In light of the AI Stargate project and it’s $500 billion privately-funded initiative, it is worth reflecting on a recent study that looked at planned AI adoption through workforce engagement management (WEM) applications in the contact center.
This global, multi-industry survey, conducted by research firm Frost & Sullivan for my company, examined who is preparing for AI and who is less prepared.
Key Findings:
- AI Adoption Surge. 65% of customer service operations plan to integrate AI into their cloud-based WEM applications within the next two years, aiming to enhance agent engagement and customer interactions.
- WEM Features and CCaaS Platforms. Only 30% of enterprises believe that WEM included in contact center-as-a-service (CCaaS) platforms are best suited for their organizations. This indicates a preference for multiple CCaaS platforms and blended operations involving contact center outsourcing providers.
- Migration to the Cloud. The study highlights the top reasons for migrating WEM to the cloud, including scalability, cost management, and accommodating fluctuating workstyles. Technology that connects remote or hybrid workers is crucial for workforce training and readiness.
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.
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.
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.
How the U.S. Can Get Back in the CX Game
What stood out from our recent survey is that the U.S is not in the leadership role and is trailing in several categories, even though Silicon Valley is still considered the cradle of AI and technology innovation.
I’ve seen underlying causes steering toward this shift throughout my professional experience and reviewing analyst research. These are worth discussing.
The U.S. has been in the enviable position of being the world’s leading economy for many years. The customer service function and its home, the contact center, were invented in the U.S. as far back as the late 1970s and early 1980s with the rise of American consumerism.
But American contact centers began to face new challenges:
- The ascent of the internet and addition of online channels in the late 1990s/early 2000s placed new demands on contact centers.
- The advent of the smart phone and social media in the 2000s took it all to a new level, placing the fate of a brand in the hands of digital consumers with increasing expectations of immediate gratification.
- Cloud computing gained traction in the first two decades of the 2000s, again by and in the U.S. But it wasn’t until the COVID-19 pandemic that struck in 2020 that the cloud became a necessity for managing operations with remote and hybrid agents.
The question arose, could contact centers be far more economical as well? The rules and tools had to be rewritten. The initial generations of cloud contact centers did not have the functionality customer service teams were used to, and this caused frustration with adoption. Now AI is another, even more profound, disruption in the field.
Other regions of the world, such as Asia-Pacific and Latin America, do not have these issues. That is because their CX industries were more nascent; they were born in the cloud/smartphone era with younger, digital native workforces that are ready and willing to embrace new technologies.
The AI Investment move
AI has the power to make agents much more efficient, productive, and insightful for customers, but not without training and new thinking.
There is a significant number of contact center professionals who, like our general population, are aging out of the workforce. Contact center operators are very conscious of this and try to hold onto legacy systems and legacy workforces as long as possible.
Factoring all this into the equation, U.S. CX is perfectly capable of raising its game to become the global innovator again. The answer is AI-powered workforce engagement management (WEM) that helps agents adapt to the new technologies.
To join in the game requires American contact center operators to make the upfront investments in the AI tools, as well as in training to show agents how their work lives can be made easier and their force multiplied with these technologies.
The rewards from winning are there. AI WEM solutions are designed to decrease job friction and increase satisfaction, leading to lower turnover rates and attracting a younger workforce that often chooses employers that offer the most advanced technologies.
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.
Focus on Emotional Intelligence. AI excels in data processing and automation, but human qualities like empathy, creativity and emotional intelligence remain irreplaceable. In customer service, demonstrating genuine empathy and understanding can significantly enhance customer satisfaction.
By honing your emotional intelligence and exercising uniquely human judgement, you can complement AI capabilities and provide a more personalized and humanized CX.
Collaborate With AI. AI is a powerful tool that can augment human capabilities rather than replace them.
In customer service, AI can handle routine queries, analyze customer data, and provide insights, allowing you to focus on complex and high-value tasks. Embrace AI as a collaborator that can streamline your workload, improve decision-making, and enhance overall efficiency.
Adapt to Change. AI adoption often brings about significant changes in workflows and processes by taking over repeatable tasks. This puts agents in a higher value role, requiring greater empathy and “people skills.”
With reportedly high churn rates in most companies, contact center agents need more training and support. Being adaptable and open to change is essential for thriving in an AI-enhanced environment. By staying flexible, you can quickly adapt to evolving AI applications and capitalize on new opportunities.
By continuously learning, you can stay ahead of the curve and make the most of AI-driven innovations.
Prioritize Data Privacy and Ethics. AI relies heavily on data, making data privacy and ethical considerations paramount. Ensure that you understand and adhere to data privacy regulations and best practices. Being mindful of ethical considerations, such as bias in AI algorithms, can help you maintain trust and integrity in customer interactions.
Communicate Effectively. Clear communication is key to successfully integrating AI into the workplace. Keep an open line of communication with your team and supervisors about the benefits and challenges of AI adoption. Share insights and feedback on how AI tools are impacting your work and collaborate to find solutions to any issues that arise.
Foster a Growth Mindset. Adopting a growth mindset means viewing challenges as opportunities for growth and development. Embrace the learning process, seek feedback and be proactive in developing new skills. A growth mindset will help you stay motivated and resilient as you navigate the changes brought about by AI.