When a contact center first toys with conversational AI, it will typically batch together its most common customer queries.
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From there, it’ll analyze how a live agent resolves that query and then look to recreate that journey within the flow of a bot.
If that’s not possible, they may ask: what knowledge does a human agent need to resolve this query? Then, they may aim to proactively feed that to agents during a live contact.
That approach is far too human-oriented. It does not consider how a business can unify AI technologies, reinvent the journey, and provide a more seamless customer experience.
As such, it’s time to take a more task-orientated approach to contact center AI and virtual agents – according to Anand Janefalkar, CEO of UJET. In conversation with CX Today, he said:
“These agents handle specific tasks, much like microservices in enterprise software. Such a modular approach allows for greater flexibility and integration.”
Moreover, the strategy welcomes a higher level of creativity as service leaders open their minds to define the best way to resolve their most prominent customer queries.
Define the Single Best Way for a Resolution
Take a common task a customer wishes to complete, and first assess whether the contact stems from a broken process. Fixing that upfront saves unnecessary investment in AI.
If that’s not possible, consider how the contact center can combine AI, humans, and modalities to drive the simplest resolution for the customer.
For instance, perhaps a customer wishes to refill a prescription. Typically, they may have to interact with a live agent or fill in an extensive online form to complete this task.
However, what if they could – using the cameras on their smartphones – scan their ID and packaging from their previous prescription bottle as part of an orchestrated online virtual agent experience?
From there, the contact center could leverage 30-year-old optical character recognition (OCR) capabilities to validate the prescription and – via workflow automation – automate the refill.
That’s just one example, and Baker Johnson, CMO of UJET, believes this new level of creative thinking could “redefine” customer experience.
“The deeper impact is in how these virtual agent and AI technologies – including GenAI – are integrated into back-end workflows and orchestration,” he said.
“This shift is redefining how businesses approach customer experience and how they use data to enhance customer journeys.”
A critical part of that transition is overcoming conventional contact center thinking. For instance, many will emphasize: “I must resolve the customer’s query in their channel of choice.”
Yet, in line with the task-oriented AI approach above, service leaders should think: “I must meet the customer at their point of ingress and blend data, channels, modalities, and automation to resolve their issue with the minimal amount of ‘experience’ required!”
Don’t Take the Wrong Turn
Consider the human-orientated approach again. Every time a business wants to add automation to a new channel, they must think: how would an agent on this channel handle that query?
Then, they’d look to replicate that within the virtual agent.
As such, when a contact center adds a new channel – such as WhatsApp, Google Business Messages, and various social media channels – they add new complexity to the AI strategy each time.
Moreover, they fragment the contact handling strategy and achieve only a fraction of the operational cost reductions they might expect.
That’s a problem, as evidenced by a 2023 study by former Gartner analyst Andrew Moorhouse.
In the study – entitled: “It’s time to rethink Conversational AI” – Moorhouse shared the story of a contact center conversational AI implementation within a tier-one bank.
That bank had 180 IVR disposition codes, 120 conversational AI intents, and over 480 self-serve journeys online – each disconnected from one another. He wrote:
“This resulted in severe customer dissatisfaction, with over one-third of Net Promoter Score (NPS) detractors unable to resolve their issues through live chat due to a lack of intent-level intelligence and poorly designed contact routing.”
As such, the example underlines the importance of task-oriented routing and orchestration.
Furthermore, it exemplifies how contact center AI projects rarely fail due to low-quality artificial intelligence. Instead, a lack of human intelligence is typically to blame.
UJET: A CCaaS Vendor That’s Ahead of the Curve
UJET has embraced the concept of specialized virtual agents. These agents consider common customer queries – across various industries – and pave the ideal, automated path to resolution, blending multiple AI technologies and modalities.
Yet, UJET also equips its customers with the AI, modalities, and open contact center infrastructure to define, design, and execute their own task-orientated bots alongside their full suite of omnichannel and workforce management solutions.
Moreover, the vendor’s CCaaS platform is mobile-centric, a significant differentiator in a world racing towards AI-adoption. After all, many contact centers are still limited by solutions designed for the landline era. However, the smart device era was a paradigm shift that began almost 15 years ago.
Nowadays, UJET stands apart by offering brands the ability to orchestrate more innovative customer journeys, leveraging the metadata and digital capabilities of those devices.
Each example spotlights UJET as a leading innovator – enabling seamless, personalized AI-powered interactions across channels and devices for modern consumers and agents.
To learn more about its AI-first CCaaS offering, visit: ujet.cx
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