The proliferation of artificial intelligence (AI) tools — particularly chatbots — is transforming the landscape of customer support. But not in the way you might think. For all the fearmongering about how AI chatbots will replace customer support agents, what we’re actually witnessing is the great potential of AI to complement human capabilities.
Today, the expertise of customer support professionals is best applied to complex issues requiring emotional intelligence — an area where AI simply can’t deliver. This shift toward proactive, empathetic support is more than an adjustment to one’s job description — it’s a strategic path to advancing one’s career.
With this shift comes a broadening of horizons, including new opportunities in content creation, onboarding, support strategy, and more. And it’s a journey that’s only just begun. As we continue working hand-in-hand with AI to unlock higher levels of customer engagement and professional fulfillment, these opportunities will only grow.
How AI is changing customer support roles
There’s no way around it: new AI technologies are reshaping both day-to-day tasks and long-term outlooks for customer support agents in meaningful ways.
AI not only empowers agents to shift their focus toward more high-value, high-complexity engagement with customers, but also to flex into new roles and responsibilities. Taken together, these trends reflect a blurring of the boundary between customer support and customer success.
We explore these trends more in depth below.
Greater focus on complex problem-solving
By leveraging AI to automate the resolution of simple, routine queries, agents now have more time to focus their efforts on proactively adding value to customer experiences. This gives agents more opportunities to leverage their emotional intelligence — a distinctly human strength. It’s a welcome shift for all involved, as agents excel at addressing customer complaints or concerns that require a nuanced understanding of emotions and context better than AI ever could.
Better career development opportunities
The automation of routine tasks has had a ripple effect on the career development of support agents. With time freed from mundane tasks, agents are now able to engage in other essential business activities — learning new skills and tackling new responsibilities in the process. This opens the door for internal promotions and allows agents to transition into new roles, benefiting both employees and the organizations they serve.
Blending customer support and customer success
With support moving away from transactional, one-off interactions, a more consultative approach emerges. As a result, the boundary between customer support and customer success is becoming increasingly blurred. This evolution places emphasis on guiding customers towards solving underlying problems, rather than simply addressing immediate questions or issues. Now more than ever, agents are well positioned to help customers understand how to maximize the utility of a product or service to address their customers’ unique challenges.
Emerging roles in customer support
Just as existing customer support roles are evolving, entirely new opportunities in the space are emerging — all in service of enhancing customer experience and driving efficiencies. Each new opportunity has a role to play in this unfolding transformation, working in tandem with AI to elevate both customer and employee experiences to new heights.
Below are some of the emerging roles that are shaping the new frontier of hybrid human and AI customer support.
Knowledge manager
The role of a knowledge manager is integral in ensuring that accurate and accessible support content is readily available. This content serves as the foundation for efficient customer problem-solving and consistency in information dissemination — whether by agents or AI bots.
Responsibilities
- Content creation and maintenance: Knowledge managers are tasked with developing and updating support resources. They play a pivotal role in keeping support materials relevant and up to date.
- Help center management: Ensuring the quality and relevance of help center content falls under their purview. They oversee the maintenance of a knowledge repository that remains an invaluable resource for customers seeking assistance.
- Conversation analysis: Assessing whether AI responses align with the genuine needs and queries of customers is a critical responsibility. Knowledge managers continuously monitor the effectiveness of AI-generated responses and make necessary adjustments.
Bot performance analytics: Knowledge managers are instrumental in enhancing AI performance by analyzing customer interactions. This data-driven approach allows for the refinement of AI responses to better meet customer needs.
Conversation designer
Conversation designers play a pivotal role in optimizing the overall support experience, with a primary focus on enhancing user satisfaction by streamlining interactions between customers, AI bots, and support agents.
Responsibilities
- UX mapping: To ensure a smooth and intuitive user experience, Conversation Designers meticulously map out the user journey. They are responsible for crafting interactions that align with customers' expectations and needs.
- Gathering and interpreting customer feedback: Utilizing customer insights is key to enhancing the support journey. Conversation designers actively collect and interpret customer feedback to identify pain points and areas for improvement.
- Problem-solving: Identifying and overcoming obstacles within the customer journey is a core responsibility. Conversation designers proactively address issues that hinder a seamless support experience.
Workflow creation: Crafting efficient processes for issue resolution is a critical aspect of this role. Conversation designers work to streamline support workflows, ensuring problems are resolved swiftly and effectively.
Conversation analyst
The conversation analyst role is instrumental in improving AI understanding and responses, ultimately enhancing customer interactions and providing valuable insights for company-wide decision-making.
Responsibilities
- Data analysis: Beyond numbers, conversation analysts delve into data to gain a deeper understanding of customer behavior and needs. They interpret data to derive actionable insights, informing support and other teams.
- Understanding of natural language processing (NLP): NLP lies at the heart of large language models. Conversation analysts need to understand how AI bots construct responses to ensure they align with customer queries and needs.
- Reporting insights: Communicating findings is a key aspect of their role. Conversation analysts provide clear and actionable insights, benefiting not only the support team but also other departments like product, marketing, and sales.
- Cross-team collaboration: Collaboration is essential for implementing improvements. Conversation analysts work effectively with various teams across the organization to ensure open communication and the implementation of key enhancements.
Support design strategist
The role of a support design strategist is to align AI and humans within the customer journey, ensuring efficient and effective support processes that cater to evolving customer expectations.
Responsibilities
- Process analysis and improvement: Continuously optimizing support processes is at the core of their responsibilities. They analyze existing processes and make improvements to meet rapidly increasing customer expectations.
- Strategy and planning: As AI integration becomes the industry standard, support design strategists play a crucial role in planning ahead. They assess what's working and what's not, and they set goals for the support team to strive for.
- Resource management: Creating an optimal human-AI support strategy requires a delicate balance of resources, including time, team members, tools, and budget. Support design strategists ensure this equilibrium is maintained.
Collaboration with other key roles: A holistic support strategy involves insights from the entire support team. Support design strategists collaborate effectively with other roles to create a comprehensive and cohesive approach to support.
Conclusion
The landscape of customer service is undergoing a transformative shift, where human agents and AI work collaboratively to maximize the customer experience. Customer service is no longer just a stepping stone in one's career journey — it’s emerging as one of the most exciting and dynamic professions.
As we embrace this change and journey alongside AI, the possibilities for growth, development, and professional fulfillment are boundless.
Intercom and Assembled enable growing support organizations to more efficiently manage and schedule their support teams, better anticipate their needs, proactively develop plans to scale efficiently across channels, and handle unexpected increases in support volume without agent burnout and without sacrificing personalized customer experiences.
