CHICAGO -- Knowledge management is the engine that helps drive artificial intelligence and makes it more usable for customers, according to experts who spoke at the eGain Solv 24 conference. Humans provide the third leg of the stool for the companies that have been the most successful in deriving value from AI, they said.
eGain CEO Ashu Roy cited the following from Gartner in his keynote address: "By 2025, all generative AI virtual customer assistants and virtual agent projects that lack integration into knowledge management systems will fail to meet their customer experience and operational cost reduction goals."
Gartner, he said, issues hundreds of reports and commentaries across many different industries, with many different types of findings. However, it is extremely rare for the research firm to express total conviction on any type of any industry trend, particularly one that is in the near future, Roy pointed out.
Generative AI debuted two years ago, but most companies have yet to get past experimenting with it, with most still in a wait-and-see mode, according to Roy. "AI is not trusted for content today. Building trust in that journey is part of what we are trying to do for you."
Most of the expected success from generative AI is still in the future. When Roy asked the audience who had gotten positive ROI from generative AI, no one rose a hand.
The eGain solution for trusted knowledge reduces costs for customers by 75 percent by combining technologies, experience, design and human expertise, according to Roy, who noted that eGain uses a layered approach to help customers be successful with its technology.
AI doesn't work in a vacuum, Roy pointed out. "You need a knowledge hub for experts and AI to work together. Trusted answers must be contextual, intentional, relevant, explained, personalized and collaborative."
The knowledge hub will be serving different audiences, so it needs to be able to provide each the answers they need in the context they need them. Marketing needs different information than technical support, for example, he stated.
eGain Agent Unveiled
One way for companies to extract benefits from the collaboration of AI and KM is through the new eGain AI agent, Roy said.
The technology is designed to conversationally engage customers, clarify intent, guide them to the personalized answer, and explain its approach, which the company says will inspire trust and customer adoption. The solution combines language models and case-based reasoning that tap into eGain Knowledge Hub content.
eGain executives also noted at the event that genAI is prompting companies to pay more attention to KM. For some, KM is helping define their AI strategy, according to Lynda Braksiek, AQPC principal research lead. She highlighted findings from her company's emerging technologies for knowledge management report. One of the top priorities in the annual survey was incorporating generative AI into operations for increased efficiency and process improvement.
Though AI has been on the priority list for several years, this was the first time it was listed as one of the top five priorities, she pointed out.
In a separate survey, AQPC found that 43 percent of companies were moderately invested in AI.
Braksiek offered the following suggestions for companies to derive the most value out of their KM and AI technologies:
- Make knowledge sharing an explicit part of the expert's role and responsibilities. Incorporate it into their job descriptions, performance reviews, and incentive structures.
- Provide training and support to help experts develop new skills, such as storytelling, content creation, and collaboration. This will enable them to effectively share their tacit knowledge.
- Establish communities of practice or expert networks where subject matter experts can regularly interact, share insights, and learn from each other. This fosters a culture of knowledge sharing.
- Involve experts in the design and validation of AI models and knowledge management systems. Their input is crucial for ensuring the accuracy and relevance of the content and outputs.
- Recognize and reward experts who actively contribute their knowledge and mentor others. This demonstrates the value you place on their expertise.
- Leverage experts as change agents to help socialize and drive adoption of new knowledge management and AI initiatives across the organization.
"People systems make technology systems work," Braksiek said. The key is to make knowledge sharing an integral part of the expert's role and provide the necessary support, incentives, and platforms to facilitate their active involvement and contribution."
She called KM workers "first responders" when it comes to working with AI.