Domain-specific models: when corporate AI needs its own language
Corporate systems require domain-specific language models for security, efficiency, and compliance with unique business processes.
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Practical guidance on management accounting, budgeting, treasury, period close, financial controls and evidence-based AI.
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Corporate systems require domain-specific language models for security, efficiency, and compliance with unique business processes.
Domain-specific AI models are becoming a key tool for modernizing enterprise applications in 2026-2027, overcoming legacy system limitations.
By 2026, over 80% of large enterprises will leverage a combination of RPA and low-code platforms to optimize business processes. This approach accelerates development time and enhances automation efficiency.
By 2026, over 80% of large enterprises utilizing multi-cloud infrastructures will integrate artificial intelligence into their FinOps strategies to optimize costs and enhance efficiency. This shift is driven by the increasing complexity of cloud environments and the need for automated data analysis.
By 2026, over 70% of new AI systems will experience data breaches due to inadequate Data Loss Prevention (DLP) integration, necessitating a reevaluation of sensitive information protection in the age of artificial intelligence.
By 2026, over 75% of new enterprise applications are projected to be developed using low-code or no-code platforms. Integrating artificial intelligence into these platforms significantly speeds up the creation and optimization of BPM systems.
By 2026, over 70% of successful digital transformation initiatives will rely on an effective Data Governance strategy integrated with artificial intelligence capabilities. This will enable addressing data quality issues critical for system integration. The increasing complexity of enterprise IT land
By 2026, companies will face intensified cybersecurity demands and the need to optimize ISO/IEC 27001 audit processes. The application of artificial intelligence will significantly automate this process, minimizing human errors and reducing preparation time.
Recent years have seen a significant rise in multi-cloud strategies, driven by businesses' pursuit of flexibility, cost optimization, and enhanced resilience.