How to transform KM for downstream benefits with M-Files, Verint, and NICE

The implications of leveraging AI and automation for KM are expansive, promising streamlined workflows, enhanced collaboration, better search results, reduced errors, and more. When used in tandem, KM is transformed for the better—and when KM is better, everything is better.

Experts from M-Files, Verint, and NICE joined KMWorld’s latest webinar, Faster, Smarter, Scalable KM: Leveraging Knowledge Automation and AI, to examine the ways in which the power of KM can be unlocked with leading AI technologies and best practices.

To begin, Daneen Storc, senior product marketing manager, M-Files, defined knowledge work for viewers, explaining that, “Knowledge work is done by employees that adds long-term value to an organization. It significantly improves a project…it involves critical thinking; it's our workers that have skills that merge fact-finding with creative thinking to solve complex problems.”

While the importance of knowledge work is undoubted, and “despite the proliferation of tools on the market, including AI, we know that 41% of knowledge workers’ time is still spent on non-value-added tasks,” said Storc. M-Files works to bridge that gap, solving the challenges of manual processes with AI and end-to-end automation that transforms knowledge work.

However, Storc pointed to the fact that most AI initiatives fail in the enterprise. To transform knowledge work with AI, a suitable, strong foundation must be in place from which AI can succeed.

“Do you know what knowledge you’ve captured? If you’re not quite sure of that, that means your AI isn’t sure either. AI can’t deliver helpful answers if your data is messy,” explained Storc.

There are three tenets that define a strong foundation for AI, according to Storc:

• Curation: AI should only access relevant and up-to-date information to ensure accuracy of responses.
• Context: AI needs to understand the right information resources to provide real value, the related content.
• Confidentiality: AI must comply with the organization's information security policy and must not disclose information to which the user is not entitled.

John Chmaj, senior director, KM strategy, Verint, introduced the variety of ways that Verint is enhancing the knowledge delivery lifecycle with AI. Achieved through bots, or microservice workflow entities that deliver content through KM systems across various tasks, Verint offers automations that streamline several different knowledge interactions, such as:

• Self-service with the knowledge answer bot that assists in centralizing knowledge for IVA and the knowledge automation bot for web/mobile devices
• Assistant service with the knowledge transfer bot for chat and email interactions and the Verint Agent Copilot for phone interactions
• Knowledge worker workflows with the knowledge automation bot for AI-powered search and the knowledge creation bot for content ingestion and curation

“All of these applications work through an AI-driven insights bot, which brings information together into a common view and allows you to ask natural language questions, create dynamic dashboards, and do a lot of very powerful things across these channels and across information sources,” explained Chmaj.

Chmaj then walked webinar viewers through several examples where each of Verint’s bots work together to deliver exceptional KM experiences.

Tim Hill, director of product, Mpower Expert KM, NICE CXone, emphasized the importance of knowledge retrieval and discovery within the KM framework, explaining how NICE zeros in on making this process effortless for both consumers and employees within its CXone Mpower Expert solution.

NICE’s focus with its CXone Mpower Expert product is “how do we drive towards [a] really high-fidelity generative search response that’s a personalized response…based on the user’s permissions to return content that’s meaningful to them in response to their question,” explained Hill. This is established through NICE’s GenAI workflow, which enables enterprises to:

• Capture and ingest content.
• Cultivate content adequacy.
• Calibrate content with pre-defined prompts through Editor AI.
• Calculate faithfulness and relevancy.

“The heart of what we’re doing [at NICE] is generative search,” said Hill, detailing the ways NICE revolutionizes knowledge management within its developed GenAI workflow.

This is only a snippet of the full Faster, Smarter, Scalable KM: Leveraging Knowledge Automation and AI webinar. For the full webinar, featuring more detailed explanations, a group discussion, and more, you can view an archived version of the webinar here.