This Is What Gartner Said Three Years Ago On Conversational AI & Service Technologies
Introduction
Please allow me to create some context…
…there are two approaches to Conversational AI implementations…
1️⃣ The first approach is via a Conversational AI interface, commonly known as a digital assistant, chatbot or voicebot.
A digital assistant can be seen as a complete conversational experience facilitated by the three components of a conversational interface, as seen below:
2️⃣ The second approach is a more fragmented approach where Conversational AI elements are used in various Contact Centre AI (CCAI) implementations.
⬇️ Below are 18 use-cases for CCAI as identified by Gartner…
To illustrate how companies are segmenting their offering according to CCAI use-cases, below is the Microsoft technology stack currently available to address the various use-cases in the CCAI market.
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Back To Channel Technologies…
IVR Self Service — Voicebot
Considering the Gartner Service Technologies Bullseye of 2019 graphic, IVR Self-Service has the biggest value, but with a very low future importance.
I believe the future importance might be misleading, as the principle of customers calling a contact centre will remain a preference, but the opportunity and market for automation is huge.
So indeed, this current value status of IVR in the bullseye is telling, coupled wit the low future importance of the current underlying technology. With the legacy underlying technology being replaced with voicebots. Again, the voicebot market is only in its infancy and big opportunities currently exist.
There is a massive opportunity for technology providers to drive the migration from a IVR experience to a Voicebot interface.
Cost savings in terms of automating telephone calls into an organisation’s contact centre is immense, hence the importance of solving for this problem.
Hindsight is an exact science.
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Search Engine Optimisation (SEO)
SEO can be considered from an outward or internal perspective. According to the graphic, the value is relatively high, and future importance is marked as unchanged. The future importance is something which most probably moved up in importance the last few years.
One thing to note here…there is significant impetus from organisations to add a semantic layer to their data, allowing employees and partners to search and access data via natural language.
The market is seeing innovations in the field of Knowledge Intensive NLP (KI-NLP), Chatbots are being bootstrapped using search, Large Language Models are being introduced and technologies like vector databases are entering the mainstream.
In the Gartner 2018 Technology Roadmap Survey, 452 service leaders from a variety of industries, business models, contact center sizes and locations provided their perspectives on 45 established and emerging technologies.
Orchestration
Something which is not explicitly mentioned in the bullseye report, is orchestration.
With the advent of Conversational AI, there is a golden opportunity to leverage Conversational AI developments across different channel technologies.
For instance, orchestration between a voicebot (displacing traditional IVR) and the callback/auto-dialer functionality are crucial for intelligent orchestration.
Channel services like…
1️⃣ Text Messaging,
2️⃣ Secure Mesaging,
3️⃣ Web Chat,
4️⃣ Social Media and Mobile App
can all leverage Conversational AI development and functionality cross-channel.
For instance, a Virtual Customer Assistant can be implemented via a text based chatbot and learnings can be leveraged to aid in the migration process from an IVR application to a Voicebot…followed by outbound campaigns, auto-dialers…and more.
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And Finally…
I started by describing Conversational AI in two ways….a single digital agent, or various CCAI components.
However, I need to emphasise the importance of orchestration within landscapes…like the Contact Centre landscape. And hence these channel technologies should not be seen in isolation.
I’m currently the Chief Evangelist @ HumanFirst. I explore and write about all things at the intersection of AI and language; ranging from LLMs, Chatbots, Voicebots, Development Frameworks, Data-Centric latent spaces and more.
