GenAI as a Management Tool: Work Smarter, Decide Better
Simulation where participants practice using AI as a management tool across 5 business scenarios at Grupo Nativa, a LATAM consumer goods company.
About this simulation
A four-round, advanced public-governance simulation set inside the Kantonales Amt für Bürgerdienste (KABD), the Cantonal Office for Citizen Services in the fictional Swiss canton of Brunnental — a 540-person agency serving 620,000 residents on a CHF 96M budget, with CHF 6.5M ring-fenced for digital transformation.
KABD is the most trusted institution in the canton (72% public trust) but one of the slowest: a 14,000-case backlog, a 19-day average processing time and a citizen-satisfaction score of 61/100.
On 11 June 2026 a neighbouring canton's automated benefits-eligibility system is suspended after it is found to disadvantage applicants by postal code and language; parliament demands KABD present a responsible AI plan this quarter — clear the backlog and cut the wait without repeating the failure.
Playing the agency director (with a digital/AI lead, a data-protection & legal officer, a service-delivery manager and a communications lead), you steward AI adoption through the lens of Reto Steiner's research on public-sector digital transformation and public corporate governance (Public Management Review, 2024): public-sector AI must be governed for public value, accountability, transparency and legitimacy, not merely efficiency.
Round 1: diagnose where the delay originates, risk-tier the four candidate use cases (UC-1 document triage, UC-2 benefits-eligibility scoring, UC-3 multilingual chatbot, UC-4 fraud detection) by rights-impact and trust-risk, and state the agency's non-negotiable trust commitment.
Round 2: within the CHF 6.5M cap, prioritize one use case to deploy first and set the governance safeguard — human-in-the-loop, transparency, appeal and contestability rights, bias testing and a named accountable owner — confirming compliance with the revised FADP before deployment, and ring-fencing budget for ongoing monitoring (the FADP deadline is this round).
Round 3: the data-quality audit reveals the historical training data carries the same postal-code skew that sank the neighbour; decide whether to proceed, narrow, or pause and remediate, then sequence the rollout — pilot scope, monitoring gates, fallback and rollback — avoiding the inequity of piloting on the most vulnerable segment first.
Round 4: defend the plan to the parliamentary oversight committee and a journalist in the language of public value, accountability and trust, owning the residual risk rather than defending a metric or blaming the data.
The scoring rewards risk-tiered prioritization, a complete safeguard package, data remediation, equitable sequencing and a legitimacy-framed defence — and punishes the five classic errors: leading with the highest-risk benefits-scoring use case, automating rights-affecting decisions with no safeguard, ignoring the biased data, sequencing risk onto vulnerable citizens, and defending on efficiency alone.
Final KPIs track citizen trust (%), governance compliance (0–100), backlog cleared (of 14,000) and budget discipline against the CHF 6.5M cap.
Who it is for
An advanced simulation for participants used to working with the main frameworks and trade-offs of the subject, designed for executive education and experienced professionals.
How a session runs
- The instructor creates a session from the Eureka dashboard and invites the participants.
- Participants play 4 rounds. In each one they submit their decisions and the simulation calculates the results.
- The instructor follows each participant's progress and results from the dashboard, and uses the class results for the debrief.