Creation of a tailored AI strategy

The client needed to establish a systematic framework for AI implementation, as the lack of a unified approach risked random use case selection, inefficient investments, duplicate initiatives, and increased regulatory, security, and organizational risks. Additionally, there was no clear procedure for linking technological AI capabilities with the real needs of individual departments or for prioritizing further development. It was therefore essential to create a strategic foundation for the safe, economically sound, and long-term sustainable use of AI.

Consultation was provided focused on AI strategy, AI governance, and use case prioritization. This included structured workshops, analysis of organizational processes and needs, identification of opportunities for AI utilization, their evaluation based on benefit, feasibility, and risks, and the design of a prioritized backlog and roadmap. Additionally, an AI governance framework was prepared, including recommendations for roles, rules, AI initiative approval, risk management, and compliance with regulatory requirements. The result was a practical foundation for the managed adoption of AI within the organization.

Organization management, department heads, process owners, IT, digitalization or innovation team, legal and compliance roles, or other AI initiative guarantors.

Several weeks (depending on the number of workshops).

Facilitated workshops, process mapping, AI readiness assessment, prioritization matrix of use cases, backlog and roadmap of AI initiatives, AI governance framework, design of roles and responsibilities, risk management model, compliance checklists for GDPR and EU AI Act, documentation and approval templates.

Top management (C‑level)

Technical support / consultation only

Subsequent possibility of running prioritized POCs and their productization.

Ability to make decisions.

Participation of suitable persons in workshops and provision of inputs.

The solution has brought the organization a more systematic approach to implementing AI, better coordination between management, IT, process owners, and compliance roles, and greater transparency in decision-making regarding AI initiatives. Thanks to the prioritization of use cases, areas with the highest potential have become clearer.

Within this type of consulting project, the main measurable outputs include: the number of analyzed agendas and processes, the number of identified and evaluated AI use cases, the number of proposed priority pilots, the scope of the created roadmap, and the number of defined governance artifacts. In similar reference projects, for example, 8 workshops were held, 150 use cases were identified, and 4 PoCs were converted into production projects.

The client particularly appreciated the ability to connect the strategic level of AI with the practical needs of the organization, clearly structure priority use cases, and simultaneously set up a realistic governance framework for the safe implementation of AI.

Strong involvement of leadership and key stakeholders, high-quality facilitated workshops.

Varying levels of digitalization and data organization, different quality of process documentation. Aligning expectations of various departments, translating general AI ambitions into specific priorities, and the need to consider regulatory and security requirements.

Start with business goals and processes, not technology. First, verify data readiness, involve business, IT, and compliance, and prioritize use cases based on benefit, feasibility, risks, and regulatory impact. Set up governance from the beginning, not just after the first pilots.