2 . The gap is widening between good and bad AI . This is becoming more prevalent as more discussions happen around AI regulations , putting a spotlight on the importance of having purpose-built AI created with the proper guardrails .
When it comes to customer service , this means AI that is domain-specific and built from rich CX data , ensuring that responses that are generated are accurate , relevant , and appropriate . AI is the answer to managing the overwhelming complexity of customer service in the digital omnichannel age .
But that does not mean that all AI is created equal . Increasingly , businesses are struggling to optimize AI tools for their needs .
Intelligently communicating with customers , supporting contact center agents , and operating in the cloud at scale are all vital parts of successful CX . Only AI which has been purpose-built and trained on millions of customer interactions is suitable and trustworthy to manage an organization ’ s CX efficiently and effectively .
3 . Cloud adoption is on its way to peaking in 2024 . AI advancements are leading to mass adoption of the cloud , with companies realizing the necessity of bringing their operations to the cloud to be able to fully utilize AI and succeed in the digital era .
Here ’ s why the cloud is essential to AI-based applications . The cloud allows for much easier data sharing across an organization and applications . This is very important as
AI is trained on this data . The easier this data is to access , the easier it is to train AI .
Organizations are no longer able to manage complicated tech stacks of patchwork solutions . In the age of AI , organizations can ’ t afford to operate like this any longer . They need their data to be easily accessible and shareable .
Consequently , organizations are moving to adopt a single , open cloud interaction-centric platform , underpinned by AI , allowing organizations to seamlessly connect thirdparty resources with native capabilities on the platform .
THE U . S . BUREAU OF LABOR STATISTICS IS FORE- CASTING SLOWER LABOR MARKET GROWTH AND A DECLINE IN THE DEMAND FOR CUSTOMER SERVICE EMPLOYEES OVER THE NEXT 10 YEARS . WILL THESE MACRO TRENDS AFFECT CONTACT CENTER DELIVERED CX , INCLUDING AGENT PER- FORMANCE AND PRODUCTIVITY ?
A : AI is allowing CX organizations to do more with less , enabling these organizations to not only maintain service levels despite the impacts of economic uncertainty but become more efficient and improve overall operations .
Even with slower labor market growth , we see a constant increase in the volume of customer service interactions in the post-COVID Digital Economy of today . Less and less is done face to face which means more business is done virtually .
While Conversational AI will pick up many of those interactions , human agents will be needed as more complex business processes move from face-to-face to virtual .
INTEGRATING THE FRONT OFFICE ( CONTACT CENTER ) WITH THE BACK OFFICE
Consumers often interact with an organization ’ s front office for transactional interactions . With the reduction in face-to-face interactions , that front office can be the traditional contact center or an organization ' s digital storefront : mobile app or website .
Generally , those transactional interactions involve business processes that extend into the back office for ordering , approvals , billing , or payments . So , we asked Barry Cooper to discuss what is happening : trends , opportunities , and challenges , with front-office-back-office integration . Is it becoming more or less important and if so , why ? And is or will AI play a role there too ?
“ Digitalization and economic uncertainty are forcing CX organizations to rethink how they manage their operations leading many to combine back-office and front-office functions ,” says Barry . “ This speeds up processing , increases first contact resolution , and reduces errors .
“ Combining the two functions in the digital age requires a different way of managing time . CX organizations need to be able to manage asynchronous work which makes up a majority of the back-office work and is increasingly more common in the contact center .
“ Advanced workforce engagement management systems powered by AI now allow organizations to break down their staffing into ‘ activity-based staffing ’ taking into account asynchronous and synchronous work items .
“ On top of this , AI is further breaking down barriers between the back office and contact center , eliminating siloes and improving efficiency across the organization .
“ When the front and back office are managed on the same cloud platform underpinned by AI , this makes the relationship between the front and back office very smooth . Back-office employees have the information they need to complete service requests quickly . This reduces the chance of customers calling in requesting status updates .
“ With a comprehensive view of operations through the platform , CX leaders can also make better-informed decisions about staffing needs to move staff around from the back to front office when needed . AI provides rich insights to truly optimize operations and
FEBRUARY 2024 41 bridge the long-standing gap between the front and back office .”