Conversational AI implementations continue to surge, with worldwide annual spending on the technology expected to reach $1.99BN this year.
Beyond 2022, Gartner forecasts that its usage will soar further, predicting that bots will reduce agent labor costs by as much as $80BN in 2026.
In line with this, the analyst expects conversational AI to handle one in every ten agent interactions by 2026. Considering that the technology only currently automates 1.6 percent of these conversations, this statistic is surprising.
However, Daniel O’Connell, VP Analyst at Gartner, points to staff shortages as a prominent reason to expect an uptick. He states:
Many organizations are challenged by agent staff shortages and the need to curtail labor expenses, which can represent up to 95% of contact center costs. Conversational AI makes agents more efficient and effective while also improving the customer experience.
Yet, it is worth remembering that bots may not automate entire customer contacts. Use cases where they gather information from customers at the start of an interaction and feed that through to a live agent will likely become more prominent to reduce handling times.
Such use cases are often a simple introduction to bots – especially voicebots – for many businesses. After all, automating entire conversations in a customer-friendly manner is still tricky – despite AI advancements and the rise of low-code/no-code tools.
Recent Zendesk research reflects this, finding that 60 percent of customers still suffer from frequent disappointment when interacting with chatbots.
These statistics highlight that conversational AI still has much maturing left to do, despite Gartner’s lofty estimations.
However, the market analyst accepts this, also noting that a fragmented vendor landscape and continued deployment complexity may stunt the growth of conversational AI over the next two years.
Building on this point, O’Connell adds: “Implementing conversational AI requires expensive professional resources in areas such as data analytics, knowledge graphs, and natural language understanding.
Once built, the conversational AI capabilities must be continuously supported, updated and maintained, resulting in additional costs.
Following such a process for large-scale, complex deployment may take months, if not years, as companies add new use cases and continuously finetune conversation flows.
Nevertheless, enterprises will continue to lead the way, as Gartner notes that operations with over 2,500 contact center agents are most likely to adopt conversational AI. After all, they harness the technical resources and budget to draw more value from the investment.
Get Gartner’s perspective on the leading bot vendors by reading rundown of the Gartner Magic Quadrant for Enterprise Conversational AI Platforms 2022