Business baseline
Map the process, manual handoffs, rework, and the metric that will prove a meaningful result.
The mandate
Leadership wants AI adoption. Your function still has to make it work.
Licences are bought and employees are experimenting, but the work remains fragmented. Functional leaders are left to choose the right process, secure data and access, keep current KPIs moving, bring the team with them, and prove value in time, quality, cost, or throughput.
The shift
From isolated pilots to operating capability.
We take one bounded workflow from a clear baseline to a measured pilot, then leave your team with the evidence and operating rules needed to scale it.
Bounded pilot
Build with approved tools and data, explicit access limits, and clear points of human decision.
Evidence for scale
Compare before and after, document the workflow, assign an owner, and plan the next 90 days.
Priority workflows
Start where digital work repeats and results can be measured.
The strongest pilots have a process owner, available data, a clear output, and a baseline the team can compare against.
Process discovery
Map SOPs, bottlenecks, manual transfers, and the stages worth redesigning first.
Reconciliation
Compare spreadsheets and systems, match records, and flag anomalies for human review.
Document operations
Receive, classify, summarise, and route contracts, requests, tenders, or reports.
Meeting to action
Turn meetings into decisions, follow-ups, assigned tasks, and visible status updates.
Research and reporting
Structure evidence into management notes, recurring reports, and decision-ready presentations.
Cross-system workflows
Connect CRM, ERP, email, and sheets around controlled points of human approval.
The lab
One workflow: Baseline → Scale
A practical cohort for 12–20 functional leaders and change owners. The goal is not course completion; it is a tested workflow with measurable value and clear operating boundaries.
- 01BaselineProcess, pain, and metric.
- 02PrioritiseChoose one bounded use case.
- 03Set boundariesTools, data, access, oversight.
- 04PilotBuild and test on real work.
- 05EvidenceCompare time, quality, throughput.
- 06ScaleSOP, owner, and 90-day plan.
Who it is for
The leaders accountable for turning AI strategy into daily work.
Designed for EU/EEA mid-market companies with repeatable digital processes: typically 50–249 employees, or multi-entity groups of 250–2,000 with central functions and no mature AI enablement team.
Operations and Shared Services
Increase service capacity, improve SLA and quality, and reduce repetitive workload without proportional headcount growth.
PMO and Transformation
Turn a board-level AI mandate into prioritised pilots, measurable business cases, and a repeatable rollout method.
HR, L&D, and People Operations
Move from one generic awareness session to role-based learning, responsible adoption, and evidence of practice.
Professional and Multi-entity Groups
Standardise document-heavy workflows and transfer proven use cases across teams, markets, and business units.
Outcomes
What your organisation can keep, measure, and govern.
The lab leaves practical artefacts for business owners, IT, privacy, and people teams—not just slides or prompt examples.
Use-case portfolio
A prioritised map with process owners, value, feasibility, data needs, and risk level.
Bounded working pilot
One real workflow with approved inputs, tool and data limits, human oversight, and acceptance criteria.
Evidence pack
Baseline and after-results for time, quality, cost, throughput, adoption, or another agreed metric.
Scale playbook
SOP, team guidance, learning evidence, named owner, and a 90-day roadmap with stop or expand conditions.
FAQ
The questions teams ask before we start.
Is this a general AI course?
No. Your cohort works on selected business processes and leaves with a tested pilot, evidence, boundaries, and a scale plan. We add shared foundations only where the group needs them.
How do you handle data and human oversight?
Each pilot defines approved tools, allowed data, access owners, review points, and acceptance criteria before implementation. Sensitive workflows stay within the environments your organisation approves.
Does the program make us AI Act compliant?
No. The lab can support Article 4 readiness with role-based learning, practical assessment, and documented measures. Legal compliance remains your organisation’s responsibility.
Can HR use cases be included?
Yes, starting with lower-risk or bounded workflows. Decisions such as candidate screening, worker evaluation, promotion, or dismissal require separate legal and risk assessment and are not included in a standard pilot.
Who should join the cohort?
Usually 12–20 functional leaders, process owners, HRBPs, programme managers, and change leads, backed by an executive sponsor. IT, privacy, legal, or employee representatives join relevant design and review points.
Founders
Operators, not course-only trainers.
We have owned delivery, not only taught AI. Between us are 15 years in CG and video production, 500+ projects, and direct responsibility for complex workflows, deadlines, budgets, clients, and teams.
Egor Maraev
Builds the systems
Built a CG, motion, and AI-video studio. Now designs AI workflows, practical learning methods, and implementation systems for teams.
Kate Chernova
Leads delivery
15 years in CG and Head of Production experience. Brings process design, adoption, and delivery discipline to every AI rollout.
First conversation
Bring one process leadership expects you to improve.
In 30 minutes, we will assess whether it has a clear owner, usable data, a measurable baseline, and the right boundaries for a practical pilot.