Impact of Knowledge Graphs and Artificial Intelligence in Wealth Management companies
The practice of knowledge management is nothing new to corporations. Traditionally, knowledge management systems focused on building knowledge repositories that allowed enterprises to collect, organize and distribute assets, such as documents and graphics. But today, the term knowledge management is seldom heard in conjunction with conversational AI platforms. This is a missed opportunity. Because when knowledge management is paired with AI, it opens doors to far more powerful and interesting possibilities. This article explains why enterprises should opt for conversational AI platforms with out-of-the-box knowledge management capabilities.
Build Domain Experts
If you’re an enterprise looking to build expert virtual assistants, knowledge management capabilities are paramount. Domain expertise is what distinguishes smart, intuitive and proactive virtual agents from the more static and simple bots that characterize most of the industry today. To build a conversational agent with domain expertise, enterprises must move beyond intents and utterances to build bots based on ontology. This is the only effective way to ensure virtual assistants have a contextual understanding of the domain. Not only does an ontological strategy make bots smarter, but also far more cost-effective. Because once the context is captured within the knowledge graph, enterprises can effortlessly scale their virtual assistants across multiple products and services.
Reap maximum benefits out of your knowledge assets
Enterprises generate hundreds, if not thousands of documents and graphics daily. These range from user manuals and website FAQs to policy documents and videos. Every enterprise sits on top of a knowledge stockpile that is overlooked and underused. With knowledge management capabilities in conversational AI platforms, enterprises can create conversational knowledge by simply ingesting these knowledge assets. This simplifies the laborious process of building an exhaustive knowledge base, by leveraging resources which enterprises already possess.
Do more, with a leaner team
To build the AI bot, subject-matter experts (SMEs) usually spend weeks collaborating with engineers to create intents. Creating intents allows the bot to understand verbal requests or patterns of behavior and convert them into actions. The integrity of these intents will determine the success or failure of the bot. If the bot can’t recognize the intent behind the query, it’s useless. But creating intents is often a manual and time-consuming process.
It doesn’t have to be. Instead of weeks, what if intents could be created in minutes? With knowledge management capabilities, a conversational AI platform can directly tap into the expertise embedded in documents and extract intents. Instead of depending on SMEs, the AI can learn directly from the enterprises’ pre-existing assets. In short, the AI becomes the SME, reducing the time and resources required to build the bot.
Enterprise information is completely accessible
Enterprise knowledge resides in various formats, ranging from PDFs, to docx, to JPEGs, to videos. Finding specific information within an enterprise is like searching for a needle in a haystack. For example, if a customer wants to know the eligibility criteria for a loan, extracting that piece of information from a document is challenging. And if they can’t find information readily, people will often give up entirely. This has significant implications not only for productivity within an organization but also for sales and conversion outside the organization. According to a 2016 study by Forrester, 53% of US adults are likely to abandon their online purchase if they can’t find a quick answer to their question.
Once companies are able to harness and manage their institutional knowledge, employees and customers can get answers to their questions instantly. And, when used by live customer service agents, they can perform better and faster than ever before.
Information is now standardized and personalized across channels and touch points
Traditional knowledge management platforms are a bit like managed chaos. They have dozens, if not hundreds of different authors — each contributing different content. Some of this is outdated. Some of it is contradictory. Some of it is duplicated. To add even more confusion, each author has a different writing style. Instead of being stored in one place, content is distributed everywhere — across brochures, websites and videos. When a customer or employee finds information, it is very likely that someone asking the same question will hear an entirely different answer.
But if enterprise knowledge is managed by the virtual assistant, customers and employees can get consistent responses across all touch points — whether it’s from a virtual assistant on the company intranet, on Facebook messenger or on Alexa.
A step towards Cognitive Enterprise
With conversational AI, companies now have the staggering ability to reuse existing enterprise knowledge. And, they can create new knowledge in the virtual assistant, on the fly. Regardless of which method they use, virtual assistants can become the brain trust of the enterprise, acting as a single point of truth. Reimagining conversational AI as a conversational knowledge management platform is the stepping stone towards becoming a truly cognitive enterprise.
Originally published in Chatbots Life under a different title.