A recent article in Datamation (yes, it’s still around – online only now, as so many former print magazines are) identifies three artificial intelligence (AI)-based “disruptions” – how future AI applications will dramatically change our way of doing things. One of the three author Rob Enderle flags is “pre-curated content” – giving people more of what they are interested in and less of what they aren’t.
This already happens to some degree, of course, on social media platforms (where many argue it has exacerbated an unhealthy political divide), and on Amazon and Netflix (where recommendation engines point you to another product or streaming TV show you might like, based on your past purchase/viewing behavior).
A business context where pre-curated content offers a compelling benefit, with real ROI, is in an enterprise knowledge management system that professionals rely upon to inform their strategic decisions. In the knowledge management use case, the machine isn’t making the decision – that’s the human’s job – but it is identifying the most relevant and important information the human should consider, and presenting that information in summary form (with links to the full documents) to help the user make the best decision. The information may come from internal market research and customer insights documents, or from external sources like syndicated research services, industry journals and authoritative news websites, conference abstracts, or government databases. Not only is the information pre-curated, it’s also pre-digested, to accelerate the human user’s time-to-insight.
This capability, like the recommendation engines on popular e-commerce sites, is not some distant AI future; it is here today. For example, Northern Light SinglePoint™, an enterprise knowledge management platform optimized for market research and competitive intelligence content, offers several AI-based machine learning capabilities – More Like This, the Insights Report, and a Recommended Reading List – all geared specifically to the professional user with a serious business use case.
Like Amazon guiding a returning shopper, SinglePoint learns about a user’s interests over time based on their research behavior (what they download). That can save the user precious time and qualitatively improve the decision-making process by surfacing content (from among terabytes of information indexed in the knowledge management system) directly related to the issue at hand. With this Recommended Reading List, relevant content will in effect come and find you rather than you having to go look for it.
Also, SinglePoint enables auto-summarization of search results. The search engine reads all of the documents and summarizes the most significant ideas contained in the documents on the search result into an Insights Report. The user can express an interest in knowing more about a topic—what used to be called a “search query”—and then the system delivers a report rather than just a search result. The machine does the search and then tells the user what it finds that the user should know.
Finally, SinglePoint’s More Like This feature builds a semantic model of each document, enabling the system to automatically find additional content for the user that will address the same topics in the same weighting as a document of interest, and present it with a quick click of the More Like This button.
Will pre-curated content and these other artificial intelligence-based capabilities evolve over time? No doubt. But make no mistake: AI is both the present and the future of knowledge management systems. Enterprises can derive significant value from AI technology today; there’s no need to wait.
To discuss the value of “pre-curating” market research and competitive intelligence content for business decision makers in your organization, contact Northern Light.