Sarah Hoffman is a Senior AI Evangelist at AlphaSense.
Have you ever said “please” or “thank you” to ChatGPT or Gemini? Recently, OpenAI stated that chatting with AI like a person can lead to misplaced trust, and the high quality of GPT-4o voice may worsen this effect. Even without voice, these systems are very responsive and seem to “understand” users’ needs, leading some people to treat them almost like humans. We see this trend across different industries, applications, and even personal relationships, such as the ability to marry AIand beyond interpersonal relationships, such as view AI as a higher power. But AI is not human. It is based on data, algorithms and code. Although AI can mimic human interactions, it does not possess intuition, emotions, or the ability to make moral decisions.
However, with the help of a human, it can be an extremely valuable tool. At AlphaSense, we have seen the immense demand for AI-powered generative search. Since launching our first generative AI feature in 2023, customers have reported saving an additional 11-50 hours per month. McKinsey estimates Generative AI will add over $200 billion in value for the banking sector, and 43% of financial services companies use generative AI.
Does this mean we should start seeing AI as a colleague, capable of handling daily tasks just like a human?
Keeping AI in Check
Imagine a seasoned financial analyst faced with a complex market decision. Next to them, an AI system quickly sifts through data and makes predictions within seconds. While it’s tempting to rely entirely on AI, there’s a nagging feeling that something isn’t adding up – a geopolitical event, perhaps, or an emerging market trend that hasn’t been fully quantified . This scenario highlights one of the biggest risks of anthropomorphizing AI: overreliance.
Finance teams need large amounts of data to guide their success, and it’s critical to leverage generative AI that can not only generate, but extract insights from that data. That said, AI lacks the contextual understanding and critical thinking that finance professionals bring. How can we exploit the advantages of AI without falling into this trap?
Financial institutions need a structured approach to implementing AI. First, it is crucial to clearly define the role of AI. Rather than viewing AI as a replacement for human workers, teams should view them as powerful tools that enhance human capabilities. Start by identifying specific, well-defined tasks that AI can handle and implement a regular review process. AI must be monitored and its results audited regularly to ensure its accuracy and reliability. Training your team is just as important. Finance professionals need to be trained not only on how to use AI, but also when to trust its recommendations and, most importantly, when to trust their own judgment.
What Generative AI Can Do for Finance Teams
While AI should not replace human decision-making, it is incredibly effective at completing routine tasks that free up time for more strategic and creative work. Additionally, generative AI can drive innovation and accelerate learning in ways once thought impossible. Some examples:
Streamlining data analysis for investment decisions: Think about the flood of financial data, including broker research, global news events and earnings calls. Generative AI can process this information at lightning speed, highlighting trends and key insights that might take analysts days to discover. At AlphaSense, our AI capabilities complement premium, pre-verified content so users can not only discover information quickly, but also have peace of mind that the information they see is trustworthy and reliable. In a high-stakes industry, neither speed nor accuracy should be sacrificed.
Stimulate creativity and innovation in investment strategies: Generative AI can serve as a powerful brainstorming tool for finance professionals, helping to generate new ideas and perspectives. AI can simulate various market scenarios, analyze historical trends or identify patterns that human analysts might miss, thereby sparking new ideas for investment approaches and highlighting potential risks.
Accelerate financial learning: Generative AI can also serve as a personalized tutor, quickly synthesizing complex financial information, news, regulatory updates, and market intelligence to help professionals keep up. For example, rather than simply analyzing data, AI can analyze emerging trends, explain the impact of new regulations, or summarize key points from lengthy reports. AlphaSense’s first generative AI tool, Smart Summaries, is one example. The tool provides highly accurate summaries of millions of documents from equity research, company filings, event transcripts, expert calls, news, trade journals and content customers. This allows financial professionals to quickly grasp new concepts, deepen their expertise in specialized areas and expand their knowledge in an ever-changing industry.
A tool, not a teammate
AI is here to stay and its role within financial institutions will only expand. But as powerful as generative AI is, it remains a tool, not a teammate. By recognizing the limitations of the technology, establishing clear guidelines for its use, and training teams on how to collaborate effectively with AI, institutions can take full advantage of the potential of generative AI.
As we move forward into the AI era, financial institutions have the opportunity to become more efficient and innovative. Understanding where AI fits (and where it doesn’t) in team dynamics is an important step in driving long-term growth. The future of AI is not about making it human, but about using it to enhance our own human creativity and strategic thinking.