KI wird erwachsen: Die neuen Governance-, Sicherheits- und Compliance-Anforderungen für 2026

The new year marks a decisive turning point in digital enterprise management, with the pure experimentation phase with artificial intelligence giving way to an era of sound governance and operational maturity. While previous years were characterized by hype surrounding generative language models, 2026 will be marked by measurable value creation and the necessary consolidation of technological ecosystems. IT executives are under pressure to master the rapidly growing complexity of their IT landscapes, manage budgets efficiently, and at the same time minimize the security risks posed by accelerated AI adoption. In this area of tension, the disciplines of IT asset management (ITAM), cybersecurity, and regulation are merging into an integrated framework that will determine future business success.

In the area of IT asset management, a significant shift is taking place by 2026 from mere inventory management to a strategic discipline that serves as a central source of information for business decisions. Companies are increasingly moving away from isolated individual solutions and instead relying on a platform strategy to cope with the burden of "tool proliferation." A central system acts as a "single source of truth", bundling asset data, contracts, and lifecycle workflows to form the basis for accurate reporting to management. This consolidation process is necessary to increase efficiency and reduce the administrative costs of maintaining numerous integrations.

Artificial intelligence is no longer used as a mere gimmick within these platforms, but as a targeted "force multiplier." In 2026, successful ITAM teams will primarily use AI models for data cleansing and normalization to automatically resolve inconsistencies in hardware and software designations. In addition, AI-powered analytics enable proactive detection of anomalies in usage patterns and spending, particularly for cloud and SaaS services, where unforeseen cost spikes can be identified immediately. Despite this automation, human oversight remains an indispensable part of the process, as experts must validate AI suggestions to maintain transparency and trust in the systems.

Another critical aspect of ITAM in 2026 is the management of AI technologies as a separate asset class. As initial adoption rates level off and licensing models for AI models remain highly complex, AI spending is becoming one of the largest items in the IT budget. Organizations that establish effective expenditure management in this area will gain a competitive advantage by bringing the costs of "shadow AI" – i.e., unauthorized tools procured independently by specialist departments – under control. Only those who understand their entire software supply chain and the associated cost structures can fully exploit the strategic advantages of AI.

The smooth transition from managing these assets to protecting them forms the bridge to cybersecurity, as undetected or poorly managed resources will offer the greatest attack surface in 2026.

The cybersecurity landscape of 2026 will be defined by a massive acceleration of threats as attackers use AI to detect and exploit vulnerabilities in software faster than ever before. Experts predict a flood of AI-generated zero-day exploits that will leave traditional defense mechanisms with little time to respond. In this environment, the "agentic SOC" is establishing itself as the new standard of defense. Here, intelligent AI agents operate within security centers, investigating threats at machine speed and autonomously initiating countermeasures, while human analysts take on the role of strategists who coordinate the overall framework.

One of the most dangerous new forms of attack is "prompt injection," which in 2026 will take on the significance that phishing had in the era of email. Attackers use manipulated input commands to bypass the security barriers of AI models, extract data, or trick AI agents into performing malicious actions. This makes the introduction of AI Detection and Response (AIDR) imperative to ensure real-time visibility into interactions between humans and AI models and to stop abuse early on. The security of AI systems is thus inextricably linked to the security of the entire company.

At the same time, the focus of identity management is shifting from a purely human-centered perspective to securing an exploding number of non-human identities. AI agents and machine identities are increasingly acting independently, have extensive access rights, and can even create sub-agents, pushing traditional accountability models to their limits. In 2026, the seamless traceability of AI agent actions back to the responsible human will become a central requirement of enterprise-wide governance in order to manage liability and compliance risks. Organizations will need to establish new systems that can monitor these complex chains of delegation in real time.

In 2026, technological advances will be accompanied by a dense network of regulatory requirements that hold companies accountable and demand clear transparency. The EU AI Act will enter its most important phase this year, with strict compliance obligations for high-risk AI systems becoming binding from August 2026. Providers of general-purpose AI models (GPAI) must submit detailed technical documentation and ensure that their training data complies with EU copyright regulations. Violations of these provisions can result in draconian fines of up to €35 million or 7% of global annual turnover, making compliance with the rules a matter of survival.

In addition to the AI Act, the reporting requirements of the Cyber Resilience Act (CRA) will take effect in September 2026. Manufacturers of products with digital elements are now legally required to report actively exploited vulnerabilities and security incidents to the authorities within short deadlines. This requires seamless integration of ITAM data into security processes, as only complete visibility of the software components used enables timely reporting. Regulatory frameworks such as NIS2 and DORA further increase this pressure by requiring precise inventory management as the basis for cyber resilience.

In addition to security, sustainability (ESG) is becoming a strategic mandate at the forefront of IT responsibility. According to the CSRD directive, companies must provide detailed evidence in 2026 of how they use, reuse, and dispose of their IT resources. IT asset management plays a key role here by providing the necessary data for the circular economy and documenting the reduction of electronic waste. At the same time, new standards are emerging for the labeling and tagging of AI-generated content to counteract the spread of deepfakes and protect trust in digital information.

The year 2026 requires a new form of technological sovereignty based on the close interlinking of transparency, security, and compliance. ITAM provides fundamental knowledge about the infrastructure, cybersecurity protects it from automated attacks, and regulations set the legal framework for the trustworthy use of AI. Companies that view these three pillars not as isolated tasks but as an integrated overall strategy will be best positioned to safely and profitably exploit the opportunities of the AI revolution. The ability to maintain high-quality, trustworthy data across all assets will become a key competitive differentiator.

Author: Eric Loewenstein