GenAI Doesn't Replace Your Job: It Enhances It — How to Leverage AI in Finance and Data

Generative AI is getting a lot of attention. Some predict the end of many jobs, while others see it as a positive revolution. The reality, especially in finance and data, is more nuanced: GenAI doesn't replace your job, it amplifies it.

Generative AI: Threat or Opportunity?

What AI Does Well

Generative AI excels at certain tasks:

• Writing: emails, reports, documentation
• Analysis: data synthesis, pattern detection
• Automation: repetitive and codifiable tasks
• Assistance: answering questions, explanations

What AI Doesn't Do (Yet)

However, it has clear limitations:

• Business judgment: understanding business context
• Decision-making: arbitrating between options
• Relationships: negotiating, convincing, influencing
• Accountability: taking responsibility for consequences

Concrete Use Cases in Finance

1. Financial Document Analysis

Before: Manual reading of annual reports, extracting key figures

With GenAI: Upload the PDF, get a structured summary in seconds

Example prompt:
"Analyze this annual report and extract:
- Key financial indicators
- Mentioned risks
- Growth prospects"

2. Writing Management Commentary

Before: Manual writing of variance analyses, considerable time spent

With GenAI: Generate a first draft based on the data

Example prompt:
"Write a management commentary explaining
a +15% variance in personnel costs,
knowing there were 3 new hires and an exceptional bonus."

3. Data Model Documentation

Before: Tedious technical documentation, often neglected

With GenAI: Automatic documentation generation

Example prompt:
"Document this DAX measure by explaining
its business logic and use cases."

4. Creating DAX/Power Query Formulas

Before: Google searches, forums, trial and error

With GenAI: Formula generation from description

Example prompt:
"Create a DAX measure that calculates year-over-year growth rate,
handling the case where the previous year is zero."

Available Tools

Microsoft Copilot

Integrated into the Microsoft 365 ecosystem:

• Copilot in Excel: data analysis, formula creation
• Copilot in Power BI: visual generation, enhanced Q&A
• Copilot in Teams: meeting summaries, action tracking

ChatGPT and Claude

For various tasks:

• Document analysis
• Content writing
• Code assistance (Python, DAX, SQL)
• Brainstorming and structuring

Specialized Finance Tools

Emergence of dedicated solutions:

• Automatic account analysis
• Anomaly detection
• AI-assisted budget forecasting

How to Adopt AI Properly

1. Start with Low-Stakes Tasks

• Documentation
• First drafts
• Information research

2. Develop Your Prompting Skills

A good prompt = better results

Weak prompt: "Make me a financial report"

Effective prompt: "You are a senior controller. Write a budget variance analysis for Q3, structured by expense type (personnel, purchases, overhead). Highlight the 3 main variances and propose corrective actions."

3. Keep Humans at the Center

AI generates, you validate:

• Check the numbers
• Correct approximations
• Add your business expertise
• Take final responsibility

4. Train Your Teams

Don't let AI be an "underground" topic. Organize:

• Discovery sessions
• Best practice sharing
• Usage guidelines

Risks to Manage

Confidentiality

Be careful with sensitive data:

• Don't share confidential data on public ChatGPT
• Prefer enterprise versions (Azure OpenAI, Copilot)
• Define a clear usage policy

Hallucinations

AI can invent information:

• Always verify facts
• Cross-reference with your sources
• Be wary of "too precise" numbers

Dependency

Don't lose your fundamental skills:

• Continue thinking for yourself
• AI is an accelerator, not a crutch
• Maintain your critical thinking

The Future of Finance + AI

Professionals who will succeed are those who:

1. Master their profession: technical and sector expertise
2. Use AI effectively: as a productivity multiplier
3. Keep humans at the center: judgment, decision, relationship

AI doesn't eliminate finance jobs, it transforms tasks. Analysts will spend less time on data extraction and more on strategic analysis.

Conclusion

Generative AI is a tremendous opportunity for finance and data professionals. It frees you from repetitive tasks to focus on what really matters: analysis, decision-making, added value.

Don't fear it, tame it. Those who know how to use it intelligently will have a major competitive advantage.

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