IT WILL TAKE JUST A FEW BIG BRANDS THAT HAVE AI MANAGING AND POPULATING THEIR WORKFORCE TO BUILD TRUST AND CONFIDENCE .
IT WILL TAKE JUST A FEW BIG BRANDS THAT HAVE AI MANAGING AND POPULATING THEIR WORKFORCE TO BUILD TRUST AND CONFIDENCE .
But imagine if the AI started bombarding them with myriad bits of data , creating information overload and critiquing everything they do ? The agent ' s focus would then shift from showing empathy to customers , negatively impacting the natural flow resulting in a stilted , scripted dialog .
So , vendors created tools that used AI to take several monotonous things such as writing call summaries off agents ’ plates , enabling them to have genuine conversations with their customers and more effectively helping to solve their problems .
A good workforce engagement tool not only does a good job of forecasting and scheduling , but it also identifies areas where you can coach your agents and help them improve around your products and services .
Speech analytics review their language skills and quality monitoring enables the coaching of agents . AI-based scoring helps so you don ' t have to listen to a small sample of five out of 5,000 calls . You can listen thoroughly to every single call with the help of AI and come up with those coaching moments .
Vendors are now using Generative AI to allow contact centers to identify these coaching moments faster , pushing training into an evaluation room for real-time learning . It ’ s also changing the landscape of the entire product suite where each product is getting better and more efficient .
Imagine an evaluator asking AI to quickly fill in the form before validating the call . Or a speech scientist trying to create a topic and all phrases are already there as recommendations .
So vendors are not only evaluating each call , or calculating NPS scores or detecting coaching moments in the products , but also augmenting their products to be AI-enriched .
AI ' S GREATEST OPPORTUNITY
We believe we can improve every aspect of a customer journey from customer experience to employee experience .
32 CONTACT CENTER PIPELINE
• Can I have my people handle this call more efficiently ?
• Can I train and coach them so that they ' re better at their jobs ?
• Can I do certain tasks for them , such as create a case for them automatically ?
• Can I create a set of action items , so they don ’ t have to go in and do it themselves ?
Nothing is impossible now . We are literally looking at everything that an agent can do . If a machine is listening to and learning from agents all year , it becomes smarter on things like :
• How do I handle objections ?
• How do I behave ?
• How do I show empathy ?
• How do I show emotions ?
After one year of training , AI will do most of the jobs and gradually shorten the training duration to the point where it will perform better than a human .
In the short term , we will see more focus on task automation . There will be a transition to a hybrid model dominated by human-assisted machines or machine-assisted humans . It will be a journey over the next 10 to 20 years .
Gartner predicts that by 2027 , chatbots will become the primary customer service channel for roughly a quarter of organizations .
There are already virtual agents that pass the Turing Test ( SEE BOX ). But as business leaders , we cannot cede total control to machines . There must always be human oversight even if AI logs many of the tasks humans handle today .
It will take just a few big brands that have AI managing and populating their workforce to build trust and confidence . It ' s like cloud migration . At the start , no
WORKFORCE ENGAGEMENT
one wanted to put their customer data in the cloud , then Salesforce happened , and others followed suit .
HOW DOES IT END ?
No , this evolution does not end in Skynet conquering the human race . But I believe something amazing will happen .
AI will understand and predict customer journeys . Currently , all the AI work that is going on in the market is reactive , reviewing and automating tasks to make agents more efficient . That ’ s the problem we ’ re solving for the next 12 to 24 months .
It will get really interesting when the AI understands and anticipates a customer ' s behavior and course-corrects them from their current trajectory to drive a better outcome for the business .
This is the evolution to a predictive AI . It will proactively influence the customer via a chat session or by launching a new marketing campaign based on a better assessment of customer preferences .
This predictive , hyper-personalized AI may send a text or write an article based on how well it understands customer behavior , moving you along in your customer journey .
This development will happen in the next three to five years and the possibilities are endless . Influencing the customer to change their course will take an anthropomorphic entity that can transform into a sales agent , a marketing expert , a product information specialist , perhaps even a psychologist .
This semi-sentient AI will start to act as a business unto itself . It will automatically take care of certain tasks , even potentially entire business functions that might take five humans in different departments across the enterprise to accomplish today .
Eventually , this shift will impact the labor market , shaping the types of roles and skills needed , but humans will always have a place in AI-powered experience . It will be a fascinating future , one in which we harness as yet unimagined capabilities through AI . With humans in charge .
Praphul Kumar , Chief Innovation & Product Officer at SuccessKPI , loves to build what ’ s next . He has a passion for solving customer problems by leveraging design , technology , and data science . Praphul brings over 20 years of experience in Customer Experience , AI and Analytics space , and held leadership positions in many organizations .