Work Smarter, Not Harder: Top 5 AI Prompts Every Finance Professional in Czech Republic Should Use in 2025

Finance teams in the Czech Republic are already seeing how targeted AI prompts can move work from guesswork to speed and clarity: the Czech National Bank's first experiments show LLMs (OpenAI o1, Grok 2) helping medium‑term CPI forecasts and embeddings that smartly cluster products - CNB even maps “Dr. Halíř butter” close to olive oil - to improve inflation nowcasting, while agent platforms are turning natural‑language prompts into live FP&A, cash‑flow and reconciliation work (see real prompt use cases in the Concourse AI agents guide: real prompt use cases for finance automation).

These advances are powerful but pragmatic: CNB treats AI as a support tool, not a replacement, and industry guidance stresses governance, data quality and staged rollout.

For Czech finance professionals who want to put prompts to work safely and quickly, the 15‑week AI Essentials for Work bootcamp syllabus - 15-week workplace AI and prompt-writing course offers practical prompt-writing and workplace AI skills, and the Concourse prompt library for automating forecasts, AR/AP and scenario planning shows how to automate forecasts, AR/AP and scenario planning in minutes rather than days.

“With the right strategy, CFOs can create substantial benefits by deploying emerging technologies such as AI.” - Ronald Gothelf, Grant Thornton

Selection of the top five prompts centred on practical impact for Czech finance teams: priority went to prompts that move numbers and audits forward (clear KPIs and P&L impact), embed strong governance and data‑quality checks, and fit into a phased, ERP‑aware rollout rather than a one‑off experiment - advice echoed in Grant Thornton's governance playbook and technology checklist (Grant Thornton governance playbook: Use AI to supercharge finance operations (2025)).

Scoring favoured prompts that target high‑friction, high‑volume workflows - reconciliations, month‑end close, scenario forecasts and tax validations - because these deliver measurable wins and are easier to audit; industry reporting shows reconciliation and close automation can cut hours dramatically, in some cases “up to 95%” of manual time, while improving traceability.

Methodology weights also reflected BCG's playbook on focusing on value and scaling in sequence (BCG report: How finance leaders can get ROI from AI (2025)), and Devoteam/industry guidance to set baselines, define ROI KPIs, and run short pilots with staged governance.

The result is a pragmatic shortlist of prompts that Czech CFOs can deploy quickly, measure reliably, and scale safely - turning speculative AI projects into boardroom‑ready tools with concrete ROI and audit trails.

“With the right strategy, CFOs can create substantial benefits by deploying emerging technologies such as AI.” - Ronald Gothelf, Grant Thornton

JPMorgan DeepX - M&A Due Diligence Summary Prompt: for Czech deal teams this prompt should turn a noisy virtual data room into a crisp executive memo by following proven checklists - start by defining the diligence scope (industry, size, geography and strategic goals), request the core documents (audited financials for 3–5 years, tax returns, material contracts, IP records, cyber incident history) and surface the highest‑impact red flags (inconsistent trends, undisclosed liabilities, cyber breaches or unusual related‑party transactions such as the $750,000 “consulting fee” example flagged in market reporting).

Embed an eight‑pillar view - finance, legal, tax, IT/cyber, operations, HR, commercial, ESG - so the output recommends a working‑capital peg, likely valuation adjustments and Day‑1 integration priorities; AI can accelerate extraction and highlight anomalies but the human team must validate.

Use Diligent's 20‑point checklist for scope and document standards and combine it with financial‑due‑diligence best practices to produce a one‑page risks‑and‑actions summary tailored to Czech regulatory realities and audit trails (see Diligent's guide and the Data‑Rooms FDD overview for templates and examples).

“What would you need to know from them that would help you in your risk model to know what to do from there? Do you need to do further screening, further investigation of them, or does that tell you what you need to know? That gives you a good foundation, but that comes from them,” said Diligent's Director, Operations Optimization Group Stephanie Font.

For Czech FP&A teams, a CCH Tagetik prompt should be built around three clear asks: produce a driver‑based 12‑month rolling forecast, generate multiple what‑if scenarios with cash‑flow implications, and return narrated insights plus visuals for stakeholders - all leveraging CCH Tagetik's Predictive Intelligence and “Just Ask AI” self‑service analytics so the output is ready for decision meetings rather than another spreadsheet clean‑up task (see CCH Tagetik budgeting, planning and forecasting capabilities).

Start the prompt by naming the forecast horizon, key value drivers (revenue per customer, headcount, FX exposure), required integrations (ERP, payroll, sales), and the sensitivity bands to test; ask for a one‑page executive summary, a scenario table and drillable charts.

This approach follows rolling‑forecast best practices: automation, focus on key drivers, and frequent updates so the forecast behaves less like a static map and more like a GPS that reroutes after every market “traffic jam” (rolling forecast best practices).

OneSumX can anchor a Pillar Two validation prompt that turns scattered entity ledgers into a defensible, auditable calculation flow for Czech tax teams: start by instructing the agent to gather per‑entity inputs (financials, taxes paid, adjustments and ownership data), run the Country‑by‑Country safe‑harbor checks, and then execute jurisdiction‑specific top‑up calculations so both OECD GloBE and each local law view are produced side‑by‑side - this mirrors the end‑to‑end approach recommended by Orbitax for automated Pillar Two compliance and Wolters Kluwer's OneSumX Pillar 2 capabilities (data, liquidity and regulatory reporting).

The prompt should enforce strict sequencing (QDMTT → IIR → UTPR) so calculations don't “step on” each other, auto‑populate the GloBE Information Return and local forms, flag mismatches between model and domestic results, and produce an audit trail for reviewers; EY and operational guides stress that reliable automation only works on standardized, high‑quality inputs, so include data‑mapping and validation steps in the prompt.

For Czech multinationals facing local rule divergence, the practical benefit is clear: a single, repeatable run that creates both global and country returns, tight version control, and a clear explanation of any deltas for tax authorities.

“AI drives the need for data standards, since confidence in the underlying data is essential to unlocking the value that AI can deliver.” - John Farrelly, EY Global Compliance & Reporting, Technology Leader

Settle Up prompts should turn messy group expenses into GL‑ready journals and a cash‑flow snapshot that Czech finance teams can trust - start by asking the agent to normalise vendor and account headers to the ERP template, validate required fields, and output both a loadable journal CSV and a reconciled cash‑flow summary for the consolidation period; use Ramp's custom CSV guidance to match column names and placement to the ERP import, and follow Zuora's export flow for well‑formatted summary journal entries so the file can be re‑imported or posted without last‑minute fixes.

Include checks for international bills and currency handling (Ramp supports foreign‑currency bills), enforce payment‑field completeness against Sage 50's payments journal field list, and set CSV separators/enclosures (semicolon or comma) as recommended in export tools to avoid misaligned columns - this removes the midnight scramble over headers and creates an auditable trail for reviewers.

Link the CSV export to a short mapping table and a versioned journal export so reviewers can replay the reconciliation step‑by‑step.

Google Cloud Agentspace - Post‑Merger Integration (PMI) Agent Orchestration Prompt: for Czech deal teams, design a prompt that spins up a coordinated agent pipeline - a cultural‑assessment agent to flag communication friction and recommend town‑hall scripts, an operations agent to map synergies and redundancies, a systems agent to propose migration paths and minimal‑downtime cutovers, an HR agent to identify critical roles and retention levers, and a risk agent that runs predictive checks and produces an auditable issue log - then have a supervisor agent orchestrate handoffs, timelines and a one‑page Day‑1 playbook so integration work is traceable and board‑ready.

Build the prompt using multi‑agent patterns (handoff, tool calls and event streams) shown in LlamaIndex AgentWorkflow multi-agent orchestration patterns so each agent emits streamable events for real‑time monitoring, adopt schema‑based agent memory and A2A handoffs like Kore.ai schema-based agent memory and A2A handoffs to preserve context across sessions, and require output formats (versioned migration scripts, KPI dashboard, GIR‑style reconciliations) that are importable into ERP or PM tools.

This approach mirrors the PMI agent benefits described in industry guides - automated cultural alignment, systems integration and risk prediction - while keeping a human reviewer in the loop for explainability; see Akira.ai primer on Post‑Merger Integration AI agents and LlamaIndex AgentWorkflow multi-agent orchestration patterns and Kore.ai implementation resources for implementation details.

For Czech finance teams the path from curiosity to trustworthy AI is practical and phased: begin with a focused pilot (think subledger reconciliations or a short‑horizon cash forecast) that proves value in weeks, lock in data governance and ERP integration so outputs are auditable, and run cross‑training so analysts can validate AI results rather than replace judgment - advice echoed across industry guides (see Vena's practical AI adoption checklist and Nominal's four‑phase rollout roadmap).

Measure wins, celebrate them, and expand: integrate agents into treasury, FP&A and tax only after you've standardised inputs and controls, and use a documented strategy (Microsoft's AI strategy guidance) to choose SaaS vs.

custom agent approaches. Upskilling matters: a staged learning plan plus a course like Nucamp's 15‑week AI Essentials for Work bootcamp gives finance pros prompt‑writing and human‑in‑the‑loop skills, while vendor playbooks and audits (see Vena's AI adoption guide and Nominal's implementation roadmap) keep rollout low‑risk - think small, measure hard, scale safely, and keep the CFO accountable for governance so AI becomes a tool that speeds decisions, not a black box that obscures them.

“With the right strategy, CFOs can create substantial benefits by deploying emerging technologies such as AI.” - Ronald Gothelf, Grant Thornton