As organizations become more complex and geographically dispersed, managing processes, people, and information gets increasingly challenging.
Enter AI. Specifically, chatbots.
Chatbots are designed to simulate conversations with human users. In a business context, they can be used for a variety of purposes, from customer service and sales to data management and process optimization.
Having worked with multinational organizations of many different sizes and backgrounds, we were searching for the right tool — both simple and effective — to help them and their customers (and us) deal with an overload of information and streamline their work.
So we built our own AI solution.
Let’s start with a concept that might seem unrelated to AI (at first glance).
One thing that many companies struggle with is knowledge management — that is, cataloging knowledge. It can be complicated to capture, share, and utilize all information effectively within an organization, especially a larger, more dispersed one.
The issue with efficient knowledge management is the sheer volume of information that organizations need to tackle. This information is often scattered across various departments, systems, and formats, making it difficult to find and access what is needed, when it’s needed. Many companies also lack standardization in how information is stored and shared, leading to inconsistencies and redundancies.
All things considered, it becomes clear why many business processes remain painstakingly inefficient and time-consuming. Plus, knowledge can quickly become outdated, especially in industries with rapidly changing technologies and trends. (In our digital age, that’s practically every industry!)
So, in exploring AI, one of our key objectives was to help our clients manage their data and knowledge. In the long run, this could significantly improve their decision-making, enhance innovation, and achieve better outcomes overall.
To many of us, perhaps the most familiar example of AI are chatbots.
Chatbots are AI-powered programs capable of simulating conversations with users. These tools leverage natural language processing (NLP) and machine learning algorithms to gather knowledge and communicate with humans, usually by responding to queries and prompts.
It's likely that nearly every internet user has encountered a chatbot in some form, even before the all-pervasive ChatGPT — whether as a floating icon on a website (see the bottom-right corner on Blue), a virtual assistant in an app, or even an early basic conversation bot, such as ELIZA. In fact, designed in 1966, ELIZA is considered the earliest developed chatbot (even though the .js script wasn’t written until 2005).
Chatbots have seamlessly integrated themselves into our online experiences, and are now revolutionizing the way organizations approach their data and work.
Within the business ecosystem, AI chatbots can be deployed in a wide range of areas, from customer service, sales, virtual assistance, to working with data. And in the context of knowledge management, these intelligent tools can address the challenges of communication, collaboration, and information overload.
Chatbots can help users quickly access relevant information by providing personalized recommendations based on user preferences and previous interactions. For example, an AI bot can help an employee find a specific company document or piece of information by following detailed prompts to narrow down the search results.
Chatbots can also enhance collaboration by connecting employees across departments and geographies, aiding in scheduling meetings, and coordinating activities. There’s even an emerging area of AI application in workforce planning (alongside many other HR tasks).
Additionally, AI bots can serve as trainers and educators, offering on-demand training and support to help team members improve their skills and stay up-to-date on company policies and procedures. Take ChatGPT — with the right prompt, it can generate guidance to master almost any skill.
(Interested? Try this: [Describe the skill you want to learn] “Assist me in learning the skill mentioned above. Provide me with tips, resources, and practice exercises to help me improve and excel in this area.”)
At the heart of effective knowledge management is having a robust knowledge base — and solutions to effectively organize, curate, and search for information within it.
AI-driven tools, like the chatbots we discussed earlier, can be programmed to store extensive databases. They can then perform tasks that involve searching these databases for specific information, files, and documents, and help human employees with other data-heavy procedures.
Typically, this technology runs using two concepts: vector embeddings and cosine similarities.
As mentioned, chatbots use NLP algorithms to process language. This involves converting text into high-dimensional vector embeddings, which enable NLP models to understand the meaning of words beyond simple keyword matching.
In simple terms, vector embeddings are a way of representing different types of information in a mathematical format. This allows the chatbot to learn the relationships between different types of information, and to make connections between them.
Cosine similarities are a way of measuring how similar two pieces of information are to each other by comparing queries against a vector database to find the closest match. This enables the chatbot to generate the most relevant information to answer a user's question, based on the similarity of the question to other queries in the knowledge base. This is what can significantly improve search accuracy and user satisfaction.
Now that you know all about chatbots, meet chat.mad.co — our very own AI tool designed to help organizations manage information and streamline data-related processes.
Our chatbot is a simple conversational interface powered by OpenAI that is designed to help team members, clients, and other users efficiently learn and access relevant information.
One of the key features of the Mäd chatbot is its NLP capabilities. This means that the bot can understand and respond to queries in natural language, making it easy for users to find the information they need without having to navigate complex software interfaces or search through multiple documents. Essentially, it taps into a specifically defined database of information, giving the user access to a whole library of information through a chat interface.
For instance, we connected our internal-use chatbot to Mäd’s extensive knowledge base of published insights. When a user enters a question or prompt about a particular subject, the bot will generate an answer based on the available information from this dataset of articles.
The Mäd AI chatbot can be precisely tailored for other organizations to align with their knowledge base, product or service, and business objectives. Its technology enables it to be programmed to access any given dataset, which means it is capable of serving the needs of any of our clients, regardless of their industry.
Eventually, we plan to offer the Mäd AI assistant as a tool that can be adapted and fully personalized to any company and its corresponding knowledge base.
The main motivation behind building the Mäd chatbot was to help our client partners, especially large multinational organizations, with their advanced knowledge management needs.
As these companies expand and become more complex and dispersed, managing information and ensuring that internal members can find relevant data gets increasingly challenging. On many occasions, finding a simple answer or a single document could get so time-consuming that it delayed other more important processes.
Our AI chatbot intends to solve this issue by providing stakeholders and employees with quick access to the information they need through a powerful yet easy tool.
So, what exactly can we do with chat.mad.co in practice?
Our chatbot offers several benefits for knowledge management, particularly for larger organizations.
Imagine you're a consultant at the UN and you need to find information about a particular digital public product or service, or identify the most important findings of any report. You could search through the company's intranet or knowledge base — but that would take a lot of time and effort to manually browse and read through documents, especially for an organization of this scale.
With our AI solution at hand, you can simply enter a question or prompt, and the chatbot will find and produce the most relevant information from a specific knowledge base. The power of OpenAI almost instantly analyzes the text for you, saving a significant amount of effort and making time for more important tasks.
Consider also the chatbot’s use for law firms. Legal professionals typically have to go through stacks of documents that often add up to hundreds and even thousands of pages, and compile statements and reports. Using an AI assistant would eliminate the need to manually search and analyze the data. Instead, the user could enter a specific query, and the chatbot will curate and generate only the necessary facts.
The emergence of chatbots in the organizational landscape represents a powerful solution for bridging the gap between traditional operational systems and a highly innovative contemporary approach.
By providing a conversational interface that is accessible to all, chatbots can help address the challenges that are common to data- and knowledge-heavy tasks. Mäd’s own chat.mad.co is an excellent example of how businesses can leverage AI to improve their knowledge management processes.
With its interactive and intuitive nature, we believe that our AI assistant has the potential to revolutionize the way organizations approach knowledge management and handle data. It can empower companies to streamline operations, reduce costs, and enhance the experience of both employees and clients, offering a powerful solution for organizations with complex information management needs.
If you’re interested in implementing AI-powered solutions to streamline your business processes and enhance operational excellence, visit ai.mad.co or reach out to us at ai@mad.co.
