The year 2026 is fast approaching and with it a series of developments that will have a lasting impact on the IT landscape. The speed at which technology is changing requires continuous adaptation and strategic foresight. Companies are faced with the need to prepare their infrastructures, processes and employees for the challenges ahead. This text highlights some of the key trends and the associated solutions.<\/p>\n
Artificial intelligence (AI) is no longer a futuristic concept, but an operational reality that increasingly controls business processes and influences decisions. This development brings with it both opportunities and considerable challenges.<\/p>\n
The integration of AI into operational tasks means that algorithms and machine learning are increasingly taking over tasks that previously required human intervention. This ranges from automating routine tasks to supporting complex decision-making processes. AI systems can analyse data in real time, recognise patterns and make recommendations or even act autonomously. For example, AI-controlled systems can be used to optimise supply chains, for predictive maintenance of systems or for personalised customer contact. The ability to control and improve operational processes is a core aspect of operational intelligence, which is fuelled by the fusion of operational data and analytical findings. The aim here is not only to understand what is happening, but also why it is happening and to respond proactively.<\/p>\n
With the growing autonomy of AI systems, the need for robust governance is coming to the fore. This concerns the clear definition of responsibilities, ensuring compliance with legal regulations and establishing processes for monitoring and controlling AI decisions. Transparency is a decisive factor here. It must be possible to understand how an AI arrived at a particular decision in order to build trust and identify sources of error. The ethical evaluation of AI applications is also becoming increasingly important. Discrimination through biased training data, data protection concerns or the potential misuse of AI technologies are ethical dilemmas that need to be addressed proactively. The development of AI ethics guidelines and the implementation of mechanisms to recognise and avoid bias are essential.<\/p>\n
The introduction of AI is also creating new job profiles. Roles such as \u201eAI auditors\u201c, who check the fairness, security and compliance of AI systems, will become increasingly important. Specialists who can orchestrate and integrate AI systems will also be in demand. This process of orchestration, i.e. the interaction of different AI components and their integration into existing IT landscapes, is a complex task. There is a considerable shortage of skilled labour here. There is not only a lack of developers with AI expertise, but also managers and technical experts who are able to develop and implement AI strategies and organise the operational changes. The training and development of existing employees and the recruitment of new talent are therefore crucial.<\/p>\n
The threat landscape in the field of IT security is evolving rapidly. Attackers are becoming increasingly sophisticated and the complexity of digital systems offers numerous gateways. A reactive security model that focuses solely on prevention is no longer sufficient.<\/p>\n
The concept of \u201epreemptive security\u201c (proactive security) aims to identify and neutralise threats before they can cause damage. This requires the use of advanced analysis tools that recognise anomalies in network traffic, as well as continuous monitoring and threat intelligence. As a result, the \u201ezero trust\u201c model is becoming increasingly important. Instead of trusting systems and users by default, every access point - whether internal or external - is rigorously checked and authenticated. This means that any attempt to access data or applications is categorised as potentially dangerous and subjected to strict verification. This protects against lateral movement, i.e. the spread of an attacker within the network after they have gained an initial entry point.<\/p>\n
The development of quantum computers poses a long-term threat to current encryption methods. Quantum computers could be able to break many of the encryption algorithms used today. Therefore, the research and implementation of \u201epost-quantum cryptography\u201c (PQC) is becoming increasingly urgent. These new cryptographic methods should also be resistant to attacks by quantum computers. At the same time, the focus is shifting from pure prevention to \u201eresilience\u201c. Resilience means the ability of a system to quickly resume normal operation after an attack or failure. This includes not only technical aspects such as backups and recovery plans, but also organisational measures and the ability to react flexibly to unexpected events. Gartner predicts that millions of security breaches could occur by 2030, emphasising the need for robust security strategies and resilient systems. Protecting against this flood of vulnerabilities requires a holistic approach that combines proactive defence with rapid recovery.<\/p>\n
The sheer volume and complexity of cyber threats in 2026 presents one of the biggest challenges. From ransomware that paralyses companies to state-sponsored cyberattacks and sophisticated phishing campaigns that exploit human weaknesses, the attack surface is enormous. Traditional firewalls and antivirus programmes are often not enough to protect against new types of malware and advanced persistent threats (APTs).<\/p>\n
It is important to recognise that the human element is often one of the biggest vulnerabilities in IT security. Social engineering attacks aimed at tricking employees into disclosing confidential information or running malicious software are ubiquitous. Therefore, continuous cyber threat awareness training and the promotion of a security-first culture are essential. Employees must learn to recognise suspicious emails, use strong passwords and understand the importance of multi-factor authentication.<\/p>\n
Given the sheer volume of security incidents and the speed at which attacks can occur, automation is becoming increasingly important in the field of IT security. Security Orchestration, Automation, and Response (SOAR) platforms help to automate recurring security tasks and accelerate incident response. AI-powered analytics tools can help analyse large amounts of log data and identify potentially malicious activity that human analysts might miss. This allows security teams to focus on more complex threats instead of getting lost in an endless stream of alerts.<\/p>\n
-The use of digital services will continue to increase, but the way in which companies strategically utilise these services will continue to evolve. Issues of digital sovereignty, i.e. control over one's own data and infrastructure, will become increasingly important.<\/p>\n
The trend is clearly moving towards hybrid and multi-cloud architectures. Companies no longer rely on a single cloud platform, but instead distribute their workloads and data across different providers (public cloud, private cloud) while keeping parts of their infrastructure on site (on-premises). This enables greater flexibility, cost efficiency and optimisation of performance for specific applications. Hybrid architectures offer the opportunity to combine the scalability of the public cloud with the control and security of on-premises solutions. Multi-cloud strategies make it possible to reduce dependencies on individual providers and benefit from the specific strengths of different cloud services.<\/p>\n
The \u201egeopatriation\u201c of workloads refers to the need to store and process certain data and applications in geographically defined regions to fulfil regulatory or latency requirements. Driven by data protection laws and the desire for more control over sensitive data, companies are increasingly opting to move workloads to specific countries or regions. At the same time, edge computing is becoming increasingly important. This involves moving computing power and data storage closer to the source of data generation, for example to IoT devices or local networks. This reduces latency, saves bandwidth and enables faster processing of real-time data, which is crucial for applications such as autonomous driving or industrial automation.<\/p>\n
The need to fulfil compliance requirements and ensure greater control over data is leading to the development of \u201esovereign clouds\u201c. These are cloud environments that are either operated by national governments or by providers that fulfil strict criteria regarding data storage and processing on national territory. These sovereign clouds are designed to enable organisations to keep their data within defined legal and geographical boundaries. One of the biggest challenges in this context is orchestration. Managing and integrating workloads across different cloud environments, geographies and local infrastructures requires sophisticated orchestration tools and a clear strategy. The complexity of managing a heterogeneous IT landscape consisting of public clouds, private clouds and edge resources requires specialised tools and expertise to ensure efficiency and security.<\/p>\n
The way we work has changed fundamentally. The modern workplace is no longer just a physical office space, but a digital environment that promotes productivity, collaboration and flexibility.<\/p>\n
The focus is on increasing productivity and promoting the acceptance of new technologies. Employees need to be able to work effectively with digital tools and feel comfortable with the changes. This requires not only the provision of the right technology, but also a culture that supports change. In particular, training employees to be able to collaborate with AI-supported tools is becoming increasingly important. AI can act as a co-pilot, automate tasks or help to analyse information. Employees need to learn how to use these tools effectively to improve their own work and open up new opportunities.<\/p>\n
A common challenge for IT teams in the context of the modern workplace is project overload. The introduction of new technologies, the migration of systems and the continuous adaptation to changing requirements often lead to an overload of available resources. This can lead to delays, quality problems and general frustration. At the same time, effective knowledge management is crucial. If knowledge is only housed in the heads of individual employees, bottlenecks and dependency on key personnel arise. The systematic recording, documentation and transfer of knowledge within IT teams is therefore essential in order to maintain operational processes and continuously expand the knowledge base.<\/p>\n
The flexibility offered by hybrid working models (a combination of office and remote working) has become an important factor in employee satisfaction. Organisations need to ensure that their IT infrastructure and collaboration tools are designed to support this flexibility. This includes providing secure access to company resources from any location, implementing tools for virtual meetings and fostering a culture of communication that works across distances.<\/p>\n
The Modern Workplace requires not only technical adjustments, but also a cultural transformation. Managers must promote a culture of trust and personal responsibility and be prepared to rethink traditional hierarchies. Creating an inclusive working environment in which all employees feel valued and supported is crucial to success. This also includes taking into account the individual needs and preferences of employees with regard to working hours and work organisation, always taking into account organisational necessities.<\/p>\n
<\/p>\n
| The challenge<\/th>\n | Description of the<\/th>\n | Expected influence<\/th>\n | Priority<\/th>\n<\/tr>\n<\/thead>\n |
|---|---|---|---|
| Artificial intelligence (AI) integration<\/td>\n | Implementation of AI technologies for automation and decision-making<\/td>\n | High<\/td>\n | Very high<\/td>\n<\/tr>\n |
| Cybersecurity<\/td>\n | Protection against increasingly complex cyberattacks and data breaches<\/td>\n | Very high<\/td>\n | Very high<\/td>\n<\/tr>\n |
| Cloud migration<\/td>\n | Shifting IT infrastructures to the cloud to increase flexibility<\/td>\n | Medium<\/td>\n | High<\/td>\n<\/tr>\n |
| Shortage of skilled labour<\/td>\n | Shortage of qualified IT specialists and experts<\/td>\n | High<\/td>\n | High<\/td>\n<\/tr>\n |
| Sustainability and green IT<\/td>\n | Reduction of energy consumption and environmentally friendly IT solutions<\/td>\n | Medium<\/td>\n | Medium<\/td>\n<\/tr>\n |
| Digital transformation<\/td>\n | Implementation of new digital business models and processes<\/td>\n | Very high<\/td>\n | Very high<\/td>\n<\/tr>\n |
| Regulatory requirements<\/td>\n | Adherence to data protection and compliance regulations<\/td>\n | High<\/td>\n | High<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n The underlying IT infrastructure forms the foundation for all digital endeavours. The development towards AI-native platforms and increasing automation are key trends.<\/p>\n AI-native platforms and hybrid infrastructures<\/h3>\nAI-native platforms are designed to efficiently process and scale AI workloads. They integrate specialised hardware such as GPUs and TPUs and provide an optimised software environment for machine learning and deep learning. These platforms are a key component for organisations looking to deploy AI at scale. At the same time, the infrastructure will be increasingly hybrid, with cloud environments, on-premises data centres and edge computing resources coexisting. This hybrid nature allows organisations to deploy resources where they are most efficient, whether for training purposes in the cloud, for critical applications on-premises or for real-time processing at the edge.<\/p>\n Scalable cryptography modernisation and increasing expenditure<\/h3>\nIn view of the threat posed by quantum computers, the modernisation of cryptography is an ongoing task. This means the gradual introduction of post-quantum cryptography algorithms and the adaptation of existing systems. This must be done in a scalable manner in order to manage the changeover across entire IT landscapes. Investment in AI infrastructure continues to increase. Companies are recognising the strategic value of AI and are prepared to invest considerable resources in the necessary hardware, software and specialist personnel. This expenditure is not just a reaction to current trends, but a strategic investment in future viability.<\/p>\n The importance of automation in infrastructure management<\/h4>\nThe complexity of modern hybrid infrastructures makes automation an indispensable tool. Infrastructure as Code (IaC) and advanced orchestration tools make it possible to provision, configure and manage infrastructure resources in an automated way. This reduces manual errors, speeds up deployment and improves efficiency. Automated processes can also be used for monitoring, scaling and patch management of the infrastructure, which reduces operating costs and increases reliability.<\/p>\n The impact on the sustainability goal<\/h4>\nWith increasing digitalisation and the use of AI, the energy consumption of data centres is also growing. The IT industry therefore faces the challenge of developing sustainable infrastructures. This includes the use of energy-efficient hardware, the optimisation of cooling systems and the use of renewable energy sources. Automation can also play a role here by optimising the utilisation of resources and reducing unnecessary energy consumption. The balance between digital transformation and environmental responsibility will be an increasingly important facet of IT strategy.<\/p>","protected":false},"excerpt":{"rendered":" Das Jahr 2026 schreitet voran und mit ihm eine Reihe von Entwicklungen, die die IT-Landschaft nachhaltig pr\u00e4gen werden. Die Geschwindigkeit, mit der sich Technologie ver\u00e4ndert, erfordert kontinuierliche Anpassung und strategische Weitsicht. Unternehmen stehen vor der Notwendigkeit, ihre Infrastrukturen, Prozesse und Mitarbeiter auf die kommenden Herausforderungen vorzubereiten. Dieser Text beleuchtet einige der zentralen Trends und die damit verbundenen L\u00f6sungsans\u00e4tze. K\u00fcnstliche Intelligenz (KI) ist kein futuristisches Konzept mehr, sondern eine operative Realit\u00e4t, […]<\/p>\n","protected":false},"author":1,"featured_media":1628201,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"rank_math_internal_links_processed":["1"],"yoast_wpseo_title":["Die IT-Herausforderungen 2026: Trends und L\u00f6sungsans\u00e4tze"],"_yoast_wpseo_title":["Die IT-Herausforderungen 2026: Trends und L\u00f6sungsans\u00e4tze"],"yoast_wpseo_metadesc":["Die IT-Herausforderungen 2026: Trends und L\u00f6sungsans\u00e4tze\r\n\r\nDas Jahr 2026 r\u00fcckt n\u00e4her und mit ihm eine Reihe von Entwicklungen, die die.."],"_yoast_wpseo_metadesc":["Die IT-Herausforderungen 2026: Trends und L\u00f6sungsans\u00e4tze\n\nDas Jahr 2026 r\u00fcckt n\u00e4her und mit ihm eine Reihe von Entwicklungen, die die.."],"yoast_wpseo_focuskw":["IT Herausforderungen 2026\r\n"],"_yoast_wpseo_focuskw":["IT Herausforderungen 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Blog","author_link":"#"},"uagb_comment_info":0,"uagb_excerpt":"Das Jahr 2026 schreitet voran und mit ihm eine Reihe von Entwicklungen, die die IT-Landschaft nachhaltig pr\u00e4gen werden. Die Geschwindigkeit, mit der sich Technologie ver\u00e4ndert, erfordert kontinuierliche Anpassung und strategische Weitsicht. Unternehmen stehen vor der Notwendigkeit, ihre Infrastrukturen, Prozesse und Mitarbeiter auf die kommenden Herausforderungen vorzubereiten. Dieser Text beleuchtet einige der zentralen Trends und die…","_links":{"self":[{"href":"https:\/\/www.cafm-blog.de\/en\/wp-json\/wp\/v2\/posts\/1628182","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.cafm-blog.de\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.cafm-blog.de\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.cafm-blog.de\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.cafm-blog.de\/en\/wp-json\/wp\/v2\/comments?post=1628182"}],"version-history":[{"count":0,"href":"https:\/\/www.cafm-blog.de\/en\/wp-json\/wp\/v2\/posts\/1628182\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.cafm-blog.de\/en\/wp-json\/wp\/v2\/media\/1628201"}],"wp:attachment":[{"href":"https:\/\/www.cafm-blog.de\/en\/wp-json\/wp\/v2\/media?parent=1628182"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.cafm-blog.de\/en\/wp-json\/wp\/v2\/categories?post=1628182"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.cafm-blog.de\/en\/wp-json\/wp\/v2\/tags?post=1628182"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}} |