We are in the midst of one of the most exciting and disruptive periods in history. AI is already having a huge impact on how people do work, and studies have shown that many jobs can now be performed by AI. This is a great opportunity for anyone likely to be affected: by learning to leverage AI you can become exponentially more productive.

Depending on your role and goals, how you leverage AI will look very different. You might need to understand the fundamentals to adapt it to your goals, or just need to understand how it could fit into the work you do to leverage it better. Skill acquisition will be key to staying relevant, and with an industry as fast paced as AI the sooner you start the better.

The Impact of AI on the Finance Industry

I've already written about the impact on the finance industry as a whole, so let's take a look at the impact on AI on work within the finance industry. As noted from the study above, there are several jobs that may experience a higher level of impact from AI and are likely to start feeling the effects first:

  • Quantative finance, or those who deal with numbers all day.
  • Writers and authors, including content marketers.
  • Web and digital interface designers.
  • Data processors, including software engineers.

The list above only focuses on jobs where over 50% of the work can be done by AI today, and over 50% can be 55% or 90%. Judging by the pace of AI development, this list will be a lot longer in 3 to 6 months.

There are ways right now to 10x or even 100x your productivity by embracing AI tooling and not trying to keep it out of your job. AI should be viewed as an enhancer and an extension of your own skills.

In-Demand Skills in the Age of AI-Driven Finance

We can split those who work with AI into two buckets: the makers and the users. The makers are the people who make the tools others use: data scientists, machine learning experts, and software engineers. The users are the people who integrate these tools into their workflows, and this category is so broad that almost every knowledge professional will eventually fall under this umbrella.

Skills for Makers

If you fall into the Maker category you can build a good baseline by focusing on the fundamentals of data analysis and machine learning, even at a high level. Understanding how data is collected and ingested, how models work, and the different implementation mechanisms are made available are key to providing any real lasting value. You can obtain this knowledge through courses like this one from Databricks.

Depending on your focal area, you might need to delve a little deeper. This will likely involve more math and a better understanding of exactly how the models work. If this is more your focus area, books like Hands-On Machine Learning are great resources to start with.

Skills for Users

Understanding the concepts behind machine learning and the strengths and limitations of data will provide a solid foundation to start from. Not only will it help you understand where the tooling is now, but you can also more accurately estimate where it might go in the near and mid-term future.

The best way to understand how to use the tooling is to start using it. Get an account on Midjourney, sign up to ChatGPT and find a specific AI tool on TheresAnAIForThat. Start using it for anything and everything and find where it shines and where you need to offer extra guidance.

Continuous Learning

We are moving so quickly that you now have to actively set aside time to learn to stay up to date. For makers this learning time is reading articles on Arxiv and trawling Github, for users this is using the tools and seeing what they are capable of. This will likely easily form a part of your normal working day and an active focus on using and learning AI will pay massive dividends: not that many people are leaning into AI, and if you do you'll quickly find yourself one of the most knowledgable.


AI will change the way we work and it's main impact will be a vast increase in productivity. The people who build these systems and the people who use these systems both have an incredible opportunity to find themselves leading discussions and development through active focus. With the great resources available, it's more a matter of a shift in focus on using or investigating AI in day-to-day activities to get to grips with the capabilities. What impact would doubling or tripling your output within a few months by leveraging AI have on your career?