The past, present, and future of search with Ontotext, Northern Light, and Workgrid

Navigating the ever-evolving, ever-fluctuating technological world is no easy feat. Even when we narrow the scope to search innovations for knowledge management, the infinite approaches available are overwhelming. What’s coming next in this space—especially for hot topics like AI, natural language processing (NLP), and knowledge graphs—is as seemingly impossible to predict as it is to maneuver.

To help shed some necessary light on advances in search, experts joined KMWorld’s webinar, What's Ahead in Search: AI, NLP, Knowledge Graphs, and More, exploring what the increasingly near future may hold for these prevailing trends—both challenges and benefits alike.

Ivaylo Kabakov, head of solutions at Ontotext, asserted that to predict, we must first examine search’s evolution. From the humble beginnings of keyword-based search to semantic search and the plunge into generative AI (GenAI) search, Kabakov argued that search’s next phase will be its AI era. Kabakov defines this phase as search that uses deep contextual and intent understanding with multimodal capabilities to ultimately deliver enhanced search interactions and responsiveness.

The role of AI is intrinsic to the future of search, according to Kabakov, used not only to improve overall accuracy with machine learning (ML) but also designed to create personalized search experiences with behavioral analysis. An example of AI’s role in search is the advent of verbal querying, where users can ask a question, aloud, in their natural language and accent, and receive a response.

“Speaking of computers understanding us,” Kabakov transitioned, “NLP is really a transformative technology that bridges the gap between human communication and computer understanding, fundamentally enhancing how search engines interpret and respond to our queries.”

By infusing search with understanding for both context and intent, machines are granted semantic understanding that heightens the possibilities for search. Knowledge graphs operate in a similar space, working to “connect the dots” between data points, according to Kabakov.

Based on these examinations, Kabakov offered their humble predictions for the future, including a growth in these areas:

• Unified search experiences where lines continue to blur
• AI and NLP-enhanced research
• Focus on contextual awareness

David Seuss, CEO at Northern Light, centered their focus on GenAI, citing a quote from Bill Gates, “Generative AI has the potential to change the world in ways that we can’t even imagine.” Despite its grandeur, GenAI has the capacity to be, for lack of a better word, useless. The key to avoiding that pitfall, according to Seuss, is ensuring that the GenAI application makes everyday tasks easier, faster, and better, as well as/or solves the major “plumbing” challenges impacting organizations’ data estates.

Content preparation is a notable plumbing problem plaguing organizations attempting to become competitive and intelligence-driven. Harnessing market research—which exists outside of the organization—is crucial in maintaining a competitive edge, yet difficult to extract. According to a study by Harvard Business School with 758 consultants, with the help of GenAI, a group of consultants were able to finish tasks 25% faster with 40% higher quality compared to those without GenAI.

The power of GenAI in content preparation is obvious, as intelligent research tools—such as Northern Light’s SinglePoint platform—can remediate the distance between enterprise teams and search success.

The future, Seuss examined, will continue to place GenAI in the spotlight with AI assistants and copilots designed to further automate various search tasks. An assistant running in the background continuously, watching content flow, and alerting the user to changes or potential opportunities is soon approaching, if not already here, according to Seuss.

Conversational AI, according to Gillian McCann, chief technology officer at Workgrid Software, is transforming search. The rise of digital friction, or “the unnecessary effort an employee has to exert to use technology,” is signaling a time for innovation, especially in the space of knowledge retrieval.

Echoing the previous speakers, the difficulties of finding the right information, when and where you need it can be alleviated and transformed with AI.

“Imagine, instead of using a search bar, employees can ask questions in natural language and get clear answers across every application, document, and knowledge repository in the enterprise,” offered McCann. “That’s exactly what conversational search, or Generative AI-based chatbots, can bring.”

McCann expressed that AI will continue to provide automations and actions that go beyond basic answers to user queries. These capabilities include:

• Understanding complex queries and providing precise answers in natural language
• Offering actions directly within a conversational interface
• Performing tasks on behalf of users
• Comprehending and addressing multiple steps within a request

For the full, in-depth webinar discussing the past, present, and future of search, you can view an archived version of the webinar here.