Agentic AI · AI Agent · OpenAI · Elon Musk · xAI · MIT Technology Review
Data readiness for agentic AI in financial services
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Financial services companies have unique needs when it comes to business AI.
Key facts
- MIT Technology Review's authoritative overview of the 10 technologies, emerging trends, bold ideas, and powerful movements in AI in 2026
- Take any bank that's been around for 50 years: They might have 60 different types of PDFs for the exact same thing
- According to Stanford’s 2026 AI Index, AI is sprinting, and they're struggling to keep up
- A Forrester study found that 57% of financial organizations are still developing the necessary internal capabilities to fully leverage agentic AI
Summary
“It all starts with the data,” says Steve Mayzak, global managing director of Search AI at Elastic. Agentic AI—systems that can independently plan and take actions to complete tasks, rather than simply generate responses—holds enormous potential for financial services due to its ability to incorporate real-time data and optimize complex workflows. However, introducing autonomous AI into any organization magnifies both the strengths and weaknesses of the underlying data it uses. Financial services companies, therefore, require a trusted and centralized data store that is easy to access, dependable, and can be managed at scale.