Remember how the world was taken aback by the sheer power of generative AI when ChatGPT was launched? That was the moment when AI became more than a buzzword—from a thing of the future into our current reality.
Since then, tools like ChatGPT have become mainstream, and new AI tools aimed at optimizing efficiency across industries and organizational departments are popping up as we speak.
The domain of analytics is no exception.
AI-enhanced analytics uses machine learning to quickly turn complex, unstructured business data into clear, actionable insights.
Marry AI with analytics, and you gain the ability to efficiently comb through extensive data, spot trends, and refine processes. This marriage leads to better, quicker decisions across various business operations, from financial strategies and supply chain management to customer service.
Keep reading to explore three concrete examples of AI-enhanced analytics in action.
Enhancing Financial Decision Workflows
Financial planning, forecasting, risk management—these are some of the areas where AI is making a dent. Think more efficiently and faster, data-backed decisions.
Small businesses and even individuals are starting to embrace new finance-focused AI tools.
Intuit, for instance, recently launched Intuit Assist. It is an AI-based tool that helps entrepreneurs and your average Joe make smarter financial choices. It works across various Intuit products like QuickBooks and Mailchimp. It uses data from business transactions, consumer accounts, and tax filings to provide personalized financial insights.
Intuit Assist automates complicated tasks and offers custom advice. It connects users with experts if needed, making financial management easier for those without a finance background.
AI is changing how we make financial forecasts and conduct risk assessments. Banks and financial firms are upgrading their tech stack to use AI models for analyzing ginormous data sets. This helps them better understand credit risks and respond to market changes.
Citibank, for example, uses AI to check financial statements during the loan approval process, improving its assessment of credit risks. ZestFinance uses AI to analyze non-traditional data, helping people with little credit history get better credit scores.
Major investment firms like Citadel use machine learning to assess and adjust investment risk strategies. BlackRock uses AI to analyze data for trading and risk management, and has even set up a special team, “AI Labs,” to dig into more cool stuff AI can do.
This increasing AI-driven approach in firms across the board hints at how financial decision workflows are leveling up for better precision.
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