AI is upending traditional finance processes, redefining how data-intensive tasks are managed. As automation takes over routine work and algorithms handle the heavy lifting of data analysis and prediction, finance professionals are increasingly stepping into strategic roles.

But that’s not the whole story, this new era in finance demands new skills. To thrive in a landscape where AI handles the data grind, finance professionals must now bring deep industry expertise, a strategic mindset, and a foundational grasp of AI-powered tech tools and data science – the new essentials for guiding AI-driven insights and making high-stakes decisions with confidence.

The criticality of industry expertise and AI

AI is fantastic at processing data efficiently, but it lacks the nuanced understanding required to interpret results within specific industry contexts. With specialised knowledge, finance professionals can add valuable insights to AI applications, guiding their use in ways that AI alone cannot achieve.

Some examples of why industry expertise matters in AI:

  • Manufacturing finance: Professionals with knowledge of production processes and supply chains can better interpret AI insights to optimise efficiency and reduce costs.
  • Retail finance: Understanding customer behaviour trends enables finance teams to leverage AI-powered sales analytics for better decision-making.
  • Healthcare finance: Expertise in regulatory frameworks and patient care processes ensures AI tools are used effectively to improve financial planning and resource allocation.
  • Financial services: Deep knowledge of market trends and regulations allows finance professionals to apply AI insights in a way that aligns with industry standards and risk management.

This blend of industry knowledge and AI is a powerful combination with humans and machines together turning raw data into actionable insights that create a durable competitive advantage from day one.

Foundational finance expertise still matters

AI is undoubtedly changing the game in finance, but the fundamentals still count. Finance professionals still need a solid grip on things like financial planning, revenue recognition, and compliance to make sure AI outputs actually line up with the organisation’s strategy and standards.

Take revenue forecasting as an example. AI might churn out predictions based on historical data, but the finance pros still have to step in to sanity-check those numbers. This could include factors AI might miss, like an upcoming product launch or shifting market conditions.

Yes, AI can handle a lot of the grunt work, but humans are still the ones who make sure the insights it delivers are useful and relevant. In the end, it’s that foundational expertise that keeps everything tied to the bigger financial picture and long-term goals.

Basic coding and automation skills

As AI continues to make its mark in finance, knowing some basic coding will become pretty much essential. With these skills, finance teams can act more autonomously as they automate repetitive tasks, speed up workflows, and free up time to focus on more important work. Plus, knowing how to tweak AI processes means you won’t always have to rely on tech experts to make things work for your team.

Some key skills that should be in your radar:

  • Python: Used for general-purpose automation, data handling, and building custom AI workflows.
  • R: Ideal for statistical analysis and data visualisation, helping to make sense of large datasets.
  • ERP platforms (e.g., NetSuite APIs): Allows finance teams to integrate AI-driven processes with existing financial systems for seamless operation.
  • SQL: Essential for querying and manipulating data in relational databases, enabling finance teams to extract and analyse large datasets.
  • Data cleaning and preprocessing: Before using AI, cleaning and preparing raw data will assure more accurate results.
  • Machine learning basics: Understanding the basics of machine learning can help finance professionals apply AI more effectively, from predictive analytics to anomaly detection.
  • Version control (e.g., Git): Useful for managing code changes and collaborating on projects within a finance or tech team.

Data visualisation and storytelling

Data visualisation and storytelling are quickly becoming must-have skills in finance, especially with AI generating ever more complex insights. It’s not so much about crunching numbers anymore - it's about turning those numbers into clear, actionable stories that resonate with decision-makers. When finance professionals can present data insights in compelling and interesting ways, they’ll be better able to drive influence strategy and action across the organisation.

Data science acumen

For finance teams looking to get the most out of AI, data science knowledge will be incredibly useful. You don’t need to become a data scientist - just understanding the basics can help you make AI work smarter for you. With a handle on concepts like regression for forecasts or time series analysis for tracking trends, finance professionals can navigate predictive models with more confidence. Think of it as having the right toolkit to validate outputs, forecast more accurately, and catch anomalies in payment and expense data before they become bigger issues.

The people factor

It's clear that AI and tech skills are becoming big players right now, but there’s one more thing worth noting - people skills are important too. Yes, finance teams need to know how to navigate AI tools, but strategic thinking, communication, and adaptability will build on that impact.

AI can crunch numbers and highlight patterns, but it’s up to you to interpret those insights and connect the dots with your business’s bigger goals.

Having strong people skills means you’re not only better at presenting complex AI insights to stakeholders but also more effective in collaborating across departments.

This comes in handy in several areas:

  • Using AI insights to align with long-term business goals.
  • Presenting AI-driven data in a way that’s clear and actionable for stakeholders.
  • Collaborating effectively across departments to implement AI solutions.
  • Turning AI insights into actionable strategies that drive growth.

In short, you’re the bridge between what the AI can do and how it drives results, making finance a real engine for strategic growth.

Leading the AI-ready finance function

Today’s finance professional is a strategic advisor, powered by AI. By building a solid mix of traditional finance know-how and essential AI skills, you’re prepping for a future where AI plays an even bigger role in strategy and decision-making. Investing in these skills now means you and your team will be ready to adapt, innovate, and help lead your organisation forward, turning finance into a true powerhouse for growth and resilience.

 

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