Generative AI tools like ChatGPT, DALLE-2, and CodeStarter have gained popularity in 2023. OpenAI’s ChatGPT has reached 100 million monthly active users within two months of its launch, becoming the fastest-growing consumer application. McKinsey predicts that generative AI could add trillions of dollars annually to the global economy, with the banking industry expected to benefit the most. However, widespread adoption of generative AI in financial services faces challenges including nascent deployment, legacy technology, talent shortages, regulatory hurdles, and validating complex output.
Unlocking the Value of Generative AI in Financial Services
Generative AI has become a hot topic in 2023, with tools like ChatGPT, DALLE-2, and CodeStarter gaining popularity. OpenAI’s ChatGPT, in particular, has seen rapid adoption, surpassing TikTok and Instagram in terms of user growth. McKinsey predicts that generative AI could add trillions of dollars to the global economy, with the banking industry being one of the sectors that could benefit the most.
However, businesses need to separate the hype from the real value that generative AI can bring. In the financial services industry, where digital tools are already widely used, the impact of generative AI is starting to be felt. Companies are using generative AI to automate repetitive tasks and free up employees for more valuable work.
While there is ongoing experimentation with more disruptive generative AI tools, commercial deployment is still limited. Practical and regulatory challenges need to be addressed before these tools can be fully utilized. Legacy technology and talent shortages may also slow down adoption, but these obstacles are temporary and can be overcome.
One of the main challenges is the need to train models specific to each company’s requirements, which requires time and investment. Additionally, validating the output of generative AI and addressing issues of bias and accountability are important considerations. Regulatory authorities are studying the implications of generative AI, and approval processes may take time.
To leverage the value of generative AI, financial services companies should focus on identifying automation opportunities, defining measurable KPIs, selecting AI solutions that align with their needs, and implementing AI gradually through pilot projects and data gathering.
If you’re looking to evolve your company with AI and stay competitive, consider finding value in generative AI for financial services. Connect with us at hello@itinai.com for AI KPI management advice and stay updated on leveraging AI through our Telegram channel t.me/itinainews or Twitter @itinaicom.
Practical AI Solution: AI Sales Bot
One practical AI solution to consider is the AI Sales Bot from itinai.com/aisalesbot. This tool is designed to automate customer engagement 24/7 and manage interactions throughout the customer journey. Discover how AI can redefine your sales processes and customer engagement by exploring solutions at itinai.com.
List of Useful Links:
- AI Lab in Telegram @aiscrumbot – free consultation
- Finding value in generative AI for financial services
- Artificial intelligence – MIT Technology Review
- Twitter – @itinaicom
