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Conversational AI and the Gartner Hype Cycle 2020: what's new and what to expect

December 15, 2020

The world's leading research and advisory firm is bullish about the conversational AI market over the next two to five years

The hype surrounding conversational AI is very real. With the ongoing coronavirus pandemic having dramatically accelerated the adoption of digital technologies by both consumers and businesses, it's becoming increasingly evident that virtual agents are not only here to stay but that the underlying technology that powers them is maturing at an exponential rate.

This is a sentiment that is backed up by the latest revision of Gartner's Hype Cycle for Artificial Intelligence. Among the two dominant AI megatrends of democratization and platform industrialization outlined in the accompanying report, chatbots (and by extension, conversational AI and virtual agents) have been reclassified to sit squarely within the 'Trough of Disillusionment' - that is to say, the initial excitement and market surge of the category has finally begun to settle.

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Source: Gartner

Far from a negative outlook, what this reclassification reveals is that we will begin to see only vendors with the right technology and approach prosper as the market matures. Gartner projects that conversational AI will see over a 100% increase in adoption rates over the next two to five years, cementing the technology as the leading use case for AI in enterprises today.

Additionally, Gartner has also revised the penetration rates of conversational AI, increasing them to between 20%-50% in 2020, compared to 5%-20% last year. Gartner attributes this marked uptick in adoption to the technology's advantages when it comes to delivering streamlined, automated customer interactions. Conversational AI can be leveraged to keep both customers and employees informed and safe during a period where many are discouraged to seek in-person customer service.

Another interesting trend that Gartner has seen emerge across its client base is the replacement of AI-related pilot projects, that were common prior to the pandemic, with accelerated development cycles and AI-based minimum viable products. Whereas pre-pandemic, businesses had more time to invest in longer development cycles, they are now gravitating towards vendors that can deliver quality results quickly - something that is being paralleled by the technology with the rise in self-learning AI and its capacity to dramatically reduce the time it takes to develop virtual agents from scratch.