to identify risks, document controls, and take action before issues escalate.
Key benefits of CheckProof’s risk assessment feature include:
Mobile-first assessments – field teams can quickly identify hazards, assess probability and consequence, and log actions directly from their devices.
Action and accountability – assign responsibilities, set deadlines, and monitor mitigation measures in real-time.
Residual risk evaluation – verify the effectiveness of safety actions with follow-up assessments, ensuring risks are reduced, and progress is fully traceable.
Elevated compliance and documentation – all assessments, actions, and results are digitised, stored, and fully traceable, creating a historical record and enabling quicker responses to high-level risks.
CheckProof said the tool is designed for daily use yet robust enough for complex projects. The feature supports pre-work risk assessments, dynamic risk checks, generic risk assessments, and brief safety moments such as Take 5 or Take 1.
This ensures frontline teams and management have full visibility, enabling proactive safety, compliance, and operational efficiency. AB
