Manish Garg is the cofounder and chief product officer at Skan.ai, a computer-vision-based process intelligence platform. Read Manish Garg's full executive profile here.
struggle to find the information needed" for day-to-day business operations, highlighting a critical gap in knowledge accessibility. Current tools—knowledge management repositories and digital adoption platforms —are often limited by poor search functions and outdated content. Although retrieval augmented generation paired with large language models simplifies the search with its Q&A format, it still demands well-crafted input from users.
The problem gets amplified in fast-paced and regulated industries like banking and insurance, in which outdated standard operating procedures fail to incorporate necessary updates for new systems, processes and regulations. The need for a more sophisticated solution becomes apparent as we explore the limitations inherent in current knowledge management tools.
According to Deloitte researchers, 29% of users struggle to find vital information. This could be due to outdated data, large volumes, departmental silos or imperfect search queries. For instance, a compliance officer might not be able to access updated anti-money laundering guidelines because of an outdated knowledge system. This risks legal fines and damages the bank's reputation by missing illegal transactions.
To fully appreciate AI's impact on enterprise knowledge accessibility, let's explore a practical application: customer onboarding in financial services. The AI agent instantaneously equips financial advisors with critical, up-to-the-minute compliance regulations, client risk profiles, market trends and tailored investment insights. Recognizing the specific context of onboarding, the AI eliminates manual searches, ensuring advisors are effectively briefed with precise, actionable data.
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