What Really Gets You Hired in Finance: Beyond the AI Hype

The fundamentals haven't changed—but how we apply them has evolved

Let's have some real talk about getting hired and promoted in finance. In an industry buzzing with AI and automation, it's easy to get caught up in the hype. But having spent years on both sides of the hiring table, I can tell you exactly what truly separates top-tier finance professionals from the rest. It's not just about knowing the latest tech; it's about mastering the timeless fundamentals and applying them with a strategic mindset. Prepare to look beyond the algorithms and discover the skills that truly make you indispensable.

The AI Reality Check

Artificial Intelligence is a game-changer, and it's essential to embrace it. I integrate AI into my daily workflow – it's phenomenal for accelerating formula generation, quickly summarizing large datasets, and sketching out initial analytical frameworks. It's an incredibly powerful aid.

But here's what I've observed: AI excels as an accelerator, not a replacement for fundamental competence And everyone is using ChatGPT that’s easy to see everyone using ChatGPT.  The professionals who leverage AI most effectively are those who already possess strong foundational skills and use AI selectively as a tool. They know what questions to ask, can spot errors in AI-generated outputs, and understand when to override automated suggestions.

Conversely, those who rely on AI as a crutch often produce work that looks sophisticated on the surface but crumbles under scrutiny. They struggle when asked to defend their assumptions or adapt their analysis to changing business conditions.

Excel: Still the Universal Language of Finance

Before you roll your eyes at another "Excel is important" argument, consider this: Excel isn't just about spreadsheets, it's about transparent analytical thinking.

When you build a financial model in Excel, every assumption is visible. Every calculation can be traced. Every relationship between variables is explicit. This transparency is crucial in finance, where stakeholders need to understand not just what the numbers say, but how you arrived at them.

What Excel Mastery Looks Like

Beyond Basic Functions:

• Dynamic array formulas and structured references

• Scenario modeling with data tables and Goal Seek

• Power Query for data transformation and automation

• Dashboard creation with conditional formatting and charts

Model Architecture:

• Modular design with clear input, calculation, and output sections

• Robust error handling and assumption testing

• Documentation that enables others to build upon your work

• Version control and audit trails

Business Application:

• Three-statement financial models that properly link P&L, balance sheet, and cash flow

• Sensitivity analysis that identifies key value drivers

• Variance analysis that highlights meaningful business insights

• Budget vs. actual reporting that tells a story, not just shows numbers

The candidates who excel aren't just Excel power user but they're business analysts who happen to use Excel as their primary tool.

Critical Thinking: The Differentiator

This is where many finance professionals stumble. They become proficient at manipulating data but struggle to generate insights. Critical thinking in finance means:

Pattern Recognition: Identifying trends, anomalies, and relationships that others miss Business Context: Understanding how financial metrics connect to operational realities Scenario Planning: Thinking through multiple potential outcomes and their implications Risk Assessment: Identifying what could go wrong and quantifying potential impacts Strategic Perspective: Connecting financial analysis to broader business objectives

Developing Your Analytical Edge

Ask Better Questions:

• Instead of "What are our margins?" ask "Why did margins change, and is this sustainable?"  “What is the root cause of the change?”

• Instead of "Are we on budget?" ask "What does our variance pattern suggest about our forecasting accuracy?"

• Instead of "What's our ROI?" ask "How does this ROI compare to alternatives, and what assumptions drive the result?"  “Where are we in terms of relative comparison?”

Challenge Assumptions:

• Test your models with extreme scenarios

• Validate data sources and understand their limitations

• Question whether correlations represent causation

• Consider what factors your analysis might be missing

Communicate Insights, Not Just Data:

• Lead with the business implication, then support with numbers

• Use visualizations that clarify rather than complicate

• Anticipate questions and address them proactively

• Recommend actions based on your analysis

The Attitude Factor: What Really Matters

Technical skills get you in the door, but attitude determines how far you'll go. The professionals who advance consistently demonstrate:

Intellectual Curiosity: They dig deeper when something doesn't make sense, rather than accepting surface explanations.

Ownership Mentality: They take responsibility for the accuracy and usefulness of their work, not just its technical correctness.

Collaborative Approach: They present analysis in ways that help others make better decisions, rather than showcasing their technical prowess.

Adaptability: They adjust their approach based on feedback and changing circumstances, rather than rigidly adhering to their initial methodology.

Professional Skepticism: They question assumptions (including their own) while remaining constructive and solution-oriented.

The Strategic Approach to Skill Development

Rather than choosing between traditional skills and new technologies, the most successful finance professionals integrate both strategically:

Foundation First: Master the fundamentals of financial analysis, accounting principles, and business strategy. Learn to think and set a structure so that your process is thought out and cohesive. We have a saying at our firm: People, process and then the tools. These provide the framework for using any tool effectively.

Tool Proficiency: Develop deep expertise in Excel, but also explore complementaryGain working knowledge of Power BI for interactive dashboards, SQL for extracting and manipulating data from databases, and Python for automating workflows and advanced analytics.

AI as Amplifier: Use AI to accelerate routine tasks and generate initial insights, but always apply critical thinking to validate and refine the output. Tools like ChatGPT, Copilot, Claude or domain specific AI to generate initial analyses or simulate scenarios.

Continuous Learning: Stay current with both technical developments and business trends in your industry.  Take online courses, look for certification programs, Subscribe to newsletters, follow thought leaders, join communities, and attend webinars or conferences.

What This Means for Your Career

For Job Seekers:

• Learn and demonstrate Excel proficiency—especially in dynamic arrays, Power Query, and scenario modeling (Goal Seek, Data Tables).

• Build a portfolio of financial models that show clarity, structure, and insight. Include three-statement models and budget vs. actuals.

• Practice walking through your problem-solving process and explaining the "why" behind your conclusions.

• Learn Power BI or Tableau to complement Excel with data visualization capabilities.

• Take AI tools like ChatGPT or Excel Copilot and use them to speed up modeling but validate outputs with critical thinking.

For Current Professionals:

• Take on challenging projects like sensitivity analysis or business case modeling to sharpen your financial storytelling.

• Seek feedback not only on technical precision but also on the strategic usefulness of your insights.

• Learn adjacent tools such as SQL for data extraction, Python for automation, or Power BI for visualization.

• Stay updated on finance trends, AI applications in FP&A, and industry-specific performance metrics.

• Use AI tools to enhance—not replace—your workflow. Think of AI as a co-pilot, not the driver.

For Managers:

• Assess team members and candidates based on their structured thinking and ability to explain assumptions.

• Encourage hands-on learning with tools like Excel, Power BI, SQL, and modern FP&A platforms like Datarails, Anaplan, or Planful.

• Promote a culture of asking better business questions, not just producing cleaner reports.

• Reward strategic thinking, ownership, and insight generation.

• Encourage team members to explore AI-enhanced processes but require validation and clarity in their outputs.

The future belongs to finance professionals who blend analytical thinking, business understanding, and tool proficiency. Learn the tools (Excel, Power BI, SQL, Python, ChatGPT), build insights, communicate clearly, and grow with the business.

The finance function is evolving rapidly, but the core requirement hasn't changed: we need professionals who can turn data into actionable business insights. This requires a combination of technical competence, analytical rigor, and business acumen that no AI tool can currently replicate.

Excel mastery, critical thinking, and a professional attitude are the foundation that make you valuable in an AI-augmented world. That's what gets you hired, and more importantly, that's what gets you promoted.