Discover the latest trends driving the conversational AI market forward.
The conversational AI market has continued its rapid evolution into 2024, with developments in recent years prompting many chatbot and virtual agent providers to rethink their business models to meet the expectations of clients and consumers. The innovation wave, initially spurred by the global pandemic in 2020-2021, has matured and is now yielding the outcomes sought by businesses universally.
With this technological advancement, the conversational AI market has necessitated that vendors modify how they develop and deploy their solutions. The era of simple question-and-answer chatbots has given way to sophisticated virtual agents. These agents not only provide instant, 24/7 support but also manage complex transactions for customers.
Advances in conversational AI have made customer self-service far more efficient and convenient than previously possible. And, as such, the expectations of what a conversational AI platform can offer, both businesses and consumers, have shifted. Companies no longer require one-size-fits-all chatbots and, instead, expect to deploy enterprise-ready solutions that take full advantage of the technology.
Here are four important market trends that will drive the business value of conversational AI well into the future:
1) Going 'chat-first' will deliver the fastest return on investment
Gartner says that the future of self-service will be powered by customer-led automation. By 2030, Gartner analysts predict that a billion service tickets will be raised automatically by chatbots and virtual agents - or their near-future cousins.
This makes a lot of sense. Chat-based self-service is a low-cost, low-barrier way to automate customer interactions at scale. And, as consumers become more accustomed to it, we will begin to see businesses capitalize on this trend.
Adopting a 'chat-first' strategy - where a company funnels all customer service traffic through a conversational AI solution - will enable businesses to play to the strengths of automaton by reducing support costs and driving up CSAT scores.
We have already seen this approach yield impressive results within the banking sector:
- Nordea - Nordic banking and financial services leader company - now employs comprehensive conversational AI strategy to scale customer service across four markets.
- Íslandsbanki - an icelandic financial institution providing banking and financial services - now also automates 50% of all chat traffic after only 6 months of conversational AI service experience.
2) Virtual agent deployment timelines will be significantly reduced
If the pandemic has taught us anything, it's that many businesses were woefully underprepared for the unexpected surges in customer service traffic that resulted overnight. Those companies with a virtual agent already in place were able to mitigate significant spikes in inquiry volume, provided their conversational AI solution was robust enough to handle it. Others, however, were not so lucky. Many businesses were caught off guard and had to scramble to quickly build and deploy chatbots that were either not feature-complete or took significant time and resources to implement.
Responsibility will fall on vendors to prove that their solutions can deliver on promises of a genuine return on investment from day zero.
Key questions to keep in mind when determining if a conversational AI vendor is the right fit, include:
- Does the solution include scaleable Natural Language Understanding (NLU) that can process thousands of user intents (topics) simultaneously?
- Can self-learning AI be used to bypass a 'cold-start' and assist with the development and maintenance of a virtual agent?
- How quickly can an AI chatbot project go from development to go-live? Is it only a few weeks (desirable) or many months (undesirable)?
3) Data-driven chatbot design is more important than ever
Gartner predicts that by 2025, half of all leading roles for software engineers will require direct oversight of generative AI. White-collar workers are already using conversational platforms daily, underscoring the importance of familiarity with AI chatbots in the workplace. What would it be in a couple of years?
If those interactions are to be meaningful, conversational AI vendors will need to step up their game, making it necessary to move beyond the basic design principles that chatbots have relied on for years.
In order to have a marked impact on how customers perceive virtual agents as a useful tool, it will no longer be enough for vendors to provide market-leading technology. Using evidence-based design to inform various aspects of virtual agent development - from its personality and avatar to its visibility on a website - will be hugely important going forward.
The solutions that provide a deep analytics toolset, and other resources such as best practices, will be key to ensuring that companies can use conversational AI to its fullest potential.
4) The future of conversational AI is decidedly human
Much of the hype surrounding conversational AI centers around the black-box nature of the machine learning algorithms that power it. What's often left out, however, is that humans also play a big role in the success of a virtual agent or intelligent chatbot.
A 2019 report from Customer Contact Week found that 88% of customer experience professionals believe that artificial intelligence will improve and enhance their work, rather than replace them outright. This is contrary to the popularly held belief that chatbot technology and automation tools will take away human jobs.
Instead, experienced human agents working in customer service can be plucked out of call center support teams and upskilled into AI Trainer roles. These skilled workers can utilize their existing customer service experience to enhance chatbot development and improve the customer journey.
For employees in conventional customer service roles, having a virtual agent handle the majority of a company's frequent customer inquiries instantly is beneficial. This will fundamentally transform their daily tasks, eliminating the routine of responding to repetitive questions. As a result, their roles become more purposeful and centered on genuine customer engagement.