This blog is part 1 of a 2 part summary of TheLoops online event “AI in Action” where nine CX leaders shared best practices, real-world wisdom and advice for other leaders and peers looking to implement AI for CX operations.
Let’s Recap A Few Of ‘AI in Action’s’ Overarching themes:
- Embrace AI as co-intelligence for your team (these terms are all synonyms: digital assistant, coworker, even advanced AI Copilots, they speak to the next evolution of AI agents working right alongside your human agents and increasing their productivity through insights and automations).
- AI is no longer restricted to chatbots, you must think of AI for internal CX ops first.
- Many CX leaders are tasked with needing to impact GRR with their current amount of headcount using AI to help increase productivity and output!
- AI adoption and implementation is not linear, nor should it be. You may crawl, you might run, then slow down to walk.
- For this reason, it’s INTEGRAL to have a flexible, agile, robust AI platform at your disposal.
Recap of Session #1: Crafting Your AI Action Plan with Mohan Achar
Crawl: Strong foundational strength on service delivery, good engagement, good principles in how you interact with customers and some technology possibly embedded in your engagement model but gaps exist around KCS and qualitative management control.
Walk: The program has multiple types of AI as part of its engagement, however, there is no good quality control management or there aren’t AI/ML in all interactions with customers.
Run: Organizations at this stage are breathing in advanced technology and have reversed the role of the human agents to assist the AI.
Mohan identified that his team is currently at a brisk walk stage ; )
What comes next: once you know what stage you are at, Mohan shares that the second step is to select the right partner, one who has AI embedded at their core.
On Why The Right AI Partner Matters Now More Than Ever
Mohan wants his peers to know: AI is not hype, it’s just been stuck in what he calls the “assist stage” for the past 8-10 years. However, those days are gone with AI rapidly moving into what Mohan describes as the analyze and act stage.
“I’m a big fan of the movie Minority Report and my initial vision in deploying AI was that it would be preventative. However, I was a little ahead of my time. For years, AI and ML have been stuck in the “assist” stage, helping agents get answers faster or reducing the manual effort needed to resolve tickets. This has been limited to responding to problems rather than solving them before they occurred. With where AI is today, the opportunity now lies in what I call the analyze and act stage—steps that empower support teams to proactively address issues and streamline operations.”
Here’s a Minority report gif for any other fans out there!
The analyze phase now shifts the focus from assistance to preemptively handling the work agents and even managers typically do.
This can range from evaluating case data, identifying trends, and recommending actions, allowing agents to validate and fine-tune outputs rather than starting from scratch.
As part of analyze and assist, Mohan shared his experience with TheLoops Intelligent routing where he’s achieved 100% routing accuracy, ensuring cases go to the right agent with the appropriate skillset. This eliminates bottlenecks and prevents tickets from being stuck in “no man’s land.”
As AI transitions into the act phase, this is where your human agents now oversee AI.
Human agents will monitor how the AI performs and provide it with feedback, reinforcement and help it fine tune the answers and output. As we wind down Mohan’s recap and move into the next, we’ll share one final thought from Mohan on how else AI of this nature adds value to CX organizations.
“As Support leaders, our duty does not end by serving the customer! After servicing the customer, we must now ask ourselves, ‘How do we transfer the data to our product partners to help on the roadmap or building the engagement models?’ This is where AI that handles topic trends and volume analysis comes into play.”
Jump to 11:19 in the “AI in Action” replay where Mohan shares a real world story of the benefits of this particularly when his CCO called him on Friday night at 6:19 pm asking about an escalation.
Lastly, he suggests that once you get to the walk or run stage, don’t be afraid to crawl once more. “AI is advancing so quickly that you have to keep an open mind and know that your deployment is never one and done.”
Recap of Session 2: From Fear to Frontier
When we last featured Monika Aufdermauer, VP of User Success, People and Culture at KOHO, she had saved $400,000 with the help of TheLoops AutoQA.
At the start of ‘AI in Action’, Monika conveyed that number is a drop in the bucket now. “We have saved millions in costs by leveraging TheLoops AI and other technologies and have also been able to allocate dollars to a higher quality BPO partner.”
When it comes to balancing the act of driving savings and managing employees fears, Monika always uses the example of the industrial revolution with her team and peers.
“I was an early adopter of AI and started with our first natural language processing bot about 7-8 years ago,” Monika shared. “As things have grown and we have gone to this mass adoption of AI, one of the biggest things I do is compare the AI revolution to the industrial revolution. Even back when we first started the industrial revolution, we experienced an economic boon! Building off of what Mohan said, I actually talk to my team about being ‘bot overlords’ and ensuring they have the skillsets to manage and govern AI as that will only help them career wise in the future.”
Speaking of careers and how the role of agents are changing, Lakshmi went from managing a team of 27 agents to managing a team of 18. All the while, customer cases grew and the knowledge base was static.
“We started leveraging AI for knowledge generation very early on, not only does this help the future of customer’s self-serving, it’s also a critical function that we never had enough time to put into before the help of AI. Now we can do this with the click of a button.” Watch her clip below for more.
Both Monika and Lakshmi have shared deeper dive blogs on what it takes to bring your teams along when adopting AI. Read Monika’s here. And Lakshmi’s on rethinking support operations here.
Following Mohan’s framework, Lakshmi described how she and her team went from crawl to run fairly quickly! Her agents have been receptive to looking at “AI as a coworker”, helping them handle increased volumes, resolving issues faster and ensuring they are more productive.
There is even interest from other teams regarding how AI can help them do less manual work and get more granular which further proves a thesis we have heard many times over: company wide AI adoption will likely be influenced by the Support org.
Speaking to cross-functional use, Monika conveyed how topic classification gave her team a, “different story to tell the product team.”
Before TheLoops Auto-tagging, KOHO:
- Relied on agent classification of around 40% of tickets for their insights
- The data was unreliable
- Tagging was too subjective and wasn’t the best use of the agent’s time either
“Once we deployed auto-tagging, we have worked with our product team to drive product improvements and decrease our actual contact rate by 60% over the last year and a half.”
During this session, Monika also discussed how she and her team have proven the ROI of AI.
To access the full 20 minute sessions from Mohan, Monika and Lakshmi and more takeaways like this, sign up for ‘AI in Action’ on-demand.
What’s up next?
Next week, we’ll share recap 2 featuring sessions from Greg Giletto, Genady Rashkovan, Daniel Rose, Mariena Quintanilla and Kartik Yegneshwar.
