Across multiple industries, AI has been automating mundane tasks, enabling companies to make data-led decisions. This covers everything from risk assessment to targeting consumer interests. Advanced language models (LLMs) can analyse large and complex sets of data and then give a comprehensive list of summaries that companies can implement into their strategy.
In finance, AI has become an immensely valuable tool to analyse a large amount of market data at record speeds. This means that information from finance reports, earnings announcements, and market sentiment from news articles can be sourced more quickly than through traditional sourcing methods (spreadsheets, modelling, etc.).
It is not thought to be vastly replacing job roles yet, but AI has streamlined the decision-making process, enabling actions to be taken much faster and with greater analytical insight than ever before.
Let's explore a little more about how the finance industry has used AI for data analytics and to dictate its decision-making. We'll also take a look at some more recent trends, which show specific firms that have adopted AI to analyse data sources and identify patterns that can influence high-level decision-making.
In the finance industry, LLMs can help forecast market trends through ‘predictive analytics’. They process historical data from online news articles and global events. The complex financial research involved in this industry can be achieved at record speed with AI models. This kind of tracking is particularly likely to have an impact on CFD broker platforms, where speculation on the price movements of global financial products is essential.
Furthermore, AI can help with the risk assessment involved in finance. These systems monitor market trends to gauge price volatility and how global events can affect price movements. They will flag any unusual activities or transactional patterns that can help prevent financial crimes.
It can automate repetitive tasks like summarising financial reports and flagging unusual trading activity. This allows financial analysts to focus primarily on high-level strategy based on results generated by LLMs.
Finance companies are no longer experimenting with AI applications; it has become part of everyday procedures. According to Neudata's 2025 industry report, AI use amongst industry firms has doubled in the last year, based on 171 responses from global hedge funds.
AI has certainly transformed the way that companies make decisions. When research and risk tasks can be automated in minutes by LLMs, it leaves room for analytic decision-making based on clear data on market trends and consumer behaviour.
There are many examples of financial institutions actively implementing AI into their workflow. Most notably, Goldman Sachs launched an AI assistant across its firm that can help employees with everyday tasks.
The main focus on AI adoption is to increase productivity. Neudata’s 2026 Report stated that "66% of respondents said their firms are using AI/LLMs mainly for productivity and workflow efficiency." This shows that AI is not trying to replace human expertise but is used as a tool to support decision-making.
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