Artificial intelligence (AI) is firmly embedded in the financial services industry, transforming how companies operate, manage risk and engage with clients. As financial institutions continue to adopt AI at scale, they enhance their potential to gain efficiency, reduce operational costs and improve decision-making.

One thing is clear: Firms that integrate AI effectively will be better positioned for long-term success, while those that resist adoption risk obsolescence. Below, we explore some of the key challenges AI is solving within financial services and why strategic adoption will be a critical competitive differentiator.

AI as a problem-solver

Given the vast amount of data financial institutions manage, AI-driven solutions are increasingly being used to extract insights and streamline operations across business units.

Customer service and sales enablement: AI-powered tools are enhancing customer engagement through natural language processing and real-time data analysis. Financial advisors and client service teams can use AI to anticipate customer needs and provide personalized recommendations. For example, AI-driven call center solutions can analyze live conversations and prompt representatives with relevant information, leading to more efficiency and customer satisfaction.

Risk management and compliance: AI-powered surveillance tools are playing a growing role in detecting fraudulent transactions, identifying compliance violations and monitoring market anomalies. Many firms are leveraging AI to enhance trade surveillance, with platforms like Behavox analyzing trader jargon to detect misconduct and Global Relay developing AI systems capable of deciphering coded messages that use emojis and informal language.¹

Investment research and portfolio management: Analysts are using AI to extract insights from earnings transcripts, market reports and regulatory filings in minutes rather than hours. AI-driven research tools are also being used to identify patterns in market data and generate investment ideas. By leveraging AI, analysts can cover more names and conduct more comprehensive research, ultimately enhancing their ability to discover opportunities and make informed decisions.

AI’s horizontal applications across financial services

AI is driving innovation in every corner of financial services. In retail banking and credit, AI is enhancing loan underwriting by analyzing alternative data sources, enabling banks to expand access to credit and more effectively manage risk. In wealth management, AI-driven tools are helping advisors deliver more tailored financial planning and investment strategies by leveraging predictive analytics to assess client needs and optimize portfolio recommendations. Meanwhile, in insurance and actuarial science, AI tools are significantly improving fraud detection and automating claims processing.

Despite its widespread applicability, AI’s impact will vary widely depending on how well firms integrate AI into their workflows. Firms must continuously learn to interact with AI systems effectively as they evolve, particularly in terms of prompting AI models and refining queries to generate more useful outputs.

The competitive edge

AI adoption is a competitive necessity for financial institutions. One of the most immediate benefits is cost efficiency, as AI allows firms to reduce operational expenses by automating high-volume, repetitive processes. For example, a major investment bank recently disclosed that AI now generates 95% of its IPO documentation.²

Beyond efficiency gains, AI is proving to be a powerful tool for enhancing decision-making. A recent study conducted by researchers at the University of Chicago and MIT found that while AI benefits all investors, the most experienced market participants gain the greatest advantage:³

• For forecasting earnings, AI improved prediction accuracy by 18% for sophisticated investors but only 7% for less experienced users.
• In stock selection, AI-driven tools increased portfolio returns by 9.6% for sophisticated investors, compared to just 1.7% for less sophisticated participants.

The gap appears to stem from sophisticated users’ ability to ask higher quality questions, structure their interactions with AI tools effectively and interpret complex financial information more efficiently. These findings reinforce an important reality: AI does not replace expertise — it amplifies it.

The bottom line

Across the board, AI adoption should be viewed as a key indicator of long-term competitiveness in the financial services industry. Those who align with firms embracing AI systems are poised to gain a significant advantage.

¹ The Wall Street Journal, “Can a Computer Learn to Speak Trader?” January 2025.

² Forbes, “Goldman Sachs CEO says that AI can draft 95% of an IPO prospectus in minutes.” January 15, 2025.

³ University of Chicago, “AI, Investment Decisions, and Inequality.” December 2024.