AI is increasingly being used to process routine tasks in customer experience. We know that artificial intelligence (AI) excels at sorting through large amounts of information and recognizing patterns. But some AI tools can fall short at meeting a customer’s emotional needs or cannot see a task through to completion. And human agents are often left to deal with the consequences.
As AI increasingly manages routine, simple matters, some unintended consequences can emerge:
- Customers can feel devalued when forced to deal with an AI agent that doesn’t meet their needs. They vent their anger at human agents when they are finally able to reach one.
- The learning curve for human agents is disrupted. Junior agents don’t gain the benefit of handling the more routine interactions and the learning that occurs at that stage.
- Human agents end up handling only the complex and emotionally demanding interactions, leading to agent burnout and turnover.
It doesn’t have to be that way. These issues can be minimized or avoided with thoughtful use of AI that can both enhance human performance and improve customer experience.
Design for Resolution, Not Deflection
Protect your agents from the “angry handoff” by designing AI experiences that prioritize resolution over deflection. When the goal of automation is genuine assistance rather than simple deflection, the human agent inherits a manageable task instead of a frustrated caller.
Design the experience to include:
- An “escape hatch”: A human agent should be easily accessible to customers. If an AI agent senses repetitive questioning or sentiment-based frustration, it should proactively offer a transfer.
- Contextual handoffs: There’s nothing more aggravating than reaching a human and having to repeat everything you just told the bot. A well-designed system passes the full transcript and intent to the agent instantly.
The Paradox of Automation: Protecting the Human Talent Pipeline
By delegating all simple queries to AI, we inadvertently disrupt the traditional human learning curve. Historically, agents learned by handling routine interactions. These low-stakes tasks provided the foundational knowledge required for them to become senior agents needed to manage complex cases requiring empathy and judgment.
When AI oversees a very simple task, new human agents are thrust into complex situations without the benefit of a foundational learning phase. To prevent this, management must be intentional about developing the skills of human agents by:
- Identifying which “routine” interactions are truly vital for long-term proficiency and ensuring that beginning agents have full exposure to them.
- Protecting introductory roles where human agents are permitted to be slower and more expensive than AI. This isn’t a cost—it’s an investment in developing the seasoned experts of tomorrow.
- Creating explicit career progression. If a career path isn’t articulated, it doesn’t exist. Progression from junior to senior roles must be mapped out with clear milestones.
Strategic Augmentation
When used strategically, AI can be used to resolve this paradox. AI can collaborate with agents to augment their capabilities and capitalize on the human skills that provide customers with empathy and answers that feel human.
However, a one-size-fits-all approach to AI augmentation fails both the agent and the customer. Instead, AI augmentation should be applied dynamically based on the agent’s tenure and the complexity of the task.
Junior or trainee agents need a coach that provides prompts, suggests resources and explains why a step is taken. This allows them to build foundational knowledge and judgment.
Intermediate agents benefit from AI that automates data entry and suggests next best actions, while allowing the agent to lead the interaction. With AI as an assistant, agents can improve efficiency and increase speed while maintaining quality.
Experienced agents who oversee complex cases can use AI as a research tool that allows them to focus on empathy and strategy. This enables them to more quickly solve the most difficult “edge cases” while ensuring that customers’ emotional needs are met.
The golden rule: In the early stages of a career, AI should be used as a training tool to teach humans how to do the work, rather than simply doing the work for them.
Strategically varying the level of AI augmentation ensures that technology elevates the human agent rather than making them obsolete.
Managing the Complex-Only Queue: Mitigating Human Agent Burnout
When AI successfully manages all simple, transactional inquiries, the human agent’s workload becomes entirely composed of the most complex, ambiguous, high-stakes or emotionally charged interactions.
This creates a complex-only queue, eliminating the psychological benefit of “easy wins.” Continuous exposure to high-intensity customer issues accelerates mental and emotional fatigue, primarily manifesting as:
- Compassion fatigue: The constant need for deep emotional labor when dealing with distressed, angry or desperate customers rapidly drains mental reserves.
- Increased cognitive load strain: Sustained complex problem-solving requires significantly more mental energy than following routine processes. Agents must constantly apply nuanced judgment, leading to mental fatigue without respite.
- Loss of control and motivation: A perpetual struggle against difficult challenges erodes the feeling of mastery. Consistent stress can severely decrease job satisfaction, leading to withdrawal and burnout.
Solutions for Agent Well-Being
Organizations must address factors that could degrade agent well-being by incorporating tactical and strategic processes designed to support human agents.
Tactical Solutions
These immediate solutions focus on providing support and necessary mental breaks:
- Mandated decompression time: Implement formal, scheduled breaks between complex interactions that agents cannot skip. This time must be reserved strictly for a mental reset, not for administrative work. Software tools are available that recognize stressful interactions and provide agents with short mental breaks when needed. Metrics show that these tools improve agent productivity.
- Peer support and mental health resources: Provide accessible and destigmatized training and tools focused on managing compassion fatigue.
- Complexity rotation: Structure shifts to allow agents to rotate between various levels of task complexity (e.g., integrating time for less complicated tasks or internal support) rather than permanently assigning them to the most difficult queue.
- Training in strategic empathy: Coach agents on how to use empathy effectively, teaching them to set necessary emotional boundaries to protect themselves while still providing genuine connection.
- Continual evaluation and improvement of the customer journey: Analyze points that create friction and make proactive design improvements to reduce customer frustration. It’s much easier for agents to handle a customer with a question, instead of an angry, frustrated escapee of a bad experience.
Strategic Solutions
The stress from the complex-only queue can create high turnover. Reducing turnover requires mitigating burnout and focusing on recognition, compensation, and career development to match the increased specialization of the role:
- Elevate compensation and title: Recognize that the agent is now performing a highly specialized role. Adjust compensation and job titles to reflect the higher level of cognitive labor, emotional intelligence, and critical decision-making authority required.
- Invest in soft skill development: Provide advanced training that goes beyond product knowledge focusing on advanced “soft” skills such de-escalation techniques, and complex case management. Investing in agent growth increases job commitment and perceived value.
- Formalize recognition of “human wins”: Implement a formal recognition system that specifically rewards outstanding empathy, and successful complex problem resolution, rather than just speed or volume.
- Demonstrate concern: Leadership must actively monitor the effective utilization of mandated decompression time and caseloads. Agent well-being must be viewed as a core business priority.
Conclusion
It can be tempting to use AI to gain quick wins by automating routine tasks. However, taking a long-term view will help to avoid customer frustration, agent burnout and turnover. And it will help ensure there’s a pipeline for building human expertise.
Human empathy and critical thinking skills are still essential. AI augmentation that enhances human capabilities takes advantage of the strengths of both AI and humans, making them better together.
Global Tech specializes in helping contact leaders to identify AI technology solutions that deliver measurable results. Further resources on AI best practices can be found here.
This article was originally published on the Genesys blog here.
