The year 2025 brings new challenges in digital transformation, especially in the manufacturing sector. Is your company ready to meet the pressure associated with AI, cloud, edge computing, and cybersecurity? Learn how to effectively manage digitization, minimize risks, and build a lasting competitive advantage in a dynamically changing world of technology.
Table of contents
Introduction
1. Strategic reflections of a CTO in the face of transformation
2. Main technological challenges in 2025
3. Specifics of challenges in the manufacturing sector
Conclusion
Introduction
The year 2025 brings new dynamics to digital transformation and a range of challenges that we, as a software house cooperating with manufacturing companies, are intensively observing. Companies that fail to keep pace with these changes risk losing flexibility, the ability to innovate, and lasting customer relationships.
McKinsey's research indicates that as many as 90% of enterprises are implementing transformational initiatives, and 72% of them actively use artificial intelligence. In the manufacturing sector, 88% of companies recognize the significant impact of Industry 4.0 technologies on their competitiveness, although the implementation of these solutions still faces certain obstacles. In this article, we share a CTO's perspective on the most important digitalization challenges in 2025 – from the evolving role of the technology leader, through key trends in AI, cloud, edge, and security, to the complexity of systems integration and the specifics of the production environment.
Strategic reflections of a CTO in the face of transformation
The role of the CTO has undergone a significant evolution – from a purely technical expert to a function of strategic importance for the organization. As the CTO of a software house, I currently combine technical knowledge and expertise with responsibility for business aspects. It's no longer just about choosing the optimal tools, but primarily about shaping the company's development direction and translating the potential of technology into tangible benefits for the management board and our clients.
In 2025, a key task becomes the skillful selection of the most relevant trends – such as AI, IoT, edge, and blockchain – through the prism of their real business value. At the same time, effective team management in a dynamically changing environment is essential: supporting innovation, continuous development of competencies, and ensuring a clear and consistent vision. The CTO is also responsible for security and ethical issues – from ensuring compliance with applicable regulations to the responsible implementation of new solutions.
Main technological challenges in 2025
Cloud, automation, artificial intelligence, the Internet of Things (IoT), and edge computing form the foundation of the fourth industrial revolution. For a CTO operating in a smaller company, a deep understanding of the synergies between these technologies and the identification of those that most effectively support the achievement of business goals is crucial.
Artificial intelligence (AI) and machine learning
In 2025, artificial intelligence takes on particular significance. Already, 55% of industrial enterprises actively use generative AI, and another 40% plan to increase their investments in the AI/ML area.
Nevertheless, the implementation of AI-based solutions is associated with specific challenges – especially in the context of data quality, its effective integration, and efficient data management. Almost 70% of companies indicate data quality as the main barrier hindering successful implementations. As a CTO, my task is to ensure a solid data foundation and develop the team's competencies to meet the dynamic development of AI tools.
At the same time, we observe strong pressure to implement solutions that generate a measurable return on investment – especially in areas such as predictive maintenance or automated quality control. However, it is necessary to take action in a prudent and ethical manner, taking into account applicable legal regulations.
Cloud computing and edge computing
Currently, cloud computing is the standard in the IT industry – enterprises are widely migrating their systems to platforms such as AWS, Azure, or GCP, often in a hybrid model. In Poland, approximately 30% of manufacturing companies' operating budgets are allocated to digital technologies, including cloud solutions. For a smaller team, the cloud offers flexibility and scalability without the need to invest in expensive hardware infrastructure, but it also involves challenges – especially in the context of cost management and the complexity of multi-cloud environments.
For smaller projects, cheaper VPS servers can be a beneficial solution, providing significant configuration freedom and sufficient computing power with a limited budget – ideal for MVP deployments, API development, or internal applications, for example.
At the same time, the importance of edge computing is growing – processing data locally, near the machines, which allows for the reduction of delays and the independence of systems from the cloud infrastructure. It is estimated that by 2025, as much as 75% of the data generated by industrial IoT devices will be analyzed at the edge of the network. This trend requires a new approach to system architecture – the CTO must decide which infrastructure elements will remain local (due to speed and security) and which will be moved to the cloud. Maintaining edge infrastructure (such as IoT gateways or local servers) also requires new competencies or establishing cooperation with partners specializing in hardware supply. Nevertheless, the synergy of cloud and edge computing opens up enormous possibilities: fast data analysis, increased system reliability, and real-time process automation.
Cybersecurity and compliance
In the era of digital tranformation and the increasing number of cyberattacks (such as ransomware), application security becomes a matter of fundamental importance – especially in the industrial sector, where security incidents can affect not only data but also the continuity of production processes. Increasingly, the targets of attacks are not only networks or infrastructure but also web applications and APIs, which constitute potential access points to company systems.
As software providers, we must follow the principle of "security by design" – from the design stage to implementation. This includes rigorous access control, thorough validation of input data, effective protection against common vulnerabilities (such as SQL injection or XSS), the use of advanced authentication and access control mechanisms (e.g., RBAC), as well as regular security testing of code and applications (such as SAST and DAST).
New legal regulations, such as the NIS2 directive or the EU AI Act, increase the pressure on compliance issues – requiring transparency of algorithms, protection of personal data, and rapid response to security incidents. For a CTO, this means not only the need to meet formal requirements but also to protect the company's reputation – an application vulnerable to attacks poses a real threat to the client's business.
In practice, this translates into building robust DevSecOps processes, regular code reviews, conducting security audits, and investing in team training in secure programming. Compliance is no longer treated as an add-on – it becomes an integral part of the application lifecycle.
Integration of legacy systems and IoT
The industrial sector is dominated by legacy systems – older ERP systems, databases, or machines that were not designed to work with modern applications. Meanwhile, digitalization requires a seamless exchange of data – from a sensor located in the production hall to a web application accessible in a manager's browser. Integrating these systems can be a complex technical challenge: older devices often do not have open interfaces, use closed communication protocols, or are not connected to the network at all. In such situations, we use IoT gateways, middleware software, and adapters that enable communication with modern applications – often based on standards such as OPC UA or MQTT.
As a software development house, we must ensure that the web application we create can securely retrieve data from existing sources (such as SQL databases or MES/SCADA systems) and publish it without disrupting the ongoing operation of the factory. We often use a phased approach – starting with a pilot and tests, and only then implementing a full migration – to minimize the risk of production downtime.
At the same time, we are observing a dynamic growth in the scale of the Internet of Things (IoT) – thousands of sensors generate huge amounts of data that require effective filtering, secure storage, and real-time analysis. This poses a challenge both for the system architecture and for the applications themselves, which must be able to handle data streams while ensuring stability, scalability, and a high level of security.
Automation and low-code/no-code platforms
Digital transformation is not just about implementing extensive systems but also about automating hundreds of daily processes. The trend of hyperautomation is gaining momentum – companies are striving to streamline all areas of their operations: from production lines to office workflows. RPA (Robotic Process Automation) technologies and low-code/no-code platforms, which enable the rapid creation of simple applications without the need for advanced coding, help in achieving these goals.
It is estimated that by 2025, as much as 70% of new business applications will be created based on the low-code model. For smaller software houses, this represents a significant opportunity – it enables faster prototyping of solutions and relieves programmers from routine tasks.
At the same time, the risk of potential chaos increases: applications created by clients without proper supervision may prove ineffective or pose a security threat (e.g., through data leakage from unauthorized sources). Therefore, we combine the flexibility of low-code platforms with a professional approach: we create dedicated extensions, provide integrations with existing systems, and secure key components (such as access and data) using our own code. We also automate our internal development processes – we use CI/CD tools, containerization, Infrastructure as Code, and AI support in the coding process to deliver applications faster and more securely.
Specifics of challenges in the manufacturing sector
Modern production is based on automated production lines and the tight integration of machines with IT systems. Increasingly, web applications play a key role in this process, supporting production management, real-time data monitoring, and integration with ERP and MES systems.
Discover key technologies supporting digital transformation
Cooperation with manufacturing companies clearly shows that the digital transformation of factories poses different challenges for us than, for example, the digitization of office processes. Below are some specific difficulties faced by the industrial sector in the context of web application development:
Digitization of production through the eyes of web application developers
Unlike companies operating exclusively in the digital space, the industrial sector cannot completely move its operations online. There is always a "last mile" between the IT system and the physical operation of the machine or employee. The implementation of a web application often requires integration with physical devices (e.g., via sensors), equipping employees with tablets or scanners, and sometimes even modifying the existing production process.
An additional challenge is the natural resistance to change – the digitization process can raise concerns about job loss or generate additional responsibilities. Therefore, it is crucial that the implemented application not only meets key business needs but also features intuitive operation, is implemented in stages, and is supported by appropriate user training.
Not all processes need to be digitized simultaneously. The key role of the IT provider is to identify those areas where the implementation of a web application will bring quick and measurable benefits – for example, by implementing a real-time production monitoring system and generating alerts in case of deviations from the norm. Such "quick wins" build trust and pave the way for further digital transformation.
Multi-layered systems in the factory – the challenge of data integration
The factory environment is characterized by a complex architecture consisting of many layers: devices (PLC, CNC), production systems (MES, SCADA), and the IT layer – often distributed, inconsistent, and characterized by data silos. The web applications we create, based for example on the Ruby on Rails framework, do not communicate directly with machines but play a key role in integrating data from various sources and presenting it in a useful form.
We support our clients in building the application layer – overseeing key processes, collecting data from existing systems, and making it available to employees, managers, and external partners. We often have to face the challenge of unifying data from different systems (different formats, units of measurement, naming conventions) and ensure the appropriate context – so that the information reported by the production line is understandable at the management and planning levels.
In this way, we support the digitization process not by directly connecting to machines, but by building a coherent and easily accessible data interface – which truly supports the decision-making process and opens the way for further automation.
Cybersecurity – the foundation of trust in digital solutions in industry
In the manufacturing environment, IT security has significance beyond just data protection – it has a real impact on the continuity of the entire factory's operation. Many OT (Operational Technology) systems are based on outdated technologies that have so far functioned in isolation. However, as digitalization progresses – integration with IT systems, cloud computing, or web applications – a new spectrum of risks emerges.
Although the applications we create usually do not have direct access to machines or controller networks, they often become an integral part of a broader ecosystem that must be properly secured. This includes a responsible approach to authentication, authorization, data encryption, and integration only with secure data sources and APIs.
Sometimes we also support our clients in organizational matters – for example, by educating them on why digitization requires the implementation of security measures of equal importance to traditional physical protection of machines. We help them look at applications not only as a tool but as a key element of a responsible transformation process – where cybersecurity becomes a standard, not an option.
Conclusion
Digital transformation is a complex process that goes far beyond the realm of technology itself. For a CTO, it is crucial to adopt a holistic approach – combining IT knowledge and competencies with a deep understanding of business, people's needs, and the regulatory environment. Although the pace of change – from the dynamic development of AI to the pervasiveness of IoT – may seem overwhelming, it carries enormous potential.
Our experience shows that even traditional manufacturing companies can successfully embark on the path of digitization, provided they do so gradually, with a clearly defined plan and with the support of a competent technology partner. For a software house like ours, the key advantage is agility and high quality of services provided – close cooperation with the client, rapid delivery of valuable solutions, and continuous learning during project implementation. This is how we build lasting trust and truly support the digital transformation process.
The role of the CTO has never been so important – this is the person who should skillfully translate new technologies into concrete business value.
And the transformation itself? It's not a destination, but a journey. The winners will be those who can follow it flexibly, consistently, and with a vision.
