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Text Processing at Scale: The Hidden AI Opportunity0m 19s
BUILDINGCLIP

Text Processing at Scale: The Hidden AI Opportunity

Unlock text at scale: mine RFPs, contracts, and news to build capabilities that numbers‑only analytics miss.

Sep 29, 2025 0m 19s

Alan Buxton

Expert Insights

Alan Buxton reveals the often-overlooked potential of AI in text processing within business operations. He signals towards a common business process, Request for Proposals (RFPs), as a key area that could benefit significantly from AI application.

Exploring the theme of 'Building,' Alan suggests that a critical yet untapped area of opportunity in AI-assisted software development lies within text processing, handling, and deriving insights from non-numerical data such as texts in RFPs or news alerts related to a supplier.

Hear Alan explain:

  • The abundance and importance of non-numerical data (text) in business operations.
  • The potential for AI to streamline and revolutionize the processing and understanding of RFPs.
  • Real-world application, where AI can efficiently process and manage business-related news alerts.
There's a lot of it that is. Text that's not numbers... there's lots of RFPs. Everyone loves to hate RFPs, but they're a fundamental part of how we kind of do business... there's lots of stuff where, for example, you wanna pick up, um, news alerts related to a supplier.
— Alan Buxton, CTO, Simphony

THE NEW DEFAULT angle

Here's how software teams can leverage AI for text processing in business operations:

  • Identify opportunities for AI: Start by mapping tasks that involve heavy text processing, like handling RFPs, and assess where AI can create efficiencies.
  • Invest in AI skills: Ensure your team can handle natural language processing tasks; this will be a critical competency in implementing AI for text processing.
  • Brace for change: Prepare your team dynamics to align with a workflow where AI assists in text processing tasks.
  • Think beyond numbers: Consider AI not only for numerical data analysis but also for parsing, interpreting, and acting upon text-based data.
  • Implement in stages: Start implementing AI in handling less critical tasks like news alerts related to suppliers, learn from the journey, and gradually expand its usage.