The Future of Customer Support: Beyond AI Implementation to Organizational Transformation

Customer Support is Changing AGAIN

AI in customer support is no longer just a technology investment—it’s a catalyst for true organizational change. The real work may not grab so many headlines, but it’s going to deliver big value” says Nick Clark, Partner in Boston Consulting Group’s (BCG) Operations Practice, on the future of AI in enterprise support organizations. As we look to 2025, support leaders should consider how AI can not only drive efficiency but also transform how support teams operate and deliver value.

For more on BCG’s perspective on AI capabilities, read their insights here.

The 10-20-70 Rule for AI Implementation

Clark highlights a realistic view on AI implementation with BCG’s 10-20-70 model:

• 10%: AI algorithms and use cases
• 20%: Technical infrastructure
• 70%: Transforming the operating model

“Only just over 10% of companies have Generative AI solutions operating at scale with measurable value so far,” Clark explains. Yet, the payoff is clear: clients who have successfully scaled report productivity gains of 20-30%, and in some cases even up to 40%. For support leaders, this model underscores the importance of focusing resources on reshaping the organization around AI, rather than investing solely in technology. 

From a Run Organization to a Change Organization

Support organizations are moving from operational centers to becoming innovation drivers. Clark describes this shift: “We see customer support evolving from a primarily run-focused organization to one that emphasizes change.” This transformation requires new capabilities that include:

• Creating and optimizing knowledge content
• Managing AI processes
• Overseeing security and compliance
• Developing continuous improvement cycles

By shifting to a change-oriented model, customer support teams can drive sustained improvement in both operational efficiency and customer satisfaction.

Value Realization: Prioritizing Growth Over Cost Cutting

Clark shared an example of a SaaS company that’s investing in AI to enhance service levels rather than cutting costs. He noted, “This company has seen shorter turnaround times and improved resolution rates, which has enabled them to deliver better service levels without slashing their support headcount.” This growth-focused approach drives:

• Improved service quality
• Faster issue resolution
• The ability to handle complex inquiries
• Scalable support operations

Leaders in support need to look beyond short-term cost reduction and prioritize growth by using AI to deliver a differentiated customer experience.

The Evolution of Support Engineering

As customers become more self-sufficient with automated resources, support engineers are seeing a shift in the types of issues they handle. Clark observes, “When cases reach a support engineer now, they tend to be high-severity or more ambiguous issues, sometimes even requiring escalation to product teams.” This shift demands dual expertise from support engineers:

1. Technical proficiency with AI tools
2. Strong stakeholder management skills

A key differentiator is the ability to interact effectively with AI tools—“Knowing what to ask the AI to get the right answer really sets the top performers apart,” Clark points out. This emerging skill set enhances engineers’ ability to resolve complex issues while delivering a positive customer experience.

Building Trust in AI-Enabled Support

Implementing AI tools requires thoughtful change management. “When a bot suggests a solution, employees can sometimes feel disempowered,” Clark notes. The key is to build tools that empower agents rather than diminish their role, helping them to feel that AI is an enabler of their expertise. This change management approach fosters greater trust among employees and helps with AI adoption, ensuring agents bring their best skills to the table.

Looking Ahead: 2025 and Beyond

The future of customer support will focus on consolidation and value realization. Clark foresees three major trends:

Data-Driven Operations
“We’re seeing more support teams gaining access to telemetry data. For instance, a cobot might notify an agent that a customer has only logged in three times, helping provide context and personalized support.”

AI-Powered Management Tools
“An area ripe for AI improvement is workforce management. If we can understand deeper reasons behind customer interactions, we can forecast needs more accurately.”

Proactive Support Integration
“Moving support from a separate function into the product itself is the next frontier,” Clark explains. Embedding support experiences directly into products can enhance the customer journey and reduce reliance on reactive support channels.

The Customer-First Imperative

Clark’s final advice cuts through the noise: “Always go back to the end customer and understand what they want.” He warns against designing customer journeys focused on deflection and containment, as they can lead to poor customer experiences. Instead, support organizations should use AI to empower customers to solve their issues in ways that align with their needs.

Key Takeaways for Customer Support Leaders

• Focus on Value Creation Over Cost-Cutting: Use AI to enhance service, not just reduce costs.
• Empower Your Team: Implement change management strategies to support AI adoption by empowering agents.
• Keep Customer Needs at the Center: Prioritize initiatives that deliver real value to the customer, not just operational efficiency.

The organizations that will excel are those that view AI as a strategic lever for elevating the entire support function—one that benefits customers, employees, and the company alike.

For support leaders looking to prioritize a customer-first approach, AptEdge is pioneering solutions that streamline workflows for support engineers, enabling them to resolve complex issues faster and more efficiently. To learn more about how AptEdge is transforming customer support with AI-driven insights and integrated workflows, visit www.aptedge.io.