These results are not shocking. Nor are the reasons behind this AI migration.
There is a growing skills gap between customer service demand and the supply of qualified agents who are willing and able to keep up with rapidly changing technologies. At the same time, human agent costs continue to rise. But organizations have increasingly squeezed customer experience( CX) budgets.
INDUSTRY BREAKDOWN
So, how does AI WEM adoption break down by contact center-using industry?
• Healthcare. Leading in AI-powered WEM adoption, with the highest rates of satisfaction across categories such as agent gamification, automation, and speech / text analytics.
• Retail and eCommerce. High adoption rates in automation and proactive customer care, showcasing commitment to innovative CX solutions.
• Business Process Outsourcing( BPO). Strong uptake of cloud-based CCaaS and advanced workforce management( WFM), though lagging in speech and text analytics adoption.
• Government and Financial Services. These sectors show the lowest adoption and satisfaction across all solution categories, with financial services scoring the lowest in six categories and government in eight. Modernizing legacy systems is a significant need for both.
These industry findings are not so surprising given that the public sector traditionally trails the private sector in emerging technology and innovation adoption.
Despite financial pressures and bureaucratic constraints, technology offers government agencies a golden opportunity to boost operational efficiency while improving the citizen experience.
As just one example, we have documented case studies where we helped agencies cut quality monitoring costs by 30 %: a level of operational savings that quickly captures attention. We believe once the Department of Government Efficiency( DOGE) understands some of these elements, we will be able to help in many similar areas.
Financial services, while a commercial industry, has typically been among the most conservative, especially regarding the adoption of cloud computing.
Although historically cautious to adopt new technologies, the landscape is changing. With improved security protocols, better regulatory alignment, the need for digital transformation, and compelling operational efficiencies on the table, financial companies are increasingly embracing innovation.
Retail and healthcare are often trailblazers when it comes to innovations that improve the customer and the patient experience. These industries face intense pressures from high consumer expectations and highly competitive landscapes. Innovation will continue to be what gives top performers a competitive edge.
GEOGRAPHIC BREAKDOWN
• Asia-Pacific( APAC): Leading in AI adoption across 13 categories, with high satisfaction rates and plans for significant investment in AI-powered WEM over the next five years.
• United States: Leading in speech and text analytics in the cloud but lagging in several other categories( see BOX).
• Latin America: Strong adoption of speech and text analytics, automation, and quality management.
• DACH( Austria, Germany, Switzerland) Region: Lowest adoption / satisfaction rates in multiple categories, indicating areas for improvement.
The DACH region is known for a cultural preference for more personal, human interactions. It also faces some of the strictest data protection norms and is often more cautious about technology adoption in these areas.
ARTIFICIAL INTELLIGENCE
BY CONTINUOUS- LY LEARNING, YOU CAN STAY AHEAD OF THE CURVE AND MAKE THE MOST OF AI-DRIVEN INNOVATIONS.
RECOMMENDATIONS FOR CONTACT CENTERS
It’ s a fact that AI will be indispensable in the contact center. How operators, managers and agents leverage it will determine their success.
By embracing AI as a collaborator, you can enhance your role and contribute to delivering exceptional CXs. As AI continues to transform the workplace, these strategies will help agents stay ahead and thrive in an AI-driven environment.
Embrace Continuous Learning. AI is evolving rapidly, so staying updated with the latest advancements is crucial.
Invest time in learning how technology enables outcomes and how to evaluate it. Many organizations offer training programs and resources to help employees understand and utilize AI effectively. By continuously learning, you can stay ahead of the curve and make the most of AI-driven innovations.
Enhance Technical Skills. While AI can handle many tasks, human oversight is still essential.
Developing technical skills, such as data analysis, understanding prompt engineering, and programming, can empower you to work more effectively with AI systems.
These skills will enable you to understand AI outputs, troubleshoot issues, and optimize AI applications to suit your needs.
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