Training

SKILLS DEVELOPMENT PROGRAMME. AI training for public administration. Practical. Safe. Human-centred

The programme combines everyday AI practice, security and law, change implementation and collaboration between institutions. Each course can be ordered separately or combined into a coherent development path

Programme facts

• 8 courses
• ISO 42001 — full compliance
• 3 × 80 min — convenient blocks
• Mode — Online
• Group — 8–18 people
• PLN 0 — up to 5 people

Skills that translate into action

Almost half of public-administration staff already use generative AI at work, 87% want training and 70% cite missing internal procedures as an implementation barrier (NASK, 2026). The Ministry of Digital Affairs guide says institutions should train staff in how AI works, its limitations and safe use

What makes the courses different

For public administration

Exercises reflect administrative work and the four NASK concepts: citizen chat, content creation, RAG search and AI agents

A practical outcome

Every course produces a document the institution can use: a checklist, oversight map, tool register, pilot charter or action plan

Manageable workload

Up to four hours of learning in three 80-minute blocks with breaks

Tool-independent

We teach capabilities and judgement, not one product; exercises can use existing tools and Polish PLLuM and Bielik models

The voice of officials

6,093 officials told us what they need. The programme responds point by point

Based on the NASK report “AI in public e-administration—the perspective of officials and institutions” (March 2026; CAWI N=6,093 and 24 focus groups, commissioned by the Ministry of Digital Affairs) and the Ministry’s public-administration AI guide. Every figure below maps to a course

87% want training in AI tools

The most frequently reported need. The Ministry guide adds that institutions must provide training on AI operation, limitations and safe use

Related courses: 01 FOUNDATIONS. + the complete path

46% already use generative AI at work—77% encounter it daily

Mostly for information search and writing, often through public tools and private accounts. Practice has moved ahead of policy

Related courses: 01 FOUNDATIONS, 03 SECURITY

70% cite missing internal rules as a barrier

An institution cannot resolve unclear legislation, but it can remove its own procedural gap in a four-hour workshop

Related courses: 03 SECURITY. → draft policy for internal adoption

72% see the greatest potential in document search and analysis

Natural-language search is the highest-rated concept when answers include a source and date and respect permissions

Related courses: 02 KNOWLEDGE. → metadata-based source catalogue

81% want routine work automated so they can focus on expert tasks

Yet agents raise questions about existing systems, liability and whether oversight costs more than it saves

Related courses: 05 AUTOMATION, 04 PILOT

91% oppose algorithms replacing people in citizen decisions

This is a boundary condition, not resistance. The programme is built around human oversight (AI Act, Article 14): information provider, not decision-maker

Related courses: 06 CITIZEN SERVICE, 03 SECURITY

Sources

• NASK, “AI in public e-administration—the perspective of officials and institutions”, 17 March 2026
• Ministry of Digital Affairs, “Artificial intelligence guide for public administration”

Recommended course order

Select a course to go to its programme

The recommended sequence moves from practical foundations through knowledge, security and pilots to automation, citizen service, change management and inter-institutional exchange

01 Foundations — AI in public administration work

Why: Organise safe everyday use of AI and produce a controlled task map Audience and outcome are described in the full course programme

02 Knowledge — Documents, knowledge and RAG—how AI can help find information in public administration

Why: Prepare documents and sources for reliable, cited AI answers Audience and outcome are described in the full course programme

03 Security — Safe and responsible use of AI—GDPR, the AI Act and internal rules

Why: Establish a shared standard for safe and responsible AI use Audience and outcome are described in the full course programme

04 Pilot — Implementing AI in public administration—from problem to controlled pilot

Why: Move from a problem to a small, measurable and reversible test Audience and outcome are described in the full course programme

05 Automation — AI agents and process automation in public administration

Why: Choose a process and define safe boundaries for AI-agent support Audience and outcome are described in the full course programme

06 Citizen service — AI in citizen service—faster, simpler and inclusive

Why: Design inclusive information services with a clear human hand-off Audience and outcome are described in the full course programme

07 Change — AI without fear or duplicate work—managing change in a public institution

Why: Reduce fear, disorder and duplicate work during adoption Audience and outcome are described in the full course programme

08 Collaboration — AI together—sharing experience and collaborating across institutions

Why: Share experience without copying solutions blindly Audience and outcome are described in the full course programme

Who it is for

Management and secretaries

Start with rules and accountability, then pilot and lead organisational change

This path establishes accountability, selects a safe first pilot and prepares the organisation for change

Recommended courses: 03, 04, 07, 08

Specialist staff and citizen service

Practical AI, document work and information for citizens

This path covers everyday tasks, documents and citizen contact with human control and clear boundaries

Recommended courses: 01, 02, 06, 08

IT and information security

Knowledge sources, permissions, usage rules and controlled automation

This path focuses on knowledge sources, permissions, the tool register and technical preparation for automation

Recommended courses: 02, 03, 05

Training prices

September–October 2026

Special edition: PLN 0 per person. Up to five participants from one institution on each course with newsletter subscription. Additional places use November rates

November–December 2026

• Single course: 1–5; PLN 200 net; PLN 246 gross; base price
• Team package: 6–10; PLN 170 net; PLN 209.10 gross; 15% less
• Larger-team package: 11–18; PLN 150 net; PLN 184.50 gross; 25% less
• Complete 8-course path: 1 person; PLN 1280 net; PLN 1,574.40 gross; 20% less

Training programme

01 Foundations — AI in public administration work

Workshop • 3 × 80 minutes

Who it is for

Specialist staff and department managers who already use AI or are about to start; no technical background required. This course fulfils the AI literacy obligation (AI Act, Article 4) and covers limitations, critical evaluation of results and effective prompting

What participants gain

• Identifies tasks that are and are not suitable for AI
• Writes precise prompts and knows how to improve them
• Uses AI for documents and plain-language content
• Knows which data must not be entered into AI tools and when to stop
• Can demonstrate that a person verified the AI output

Outcome for the organisation: Staff perform common tasks with AI consistently and under control. The institution reduces informal use of public tools and gains a task map and checklist that can support its internal AI policy

Next step: The task map feeds into Course 03 (policy and register) and selection of the first use case in Course 04. Institutions that want to work on their own documents and infrastructure, including with PLLuM or Bielik, can continue in SAIE

Training programme

A. Where AI helps—and where it does not

• Common AI uses in public administration, based on the four NASK concepts
• Why a model can sound confident when wrong: hallucinations, outdated law and AI slop
• Low-risk, conditional and unacceptable tasks; data that must not enter public tools

Outcome: Task map: use / check conditions / do not use, aligned with the Ministry guide

B. Document work and content creation

• Prompt structure: goal, context, audience, format and constraints
• Summaries, analyses and comparisons; simplifying administrative language
• Drafting a reply or note from named sources without inventing legal grounds

Outcome: A working draft marking what AI generated and what a person verified

C. Human verification and decision

• Hallucinations, omissions and false matches in administrative letters
• Checking source, version, date and completeness; when to ask an expert or DPO
• Decision trail: what was accepted, rejected and changed (human oversight, AI Act Article 14)

Outcome: AI-output verification checklist ready for the institution’s internal policy

Training dates

Term 1: 16.09 • śr • 10:00 - 11:20 | 17.09 • czw • 10:00 - 11:20 | 18.09 • pt • 10:00 - 11:20

Term 2: 20.10 • wt • 10:00 - 11:20 | 21.10 • śr • 10:00 - 11:20 | 22.10 • czw • 10:00 - 11:20

Term 3: 16.11 • pon • 10:00 - 11:20 | 17.11 • wt • 10:00 - 11:20 | 18.11 • śr • 10:00 - 11:20

Term 4: 14.12 • pon • 10:00 - 11:20 | 15.12 • wt • 10:00 - 11:20 | 16.12 • śr • 10:00 - 11:20

02 Knowledge — Documents, knowledge and RAG—how AI can help find information in public administration

Workshop • 3 × 80 minutes

Who it is for

Staff responsible for documentation and procedures, secretaries, IT teams and teams preparing a search engine or knowledge base. 72% of officials see the greatest AI potential in searching and analysing documents (NASK, 2026)

Natural-language document search was the highest-rated NASK concept, but it raises questions about permissions, source currency and ownership. Participants learn RAG logic, organise document status and ownership, and design source-grounded answers that respect access rights

What participants gain

• Understands the difference between a general AI assistant and a RAG knowledge base
• Distinguishes current, archived and working documents
• Knows who owns documents, updates and permissions
• Can respond when reliable information is missing or sources conflict

Outcome for the organisation: The institution gains a structured starting point for a RAG knowledge base: source scope, document statuses, owners, update rules, permissions and answer-quality criteria

Next step: The source catalogue can be used directly in a search pilot (Course 04). In SAIE, the knowledge base runs on the institution’s infrastructure or private cloud, with department permissions and citations in every answer

Training programme

A. From documents to a reliable answer

• Search combined with answer generation
• General-purpose assistant versus documentation-based assistant
• An answer with a citation, location and date as a condition of trust

Outcome: Flow from a question to a source-grounded answer

B. Information governance and source readiness

• Document scope and source hierarchy
• Status: current, archived, draft or approved
• Version, validity period, review date and owner

Outcome: Source catalogue with metadata and owners—the basis for an ingestion procedure

C. Access, testing and quality maintenance

• Roles and least privilege: staff see only what they may access
• Test questions, edge cases and hallucination-resistance tests
• Relevance, completeness and currency; outage procedure

Outcome: Minimum knowledge-base design with acceptance tests and assigned ownership

Training dates

Term 1: 24.09 • czw • 10:00 - 11:20 | 25.09 • pt • 10:00 - 11:20 | 28.09 • pon • 10:00 - 11:20

Term 2: 28.10 • śr • 10:00 - 11:20 | 29.10 • czw • 10:00 - 11:20 | 30.10 • pt • 10:00 - 11:20

Term 3: 23.11 • pon • 10:00 - 11:20 | 24.11 • wt • 10:00 - 11:20 | 25.11 • śr • 10:00 - 11:20

03 Security — Safe and responsible use of AI—GDPR, the AI Act and internal rules

Workshop • 3 × 80 minutes

Who it is for

Management, secretaries, DPOs, information-security officers and department managers. 66% of officials want training on the legal aspects of AI (NASK, 2026)

Unclear regulations, missing regulations and missing internal procedures are the three most cited barriers. This course turns GDPR and AI Act requirements into practical rules: participants classify uses, define human oversight and prepare an internal AI policy

What participants gain

• Recognises risks involving data, content, private accounts and liability
• Knows when AI is allowed, requires approval or must not be used
• Knows when a person must verify an AI result
• Can assess whether an AI tool is approved, secure and compliant with GDPR and the AI Act

Outcome for the organisation: The institution gains a shared vocabulary and a working policy model covering permitted uses, conditions, approval and incident handling

Next step: The policy and register underpin a safe pilot (Course 04). PROXY:AI can enforce approved-model access, personal-data filtering and use logging. allclouds.pl is Poland’s first Bureau Veritas-certified ISO/IEC 42001 company

Training programme

A. Law, data and controlled use cases

• GDPR in AI work: personal and special-category data, minimisation, anonymisation and DPIA
• AI Act: prohibited practices, high-risk public-sector systems and AI literacy (Article 4)
• Approved and unapproved AI environments; what a supplier contract does not guarantee

Outcome: Initial review of AI uses and processed information with risk classification

B. The person in the process and accountability boundaries

• AI as supporting material, not a decision
• Automated actions, proposals for approval and human decisions
• Roles of user, verifier, process owner and expert

Outcome: Human-oversight map for one use case (AI Act, Article 14)

C. Organisational rules, register and incidents

• Register of approved tools and uses
• Minimum logging and log protection
• Reporting errors, breaches or out-of-policy use

Outcome: Draft safe-AI policy ready for adoption by internal order

Training dates

Term 1: 21.09 • pon • 10:00 - 11:20 | 22.09 • wt • 10:00 - 11:20 | 23.09 • śr • 10:00 - 11:20

Term 2: 23.10 • pt • 10:00 - 11:20 | 26.10 • pon • 10:00 - 11:20 | 27.10 • wt • 10:00 - 11:20

Term 3: 19.11 • czw • 10:00 - 11:20 | 20.11 • pt • 10:00 - 11:20 | 23.11 • pon • 10:00 - 11:20

Term 4: 17.12 • czw • 10:00 - 11:20 | 18.12 • pt • 10:00 - 11:20 | 21.12 • pon • 10:00 - 11:20

04 Pilot — Implementing AI in public administration—from problem to controlled pilot

Workshop • 3 × 80 minutes

Who it is for

Secretaries, department managers, process owners, IT and project staff—the team deciding on the first implementation

The Ministry guide starts at Stage 0: is AI needed at all? This course follows the same path from a defined problem to a small, reversible and measurable pilot. Technology is selected only after outcomes, data, risks and controls are clear

What participants gain

• Identifies problems where AI may help
• Assesses benefits, risks and organisational readiness
• Plans a small, safe and reversible AI test
• Defines metrics, operating costs, controls and stop conditions

Outcome for the organisation: Participants finish with a realistic pilot charter rather than a generic idea list. It can be reviewed by legal, security, IT and the process owner

Next step: The charter feeds a CDF pilot: demonstration on institutional data, limited pilot and scale decision. SAIE supports a pilot without buying infrastructure or locking into one supplier

Training programme

A. Problem before technology

• AI versus ordinary automation: AI, a better form or a better procedure?
• Repetition, time cost and verifiability
• User, need and measurable goal: service time, errors and availability

Outcome: Use-case description with a measurable goal and expected benefits

B. Readiness and pilot design

• Data, sources, procedures, skills and infrastructure; GDPR and AI Act risk classification
• Small scope, test group and manual fallback
• Process, data, knowledge and technology owner roles

Outcome: Limited pilot design with assigned roles

C. Measurement and decision

• Tests on real cases: time with and without AI, consistency and unusual queries
• Output quality, errors, corrections and rejections
• Verification, data-update and maintenance cost

Outcome: Pilot charter with metrics and a continue / redesign / stop gate

Training dates

Term 1: 29.09 • wt • 10:00 - 11:20 | 30.09 • śr • 10:00 - 11:20 | 01.10 • czw • 10:00 - 11:20

Term 2: 02.11 • pon • 10:00 - 11:20 | 03.11 • wt • 10:00 - 11:20 | 04.11 • śr • 10:00 - 11:20

Term 3: 30.11 • pon • 10:00 - 11:20 | 01.12 • wt • 10:00 - 11:20 | 02.12 • śr • 10:00 - 11:20

Term 4: 21.12 • pon • 10:00 - 11:20 | 22.12 • wt • 10:00 - 11:20 | 23.12 • śr • 10:00 - 11:20

05 Automation — AI agents and process automation in public administration

Workshop • 3 × 80 minutes

Who it is for

IT, records and document-workflow process owners and secretariat managers, especially institutions considering automated registration or routing

AI agents drew the most scepticism in the NASK study. Participants distinguish agents from general assistants and rule-based automation, then design one bounded process with explicit actions, permissions and human decisions

What participants gain

• Understands assistants, workflows, rule automation and AI agents
• Selects a process suitable for agent support
• Defines what the agent may do and access
• Knows how to reverse an action, fall back to manual handling or stop safely

Outcome for the organisation: Participants can judge whether an agent is justified and design it so people retain decisions and process control. The agent starts with a simple proposal, not autonomy

Next step: The flow can be piloted in SAIE, where automation works alongside knowledge bases and assistants while PROXY:AI enforces permissions and logs every agent step

Training programme

A. Does this process need an agent?

• AI assistant, workflow, rule-based automation and AI agent
• Repeatable, reversible and verifiable tasks
• Risk of duplicating existing document-management functions

Outcome: Reasoned decision: agent / automation / no implementation

B. Designing a safe flow

• Trigger, inputs, knowledge sources and tools
• Least privilege, action limits and no autonomous citizen decisions
• Automated steps, AI steps and human approval

Outcome: One process map with a defined AI-autonomy boundary

C. Testing, monitoring and error response

• Typical, unusual and invalid scenarios tested before launch
• Stop criteria, human escalation and manual fallback
• Logging steps, decisions and tools used

Outcome: Test and oversight plan for the designed flow

Training dates

Term 1: 12.10 • pon • 10:00 - 11:20 | 13.10 • wt • 10:00 - 11:20 | 14.10 • śr • 10:00 - 11:20

Term 2: 05.11 • czw • 10:00 - 11:20 | 06.11 • pt • 10:00 - 11:20 | 09.11 • pon • 10:00 - 11:20

Term 3: 26.11 • czw • 10:00 - 11:20 | 27.11 • pt • 10:00 - 11:20 | 30.11 • pon • 10:00 - 11:20

Term 4: 14.12 • pon • 10:00 - 11:20 | 15.12 • wt • 10:00 - 11:20 | 16.12 • śr • 10:00 - 11:20

06 Citizen service — AI in citizen service—faster, simpler and inclusive

Workshop • 3 × 80 minutes

Who it is for

Citizen-service offices, information desks, call centres, communications teams and departments handling repeated questions. A separate internal-assistant variant is available for regional and central authorities

Officials support citizen chat when it informs rather than advises, clearly identifies AI, offers a human hand-off and creates no new digital barrier. Participants design an informative, bounded and inclusive service

What participants gain

• Distinguishes informing, advising and deciding, and knows where AI is appropriate
• Designs an AI assistant’s knowledge and answer scope
• Ensures plain language and transparency
• Defines when the assistant must offer a staff member or another channel

Outcome for the organisation: The institution gains a safe information-service scenario that reduces simple enquiries without blocking access to a person

Next step: The scenario can run in SAIE on a local knowledge base and a Polish model such as PLLuM or Bielik, with full conversation logging. Small municipalities can share an assistant

Training programme

A. AI’s role in citizen contact

• Repeated questions and first-line needs
• Information guide, not adviser or decision-maker
• Clear disclosure that the user is interacting with AI

Outcome: Assistant scope and a list of matters outside its remit

B. Service path and content design

• User intents and clarifying questions
• Plain-language answer with source, date and legal version
• Link to the correct form, department or instruction

Outcome: Conversation scenario and citizen-service stages

C. Accessibility, currency and trust testing

• Tests with different levels of digital skill
• Hallucinations, unusual cases and missing grounds
• Knowledge-base owner and update cycle after legal changes

Outcome: Service test plan covering quality, accessibility, hand-off and currency

Training dates

Term 1: 07.10 • śr • 10:00 - 11:20 | 08.10 • czw • 10:00 - 11:20 | 09.10 • pt • 10:00 - 11:20

Term 2: 09.11 • pon • 10:00 - 11:20 | 10.11 • wt • 10:00 - 11:20 | 12.11 • czw • 10:00 - 11:20

Term 3: 03.12 • czw • 10:00 - 11:20 | 04.12 • pt • 10:00 - 11:20 | 07.12 • pon • 10:00 - 11:20

Term 4: 17.12 • czw • 10:00 - 11:20 | 18.12 • pt • 10:00 - 11:20 | 21.12 • pon • 10:00 - 11:20

07 Change — AI without fear or duplicate work—managing change in a public institution

Workshop • 3 × 80 minutes

Who it is for

Management, secretaries, HR, department managers and future AI ambassadors—the team leading implementation

Officials’ concerns include error, liability, duplicate work and loss of expertise. Participants identify concerns, involve staff in testing and verify that AI makes work easier without weakening competence

What participants gain

• Understands employee concerns and the real cost of change
• Knows when to explain an implementation better and when to change it
• Can involve staff in testing and evaluating AI

Outcome for the organisation: The institution gains a change plan reflecting staff concerns and knowledge, the work balance and safe adoption instead of forced tool use

Next step: The change plan accompanies the Course 04 pilot and forms part of CDF, where roles, concerns and team capabilities are defined before technology selection

Training programme

A. Diagnosing concerns and stakeholders

• Fear of role loss, control, error and lost expertise
• Fear that overseeing AI costs more than it saves
• Differences between user, manager, IT and control functions

Outcome: List of people involved, their concerns and information needs

B. Co-designing the new way of working

• What disappears, remains and is created—and who verifies
• Staff role in selecting and testing the use case
• Human control at key stages instead of automatic approval

Outcome: Before-and-after comparison of time and competence

C. Communication, learning and sustained change

• On-the-job support when a tool fails
• Short training, practice, consultations and AI ambassadors
• Safe reporting of errors and problems

Outcome: Communication and skills-development plan for the test

Training dates

Term 1: 02.10 • pt • 10:00 - 11:20 | 05.10 • pon • 10:00 - 11:20 | 06.10 • wt • 10:00 - 11:20

Term 2: 12.11 • czw • 10:00 - 11:20 | 13.11 • pt • 10:00 - 11:20 | 16.11 • pon • 10:00 - 11:20

Term 3: 01.12 • wt • 10:00 - 11:20 | 02.12 • śr • 10:00 - 11:20 | 03.12 • czw • 10:00 - 11:20

Term 4: 21.12 • pon • 10:00 - 11:20 | 22.12 • wt • 10:00 - 11:20 | 23.12 • śr • 10:00 - 11:20

08 Collaboration — AI together—sharing experience and collaborating across institutions

Workshop • 3 × 80 minutes

Who it is for

Secretaries and digital coordinators from several institutions, municipal associations, agreements, territorial partnerships, counties and municipalities; delivered as a joint workshop

Small municipalities cite implementation cost and propose shared solutions. Participants learn to exchange AI experience without blindly copying solutions or disclosing protected information, using comparable pilot records and peer review

What participants gain

• Documents an AI test so other institutions understand its process and results
• Separates institution-specific findings from reusable ones
• Structures and discusses conclusions from a test
• Knows what to conceal or anonymise and what must not be shared

Outcome for the organisation: Institutions gain a shared format for comparing experience and a practical collaboration plan that prevents duplicated testing and enables reuse

Next step: A group can launch a shared SAIE pilot: one environment, separate knowledge bases and permissions, with costs shared among participants

Training programme

A. Describing experience so others can use it

• Problem, user, scope, data and environment
• Metrics, result, errors, cost and decision
• Facts, interpretations and recommendations

Outcome: Pilot summary card comparable across institutions

B. Peer review and transferring a solution

• Critical questions without personal judgement
• Conditions for success and causes of failure
• Differences in process, data, local law and infrastructure

Outcome: Assessment of whether other institutions can reuse the solution

C. A lasting collaboration mechanism

• Card repository, webinar, forum or working group linked to AI HUB (ai.gov.pl)
• Owner, moderator and expert roles
• Update, review and retirement cycle

Outcome: 90-day experience-sharing and joint-action plan, including a shared pilot option

Training dates

Term 1: 15.10 • czw • 10:00 - 11:20 | 16.10 • pt • 10:00 - 11:20 | 19.10 • pon • 10:00 - 11:20

Term 2: 17.11 • wt • 10:00 - 11:20 | 18.11 • śr • 10:00 - 11:20 | 19.11 • czw • 10:00 - 11:20

Term 3: 07.12 • pon • 10:00 - 11:20 | 08.12 • wt • 10:00 - 11:20 | 09.12 • śr • 10:00 - 11:20

Training calendar

All 2026 dates in one place

01 Foundations: 16.09 • śr • 10:00 - 11:20 | 17.09 • czw • 10:00 - 11:20 | 18.09 • pt • 10:00 - 11:20 || 20.10 • wt • 10:00 - 11:20 | 21.10 • śr • 10:00 - 11:20 | 22.10 • czw • 10:00 - 11:20 || 16.11 • pon • 10:00 - 11:20 | 17.11 • wt • 10:00 - 11:20 | 18.11 • śr • 10:00 - 11:20 || 14.12 • pon • 10:00 - 11:20 | 15.12 • wt • 10:00 - 11:20 | 16.12 • śr • 10:00 - 11:20

02 Knowledge: 24.09 • czw • 10:00 - 11:20 | 25.09 • pt • 10:00 - 11:20 | 28.09 • pon • 10:00 - 11:20 || 28.10 • śr • 10:00 - 11:20 | 29.10 • czw • 10:00 - 11:20 | 30.10 • pt • 10:00 - 11:20 || 23.11 • pon • 10:00 - 11:20 | 24.11 • wt • 10:00 - 11:20 | 25.11 • śr • 10:00 - 11:20

03 Security: 21.09 • pon • 10:00 - 11:20 | 22.09 • wt • 10:00 - 11:20 | 23.09 • śr • 10:00 - 11:20 || 23.10 • pt • 10:00 - 11:20 | 26.10 • pon • 10:00 - 11:20 | 27.10 • wt • 10:00 - 11:20 || 19.11 • czw • 10:00 - 11:20 | 20.11 • pt • 10:00 - 11:20 | 23.11 • pon • 10:00 - 11:20 || 17.12 • czw • 10:00 - 11:20 | 18.12 • pt • 10:00 - 11:20 | 21.12 • pon • 10:00 - 11:20

04 Pilot: 29.09 • wt • 10:00 - 11:20 | 30.09 • śr • 10:00 - 11:20 | 01.10 • czw • 10:00 - 11:20 || 02.11 • pon • 10:00 - 11:20 | 03.11 • wt • 10:00 - 11:20 | 04.11 • śr • 10:00 - 11:20 || 30.11 • pon • 10:00 - 11:20 | 01.12 • wt • 10:00 - 11:20 | 02.12 • śr • 10:00 - 11:20 || 21.12 • pon • 10:00 - 11:20 | 22.12 • wt • 10:00 - 11:20 | 23.12 • śr • 10:00 - 11:20

05 Automation: 12.10 • pon • 10:00 - 11:20 | 13.10 • wt • 10:00 - 11:20 | 14.10 • śr • 10:00 - 11:20 || 05.11 • czw • 10:00 - 11:20 | 06.11 • pt • 10:00 - 11:20 | 09.11 • pon • 10:00 - 11:20 || 26.11 • czw • 10:00 - 11:20 | 27.11 • pt • 10:00 - 11:20 | 30.11 • pon • 10:00 - 11:20 || 14.12 • pon • 10:00 - 11:20 | 15.12 • wt • 10:00 - 11:20 | 16.12 • śr • 10:00 - 11:20

06 Citizen service: 07.10 • śr • 10:00 - 11:20 | 08.10 • czw • 10:00 - 11:20 | 09.10 • pt • 10:00 - 11:20 || 09.11 • pon • 10:00 - 11:20 | 10.11 • wt • 10:00 - 11:20 | 12.11 • czw • 10:00 - 11:20 || 03.12 • czw • 10:00 - 11:20 | 04.12 • pt • 10:00 - 11:20 | 07.12 • pon • 10:00 - 11:20 || 17.12 • czw • 10:00 - 11:20 | 18.12 • pt • 10:00 - 11:20 | 21.12 • pon • 10:00 - 11:20

07 Change: 02.10 • pt • 10:00 - 11:20 | 05.10 • pon • 10:00 - 11:20 | 06.10 • wt • 10:00 - 11:20 || 12.11 • czw • 10:00 - 11:20 | 13.11 • pt • 10:00 - 11:20 | 16.11 • pon • 10:00 - 11:20 || 01.12 • wt • 10:00 - 11:20 | 02.12 • śr • 10:00 - 11:20 | 03.12 • czw • 10:00 - 11:20 || 21.12 • pon • 10:00 - 11:20 | 22.12 • wt • 10:00 - 11:20 | 23.12 • śr • 10:00 - 11:20

08 Collaboration: 15.10 • czw • 10:00 - 11:20 | 16.10 • pt • 10:00 - 11:20 | 19.10 • pon • 10:00 - 11:20 || 17.11 • wt • 10:00 - 11:20 | 18.11 • śr • 10:00 - 11:20 | 19.11 • czw • 10:00 - 11:20 || 07.12 • pon • 10:00 - 11:20 | 08.12 • wt • 10:00 - 11:20 | 09.12 • śr • 10:00 - 11:20

ALLCLOUDS.PL IS THE FIRST COMPANY IN POLAND CERTIFIED TO ISO/IEC 42001 BY BUREAU VERITAS

We teach AI management the way we manage it according to the standard

Our AI management system covers every AI system, the CDF methodology, SAIE ecosystem products, personnel and supply chain from concept to retirement. Training and consulting are covered by the same Integrated Management System alongside ISO 9001, 27001, 27017, 27018, 22301, 14001 and 42001

42001 audit: 0 nonconformities

Instructors

People who build AI systems for the public sector—not just talk about them

Four instructors, each with more than five years of public-institution project experience. Designers of TWIN:DESK and PROXY:AI and co-authors of CDF and an ISO/IEC 42001-certified AI management system

Anna Pawelec — AI systems designer

Specialisms: TWIN:DESK, Systems for central institutions, External-user processes

For more than five years she has designed public-sector IT solutions. A lead TWIN:DESK designer, she developed process systems involving external users for central institutions and now leads the TWIN:DESK roadmap

In the courses: turning institutional documents into a working knowledge base and designing an assistant that always leaves citizens a path to a person

Teaches: 02 KNOWLEDGE, 05 AUTOMATION, 06 CITIZEN SERVICE

Robert Duda — AI security consultant

Specialisms: PROXY:AI, IT security, Critical infrastructure

For more than ten years he has built public-sector IT solutions. A lead PROXY:AI designer, he has worked on critical network and security implementations and specialises in secure AI adoption and training

In the courses: what happens to data entered into AI tools and how to build rules that can be enforced technically

Teaches: 03 SECURITY, 05 AUTOMATION

Rafał Grzegorzewski — AI security and methodology consultant

Specialisms: CDF methodology, ISO/IEC 42001, AI Act, Reporting systems

For more than ten years he has built public-sector IT solutions, including reporting systems for supervisory institutions. He specialises in CDF, ISO/IEC 42001 and AI Act training

In the courses: moving from a problem to a controlled pilot and preparing documentation that stands up to audit

Teaches: 03 SECURITY, 04 PILOT, 08 COLLABORATION

Marek Skrycki — AI systems project manager and adoption lead

Specialisms: Digital transformation, Project management, AI adoption

An experienced project manager specialising in digital transformation, he has managed complex technology projects with multi-million-zloty budgets and now leads practical AI adoption

In the courses: bringing AI into everyday teamwork without fear or duplicate work, and leading lasting change

Teaches: 01 FOUNDATIONS, 04 PILOT, 07 CHANGE

How to order

From order to training in 4 steps

1. Complete the order form

YOU • 5 MINUTES. Choose courses, dates and participant numbers, then enter requester and institution details

2. Receive order confirmation

US • E-MAIL. We e-mail confirmation and, for paid training, a proforma invoice

3. Pay the proforma before training

YOU • PAID TRAINING ONLY. Pay by bank transfer. This step is skipped for the free edition

4. Receive the training link

US • 3 DAYS BEFORE TRAINING. We e-mail it three days before the course. A browser is all you need

Training order form

• Requester: name, business e-mail, phone and role
• Institution: name, street, building number, postal code, city and NIP
• Each course: name, dates, participant count and each participant’s name and e-mail
• Required personal-data processing consent
• Optional newsletter consent determining eligibility for the September–October 2026 free edition

Fields marked with an asterisk are required. The form collects requester, institution, selected-course, price and participant details

Newsletter consent is optional and determines eligibility for the September–October 2026 free edition

Consent to personal-data processing for order handling is required

Training financed entirely from public funds (Article 43(1)(29)(c) of the VAT Act) or at least 70% from public funds (§ 3(1)(14) of the Minister of Finance Regulation of 20 December 2013) is VAT exempt, so the gross price equals the net price. An institution paying from its own budget normally selects 100% funding. The declaration template sent with order confirmation includes both options. If either applies, complete, sign and return it to office@allclouds.pl

What happens after submission

• 1. Order form: Courses, dates, participant numbers and institution details
• 2. E-mail confirmation: For paid training, together with the proforma
• 3. Proforma payment: Before training; skipped in the free edition
• 4. Training link: Sent by e-mail three days before the course