Manish Garg is the cofounder and chief product officer at Skan.ai, a computer-vision-based process intelligence platform.
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Gartner researchers report that "47% of digital workers 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management repositories and digital adoption platforms (DAPs)—are often limited by poor search functions and outdated content. Although retrieval augmented generation (RAG) paired with large language models (LLMs) simplifies the search with its Q&A format, it still demands well-crafted input from users.
The current solutions are just not cutting it.
Enterprises seek a breakthrough: an AI agent that merges in-house expertise with on-demand insights, available 24/7 to deliver essential information without complex searches. Imagine instant access to targeted knowledge anytime, anywhere. It's an exciting journey ahead!
The Current State Of Knowledge Management And Accessibility
A lot of business and process knowledge is scattered and inaccessible. Consequently, employees spend precious time hunting for necessary information and updating outdated documents, reducing productivity.
The problem gets amplified in fast-paced and regulated industries like banking and insurance, in which outdated standard operating procedures (SOPs) fail to incorporate necessary updates for new systems, processes and regulations.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.
Knowledge Management Repositories: 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 This could be due to outdated data, large volumes, departmental silos or imperfect search queries.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instance, a compliance officer might not be able to access updated anti-money laundering (AML) guidelines because of an outdated knowledge system. This risks legal fines and damages the bank's reputation by missing illegal transactions.
Digital Adoption Platforms (DAPs): DAPs aim to simplify knowledge management software use by guiding users through its features. Yet, they can fall short when real-time, role-specific information is buried in outdated systems or obscured by industry jargon, making it even more challenging for new hires. For instance, even with DAPs, claims processing officers face delays in accessing the latest claims guidelines, leading to prolonged processing times and customer dissatisfaction.
Retrieval Augmented Generation (RAG): RAG systems offer a streamlined Q&A interface, letting users easily search by typing questions in plain English and integrating the latest enterprise documents. However, they demand users master "prompt engineering" to extract accurate information from extensive data pools.
Conclusively, new hires struggle without instant access to knowledge. Expert turnover without continuous updates erodes know-how, hurting customer service and business outcomes. Given these pervasive challenges, it's clear that a transformative approach is necessary—one that AI is uniquely positioned to offer.
Transforming Enterprise Knowledge Access With AI Agents
Before jumping into AI's potential, let's outline the ideal solution. It needs to:
• Offer immediate access to the latest information.
• Quickly uncover specific details from vast amounts of data.
• Remove the hassle of crafting complex searches.
• Understand precisely why knowledge workers need particular information, implying that the searches are context-aware.
• Constantly and automatically refresh enterprise knowledge with new insights and guidelines.
Can an AI agent actually deliver on these demands?
McKinsey researchers report that an AI agent can significantly boost knowledge accessibility by providing round-the-clock technical support, drawing on proprietary information such as policies, research and customer interactions. Here's how:
Intelligent Content Discovery: Leveraging machine learning and natural language processing, AI can automatically categorize, tag and index content across platforms. This not only improves searchability but also helps in uncovering hidden connections and insights within the vast amounts of data enterprises generate.
Unified Data Access: AI agents can be trained to understand and interpret data from diverse sources, offering a single access point to disparate knowledge bases. This unified approach simplifies the user experience, making it easier for employees to find what they need without navigating multiple systems.
Context-Aware Assistance: This AI agent integrates deeply with the user's workflow and automatically grasps the task's context. This way, a user can get precise, relevant knowledge snippets without typing extensive keyword-specific queries.
Updating Knowledge Bases: An AI agent could not only refer to existing documents but also update them based on new insights and user interactions, ensuring that the knowledge base remains current and accurate.
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. By delivering instant, relevant and personalized information, AI transcends traditional knowledge management system limitations, signaling a more informed, efficient and agile workforce.
Anything Incredible Has Its Fair Share Of Struggles
Transforming enterprise knowledge accessibility with AI isn’t a simple journey, but the destination—a workplace where information is instantly accessible without the hunt—can offer remarkable efficiency gains. Banks have already begun to realize AI’s truly transformative potential in enterprise knowledge accessibility. Morgan Stanley is creating a GPT-4 AI assistant to help its 16,000 wealth managers quickly pull and tailor data from an extensive internal database, streamlining personalized client information delivery.
Knowledge management ranks among the top three factors influencing the success of companies, yet a mere 9% of organizations surveyed by Deloitte researchers believe they're prepared to tackle this challenge. As we stand on the brink of this transformation, the urgency to embark on this journey has never been more pronounced. However, the road ahead is filled with technical and adoption challenges.
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