Current Situation Analysis: How Industry and Logistics Work with Digitalisation

Supply Chain Under Pressure

Swedish industry has gone from a relatively stable external environment to a geopolitical reality with several simultaneous disruptions. The war in Ukraine, unrest in the Red Sea, tariff escalations, and expanded sanction regimes have led to material shortages, delivery delays, and high cost pressures.

For logistics operators, the situation is particularly palpable. They are not in a vulnerable supply chain; they are the supply chain. A port conflict or rerouted route directly affects their own operations. Add volatile energy prices in a fuel-driven industry, and the conclusion is clear: every disruption costs more today than five years ago.

Cyber Threats Grow and Manufacturing Most Vulnerable

Alongside the geopolitical pressure, the digital threat landscape is expanding. According to IBM, the manufacturing industry is the most vulnerable sector globally. Attacks are directed not only at traditional IT but also at OT environments: production lines, control systems, and the technology that keeps operations running.

The logistics sector is also exposed. The number of integrations with customers, partners, customs systems, and transport platforms creates attack surfaces that grow in pace with digitalisation.

New EU Regulations Drive Digitalisation in Industry and Logistics

The EU has recognised that cyberattacks are about more than economics; they concern critical infrastructure and societal security. A series of regulations are now tightening requirements for both industry and logistics:

• NIS2 places stricter demands on risk management, incident reporting, and management responsibility. Large parts of industry and logistics are covered.

• Cyber Resilience Act requires that products with digital components must be secure throughout their entire lifecycle.
• EU’s Machinery Regulation (replacing the Machinery Directive 2027) includes cybersecurity as part of machine safety, introducing a whole new dimension for industrial companies.
• EMDS, ICS2 and CSRD scope 3 impose further data requirements throughout the transport chain, particularly for the logistics sector.

The regulations drive digitalisation forward but require high digital maturity. The question is not whether to act, but whether to do so proactively and strategically, or reactively and expensively.

Customer expectations drive change

Expectations of real-time tracking, fast deliveries and full transparency are now seeping through the entire value chain. Can you show where the goods are? What does your sustainability data look like? Do your systems communicate with the customer’s? If the answer is no, you risk being replaced. Not because the service is poor, but because the digital capacity is insufficient.

Outdated systems hinder digital development

If external pressure creates urgency, internal challenges determine how quickly the organisation can act. Many industrial companies are stuck with ERP and production systems implemented 10–20 years ago. They work, but they are difficult to integrate, expensive to upgrade and create bottlenecks.

In logistics, the picture is even more fragmented. TMS, WMS, booking portals and customs systems from various suppliers and eras have created a large integration debt. There is also a growing platform dependency here, where actors risk losing control over data and terms.

Skills shortage complicates the transition

Recruiting IT expertise is difficult in most industries, but in industry and logistics there is an additional need for people who understand both IT and OT, who can navigate control systems and data security, or flow optimisation and system architecture. That expertise is rare.

Smarter investments – not more

AI, machine learning, APIs and cloud services are prioritised highest in the sector's investment plans. This shows an understanding that the IT architecture of the future is built on connected, scalable and intelligent systems. The high prioritisation of APIs confirms the need to connect fragmented systems. The investment in Data Lake and Lakehouse shows the awareness that AI requires a developed data platform.

But if the AI ambition is high, what does actual AI maturity look like? The gap between ambition and reality, between prioritising AI and actually having the data platform, expertise and organisation in place, is a real risk. The companies that address the gap methodically build a competitiveness that lasts.

The solution is not more investments but smarter ones. Those that both streamline and build digital capacity, in a way that meets customer requirements, regulations and threat landscape simultaneously.