IT Project Management | The bridge between the idea and reality
Project management is much more than schedules and budgets. It is the discipline of orchestrating talent, time and resources to reach a common goal. In a volatile environment, planning rigorously and executing flexibly makes the difference. That is why the best teams deliver results, not just manage activity.
Here we approach IT project management not just through its tools, but through the frameworks and mindset needed to deliver real value in every project. Whether you are looking to optimise technical processes or improve the strategic direction of your initiatives, here you will find analysis, guides and reflections based on real experience.
If you are looking for a professional to lead your projects with AI and regulatory compliance, I invite you to see how to hire an AI Project Manager or review my background.
The AI Omnibus postpones high risk to December 2027, but it does not postpone the AI asset inventory. How to build the living register and life cycle your compliance must close before August 2026.
AI cybersecurity banking DORA: why AI does not fill the cyber-expert deficit, it shifts it. An analysis of the real limit under DORA.
Cybersecurity talent shortage in banking: 15,000 vacancies DORA requires filling since 2025. The solution with a senior AI/Cyber Project Manager.
The EU postpones the AI Act to December 2027 and August 2028 and cuts red tape. Timeline, fines and what your company must do before August 2026.
Vibe coding in the enterprise: how to make the most of AI-assisted development with governance, security and EU AI Act compliance without losing pace.
DORA in banking and fintech: five pillars, real deadlines and how they fit with NIS2 and the EU AI Act. What I implemented in financial-sector projects.
NIS2 compliance from the first project phase, not the final audit. A method for Project Managers who can no longer look the other way.
Autonomous AI agents for the PMO: dynamic planning, risk prediction, automated reporting, governance and how to implement them.
Modernising COBOL with AI and Claude: a step-by-step guide with strategy, phases, risks and real cases of banking and insurance migration.
GenAI risks in IT projects: a practical guide to leading generative AI implementation with security, efficiency and regulatory compliance.
AI IT project: planning, architecture, quality, governance and the EU AI Act. A practical guide to managing AI projects.
AI Project Manager: role, key skills and the future of this figure leading AI integration in projects in 2026.
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