Shelf Blog

Large language models are a type of artificial intelligence (AI) infrastructure used to generate human-like text-based content based on the input they receive.

Harnessing the potential of AI will make the difference for competing organizations in the future. The opportunities made possible by this technology come with a number of new risks, but by following the steps outlined in this blog — and giving knowledge management the priority it deserves — business leaders can navigate the potential and risks of this new technology.

The accessibility and ease-of-use of your organization’s knowledge results in an agent who is immediately helpful at resolving customer questions. With one implementation, your support center can benefit from the service benefits of AI customer support including greater accuracy, better knowledge integration, and reduced onboarding costs.

Learn how Shelf’s AI-powered Answer Assist resolves one of the biggest pain points for support centers by creating entry-level experts.

A knowledge base can be empowered by AI and provide streamlined onboarding, greater security and compliance, and reduced strain on resources.

The CASC approach hopes to provide regulation that is “future-proof” since it gives agencies free rein to keep adapting to the evolution of AI technology, but it doesn’t provide the clear direction some organizations may want (or need) to pursue their AI strategy.

Shelf Search Copilot is a comprehensive solution that enhances agent efficiency, fosters customer satisfaction, and offers a concrete step forward to infusing AI into everyday customer service operations.

GenAI promises to provide greater productivity to knowledge work and a recent study on AI productivity may be the conclusive proof organizations need to invest in AI as a strategy. Harvard Business School conducted a study with Boston Consulting Group (BCG) measuring the performance of consultants...

Knowledge managers might have previously compared their role in an organization to a tail trying to wag the dog, but AI is a sea change. Knowledge engineers are now in the best position to understand how to turn an organization’s knowledge into a tailored solution for the optimization of AI.

As many businesses adopt Knowledge as an Infrastructure, the potential for AI will continue to flourish. That progression can take many different forms. We’ve laid out a spectrum of potential outcomes to assist business leaders considering adopting AI into their business.

The challenges of Salesforce Knowledge pose significant risks for businesses attempting to compete in a space heavily influenced by AI. Usability problems, reporting restrictions, lack of integrations, high costs, and poor use of AI all contribute to a poor productivity and cost-effectiveness.

A modern KMS tool will unlock your organization’s knowledge to be used with GenAI solutions and other innovations made possible by artificial intelligence. Shifting your organization’s strategy from digitizing knowledge to laying the foundation of Knowledge as an Infrastructure can make the difference for successfully implementing the power of AI.