Written by: John Fourness
In a world powered by machines, artificial intelligence is taking things by storm. Artificial intelligence has been a topic of excitement, skepticism, and fear since the 1950s. However, with the release of ChatGPT, an LLM with 750 million weekly active users, things are reaching a tipping point. This new technology has already become intertwined in our daily lives, and its advancement has profound implications for the financial market.
Corporations are pouring money into research. AI investment reached $252.3 billion in 2024. Private investment has also risen by 44.5% and mergers and acquisitions by 12.1% from the previous year (Stanford University, 2025). Clearly, the role of AI in the economy is quickly accelerating. Companies are prioritizing investments in AI because of its ability to optimize tasks and improve efficiency. For starters, generative AI is already being used by companies like Google, Microsoft, Wayfair, and Citibank to automate certain tasks and elevate productivity in the workplace. Finance is one field with a very high potential to take advantage of AI, due to much of the industry revolving around processing and understanding data. What this means for investors is that AI is a must-have asset, with a high long-term profit but short-term volatility.
The effect of AI can already be felt today. According to the International Monetary Fund (IMF, 2025), AI in the form of machine learning and neural networks has been used by cutting-edge investment firms for at least ten years. This means that AI has already been impacting the financial markets. As of today, AI plays a crucial role in the automated and high-speed trading that dominates most of the financial markets. A Gartner survey showed that in 2024, 58% of finance functions already use AI, which is a 21% rise from 2023 (Gartner, 2024). As AI continues to develop, more and more finance leaders begin to lean into its possibilities. On top of this, despite 42% of finance functions not using AI, almost all of them have plans to implement it in the near future. Implementing AI in the workspace is not that simple as it involves costs of data acquisition, infrastructure, talent, maintenance, compliance, and model development. The cost of AI automation can range anywhere from $10k for small automation to $10M+ for Enterprise AI (Trotolo, Hayat, & Hayat, 2025). As part of its latest U.S. AI pulse survey, EY queried decision-makers across a range of industries and found that 21% of senior leaders say their organizations have invested $10 million or more in AI, an increase of 16% from the previous year. Roughly 33% anticipate spending at least $10 million on AI in the coming year (Violino, 2025).
When people talk about AI, they often think of jobs being replaced; however, AI is also creating many new job opportunities. AI-related job postings have grown at an annual rate of nearly 29% over the past 15 years; this outstrips the 11% rate of postings in the general economy (Cunningham, 2025). Due to AI’s high potential, companies are eager to bring in anyone who can help them understand and use it. According to Indeed (2025), the average Machine Learning Engineer salary in the United States is roughly $176k-well above the average. Machine learning is a very lucrative industry, and it’s only expected to grow. But it is also very fluid. The definition of an “AI job” changes every day as businesses find more and more ways to incorporate AI into their workspaces. The market for AI is constantly being redefined due to rapid shifts in technology and the competitive nature of the market. On top of this, despite many companies pouring money into AI, vast numbers of people still barely understand it. The long-term potential is high, but it’s unclear what the returns will be in the near future. While nearly every company is investing in AI, only 1% of companies have fully integrated AI into workflows and can drive substantial business outcomes (Mayer, Yee, Chui, & Roberts, 2025). This is because these companies have to make a hard decision: jump into an unknown field to remain competitive, or risk losing their edge altogether.
AI’s long-term potential is too high for companies not to take risks today. By 2027, global IT spending associated with AI software, hardware, and services is expected to reach $521 billion, and by 2030, AI could contribute up to $15.7 trillion to the global economy (Merrill Lynch, 2025). According to Haim Israel, the head of Thematic Investing for BofA Global Research: “The U.S. and China, already the world’s two largest economies, are likely to experience the greatest economic gains from AI.” China and North America are expected to account for 70% of the global economic impact of AI by 2030 (Merrill Lynch, 2025, para. 3). These statistics all suggest that AI is becoming a core driver of economic growth, and it is positioned as one of the largest economic forces of the coming decades. These numbers suggest that AI will not only help existing industries operate more efficiently, but it suggest that productivity, efficiency, and innovation will be redefined across the global economy (Merrill Lynch, 2025). Companies are going to be forced to invest in this field; if they do not, they risk losing their competitive edge and falling behind. This will have serious implications for the financial market.
Overall, AI is not a new concept, but it is rising at an unprecedented rate. It has already had a major impact on the financial market, which is only subject to an increase in the following years. As more and more companies lean towards AI’s possibilities, expect to see more and more of it in your day-to-day life.
References
Adrian, T. (2024, September 6). Artificial Intelligence and its impact on financial markets and financial stability. Artificial Intelligence and its Impact on Financial Markets and Financial Stability. https://www.imf.org/en/News/Articles/2024/09/06/sp090624-artificial-intelligence-and-its-impact-on-financial-markets-and-financial-stability
AI Index Steering Committee. (2025, April 7). Economy: The 2025 AI index report: Stanford Hai. The 2025 AI Index Report. https://hai.stanford.edu/ai-index/2025-ai-index-report/economy
Cunningham, M. (2025, July 24). Job listings looking for people with AI skills are Rising fast. Job listings looking for people with AI skills are rising fast. https://www.cbsnews.com/news/ai-job-postings-brookings-lightcast
Gartner. (2024, September 11). Gartner Survey Shows 58% of Finance Functions Using AI in 2024. Retrieved September 25, 2025, from https://www.gartner.com/en/newsroom/press-releases/2024-09-11-gartner-survey-shows-58-percent-of-finance-functions-use-ai-in-2024.
Mayer, H., Yee, L., Chui, M., & Roberts, R. (2025, January 28). Superagency in the workplace: Empowering people to unlock AI’s full potential. Superagency in the workplace: Empowering people to unlock AI’s full potential. https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/superagency-in-the-workplace-empowering-people-to-unlock-ais-full-potential-at-work
Merrill . (n.d.). How will the AI revolution impact the economy and markets?. Artificial intelligence: A real game changer. https://www.ml.com/articles/economic-impact-of-ai.html
Trotolo, F., Hayat, H., & Hayat, D. (2025, February 26). The cost of implementing AI in a business: A comprehensive analysis. The Cost of Implementing AI in a Business: A Comprehensive Analysis. https://www.walturn.com/insights/the-cost-of-implementing-ai-in-a-business-a-comprehensive-analysis
Violino, B. (2025, September 24). Companies are spending big on agentic AI without always knowing what it does. CNBC. https://www.cnbc.com/2025/09/24/generative-ai-spending-investment-bubble.html
Wallpoper. (2013a). Pure mathematics formulæ blackboard. File:Pure-mathematics-formulæ-blackboard.jpg. Wikimedia Commons. Retrieved October 14, 2025, from https://commons.wikimedia.org/wiki/File:Pure-mathematics-formul%C3%A6-blackboard.jpg.