Conversational AI in the Enterprise

In the technology world, aside from all the layoffs which are shocking, we have this flood of information, awareness and now access to immensely powerful conversational artificial intelligence. In my last post, I mentioned that we are in a moment of historically relevant technological transformation. I’d say, we are just seeing a tip of the wing of the butterfly emerge from the chrysalis. This kind of technology has been in the works for an exceptionally long time. The difference has to do with accessibility.

Car phones were available to people long before everyone had a phone. Once phones became available to the public, everything changed. Phone technology advanced with multitudes of innovation. Telephone networks were used for computing and these advanced into leveraging radio in ways we never imagined. Phones are now provided to people in poverty in a similar way that food and water are provided. Who would have said that a phone is as essential as a basic natural resource for survival?

Phones didn’t come overnight, it took time, but they lit a fire storm of interconnection and took other connective technologies with them. In other words, the phone itself caused massive ripples and innovation in other areas of our world. The basics of our communication have changed in every way. A friend called me the other day and asked, “why do we text each other before we call”? It’s true, most of the time many of us will text each other to see if it is ok to call. Before texting, you picked up the phone and made a call. While this seems minor, it demonstrates a change in fundamental behavior. Conversational AI, which uses a multitude of technologies, has now sparked a flame. The accelerant and the capabilities far exceed historical technologies and not unlike something that goes socially viral, the network is in place for this technology to become present in our lives with blazing speed.

Conversational AI can be composed of several techniques such as rule-based systems, decision trees, and neural networks. Typically, it is built with a combination of different techniques, depending on the complexity and the specific use case. The main idea behind conversational AI is that it can understand natural human language and respond in a way that simulates human conversation.

Conversational AI interacts with a variety of technologies, including:

• Natural Language Processing (NLP): NLP is a subfield of AI that deals with the interaction between computers and human languages. NLP algorithms allow conversational AI to understand and generate human language, which is essential for its ability to understand and respond to user input.
• Machine Learning: Machine learning algorithms are used to train conversational AI to understand and respond to user input. These algorithms allow the AI to learn from experience and improve its performance over time.
• Text-to-Speech and Speech-to-Text: Conversational AI systems often use Text-to-Speech and Speech-to-Text technologies to enable voice interactions with users.
• Dialogue Management: Dialogue management is the process of controlling the flow of conversation between the user and the AI. This is essential for maintaining a natural and coherent conversation and to make the user experience more human-like.
• Knowledge Management: Conversational AI uses knowledge management to store and access information that it can use to respond to user requests.

The main idea behind conversational AI is that it can understand natural human language and respond in a way that simulates human conversation.

Conversational AI has the potential to significantly change Knowledge Management in corporate environments by making it exceedingly more efficient and accessible. With conversational AI, employees can access information and complete tasks through natural language interactions with a digital assistant, rather than having to navigate through multiple software systems. This will save time, increase productivity, and reduce employee count. Additionally, conversational AI can improve the accuracy and relevance of information by using natural language processing and machine learning techniques to understand the intent behind a user’s request and provide a more personalized response.

Conversational AI has the potential to impact a wide range of services in corporate environments. Some examples include:

• Customer service: Conversational AI can be used to handle common customer inquiries, such as answering questions about products or services, providing support, or processing orders. This can free up human agents to handle more complex issues and improve the overall efficiency of the customer service team.
• Human Resources: An AI-powered chatbot can be used to provide employees with quick answers to common HR-related questions, such as vacation time, benefits, and company policies.
• Sales: AI-powered chatbots can help with lead generation and qualification by engaging with potential customers and providing them with the information they need to make a decision.
• Marketing: AI-powered chatbots can be used to personalize content and messaging, and to provide tailored recommendations to customers.
• IT support: AI-powered chatbots can be used to troubleshoot common IT issues and provide employees with the information they need to resolve problems on their own.

In terms of what companies can discover, conversational AI can help to uncover patterns and insights in customer interactions and interactions between employees, which can be used to improve products, services, and internal processes. Additionally, conversational AI can help to identify and prioritize customer needs and preferences, which can be used to inform marketing and sales strategies.

So Far Ahead We Failed

Wendy, Matt, and I wouldn’t have called ourselves futurists at the time but back in 2000’s we along with a few other KM practitioners identified an effective but socially unacceptable way to uncover organizational knowledge.

We surmised that if we tap into email and the historical email archives that we could discover who the subject matter experts were in an organization. We believed that not only could we find the expertise, but we could also unlock hidden knowledge buried in the messages. The digital echoes of those who came before us left their words, they had no choice, and most people aren’t thinking about the fact that everything they write in emails is owned by the organization. This means all sorts of things will be in email that don’t belong.

There were a few things we learned along the way including that we initially didn’t even need access to the body of emails. We only needed to see information about meeting invitations, and we could find experts very quickly. There were a few companies that were thinking the same way we did, and some technologies were developed to discover knowledge maps and find experts through the use of email.

They were well ahead of their time as well. People were absolutely petrified of the implications of someone digging into their emails. In commercial companies, EU and other non-US bodies rejected even the notion. There was literally nothing that could be said or shown that would convince them to all it. Later with GDPR and other privacy laws, this solidified the death of these kind of analytics. That was then, this is now.

It’s happening and that’s what’s up

For many years leading IT teams and working in this field there has been and still is a very consistent pattern across every organization I’ve ever worked in. Senior leadership wants everything in less than 8 slides. In fact, that amount may be too many. It’s too complicated and they just want the basics until there is an emergency. Even then they don’t want to read, they want someone to explain to them what happened. This is different from truly understanding what IS happening or what WILL happen. Very smart people in commercial companies like Microsoft used this as an advantage when they positioned their technical services. As I have written in many posts before, Microsoft and others have most commercial companies under their control. They are the basic utility and communication engine of global corporations. If and when they want to deploy changes to underlying technologies, global companies using their services have NO choice. While there are exceptions to this, there are two considerations to these exceptions. The first is that organizations would have to know what they wanted to block, which most don’t. The second is that Microsoft and others deploy technologies and modifications to current implemented capabilities at a high frequency without disclosure. This means you don’t know what is going on. They are your captain as one senior leader at Microsoft told me.

If the entire corpus of global knowledge is moved from share drives to SharePoint and this becomes part of the M365 ecosystem, it is highly discoverable. Add a little bit of the technologies I’ve mentioned above, include email in the mix and what do you have? One of the most comprehensive, powerful (risky) and transformational capabilities for knowledge workers in the history of technology.

If we add connectivity through integrations and import archived data and/or scan archived data, this is beyond game changing.

While there is still a lot to cover here and I do want you to think about this, I’ll leave some room for my next post. Before I do this, I’d like you to think about what email you have in Gmail if any? I’d like you to think about where your documents and images are stored and backed up. If you own an Apple device, Apple cloud etc. When Google releases its conversational AI capabilities, it will have access to the entire corpus of the “GoogleVerse” including your email, your documents, your images. Think about this.

Think about the fact that Microsoft just invested ten billion in Open AI while laying off 10k people. Think about the fact that not only do you not have control of services like this you’ve outsourced, but you also have no idea what services exist overall and what they do. I surely can’t tell you in a few slides and the fact is, since new services come out daily, I am already behind as well.

Bringing this altogether.

Conversational AI will change your life.

Your data, both personal and organizational, is not in your hands.

The services that are being deployed and positioned are out of your control.

The history of each organization is conversationally buried in email archives. Who knows what secrets wait in there?

Hey Clippy.. What the heck just happened here?