Home > Columns > CRM Columns
Addressing the AI Elephant in the Room: Trust
Contributed article by Seth Johnson, CTO at Cyara
Unless you’ve been living under a very large
rock, you’ve most likely interacted with Artificial Intelligence (AI) – whether
in a personal setting engaging with bots like Alexa or Siri, or in a business
setting using apps like ChatGPT or Claude, or less obvious automation use cases
to improve workflows. In the contact center space, the proliferation of agentic
AI is especially prevalent as the use cases are obvious, and the benefits to
enterprises are numerous – from improved customer experience, to reduced agent
turnover and overall cost savings.
While enterprises are quick to adopt AI agents
to reap those aforementioned benefits, their haste to do so may actually be
costing them more in the long run. That’s not to say AI can’t cut costs – it
can, and it does. The challenge is that many leaders mandate AI agent
deployments without implementing the proper training and guardrails, resulting
in inefficiencies, hallucinations, and clunky customer experiences (CX) that
damage brand reputation and loyalty, leading to lost revenue. Overall, it comes
down to trust between brands and their customers.
In this piece, we’ll explore the top CX
mistakes brands make, according to customers, and address steps enterprises and
brands can take to ensure AI and AI agents are enablers of trust, not
detractors.
Top CX Dealbreakers for Customers
“Speak to agent” is an all-too-familiar trope
of customer service interactions, and data that Cyara recently commissioned confirms it – the number one CX
dealbreaker for consumers is not being able to reach a live human. Further, 73%
believe human agents resolve issues faster than AI bots. However, expectations
are also higher, with 87% saying they have higher issue resolution expectations
for humans than for either chat or voice bots.
This is both a trust issue, and a perception
one. Even with advances in agentic AI, it’s difficult to replicate true
human-to-human interactions and the inherent trust that comes along with that,
but there’s a misconception that humans tend to resolve issues the fastest or
most comprehensively. When it comes to issue resolution, data shows that
technologies like agentic AI can actually solve many issues more efficiently
and with shorter wait times. Approached properly with testing and monitoring,
conversational AI can lead to an 80% boost in self-service interactions that
don’t depend on a human to resolve the issue.
Additional CX dealbreakers from the survey
include long hold times and slow responses, having to repeat themselves across
multiple agents or channels, and a lack of resolution or unclear next steps
after an issue. Each of these can cause strong negative customer reactions,
leading to frustrations and loss of loyalty. They are also strong use cases for
implementing AI, which can easily cut down on wait times and mitigate the
dreaded information repeat dilemma while guiding customers to clear next steps.
Finding the Balance Between AI Automation and
Human Empathy
Listen, I am not the first to say that it’s
not humans vs. AI, it’s humans and AI. But it does bear repeating. Keeping a
human in the loop will be a point of distinction, particularly for certain
demographics and use cases. For example, 81% of Baby Boomers favor human agents
for resolving issues faster, while Gen Z has a more positive sentiment toward
AI bots, with 21% saying that human agents and AI bots resolve issues in a
similar timeframe. Looking at use cases, 65% wouldn’t trust bots to handle
financial/security transactions and 53% are skeptical about bots handling
sensitive healthcare data. That’s not to say that enterprises should abandon AI
for these use cases altogether, but rather they need to be careful and
strategic about their deployments, and be transparent with customers about AI’s
use – while always ensuring they have access to a human.
There’s also plenty of opportunity for AI to
improve the experience in the background for better agent experiences and
outcomes. This helps keep a human in the loop, instilling strong trust and
ensuring empathy is front-and-center, while still reaping the benefits of AI’s
intelligence and automation capabilities.
Modernizing CX and the Case for AI
Accountability
Modern CX requires modern solutions, but it
doesn’t mean AI without guardrails is the catch-all to resolve all of CX’s
challenges. As enterprises look to not only experiment but fully deploy tech
such as agentic AI, it must be thoughtfully designed and deployed. The key to
AI’s success lies in its ability to resolve issues and build trust, and to do
that, leaders must ensure proper guardrails, testing and monitoring. You
wouldn’t buy a car without seatbelts or one that didn’t undergo rigorous safety
inspections, and you shouldn’t implement AI without assurances that it will
work how it’s supposed to and lead to stronger CX outcomes. At the end of the
day, if your AI agent hallucinates, makes a mistake or gives improper guidance,
you can blame a rogue agent all you want, but it’s your brand that will suffer
reputational and revenue losses. CX assurance is not a nice-to-have for brand
reputation – it’s a critical must-have for brand survival.
The real benefits of AI implementations in the
contact center are too great to ignore – but so, too, are the risks. The onus
is on leaders to deploy AI agents responsibly to build trust with customers.
Their livelihood and brand reputations depend on it.