
Expand Self-Service with Intention
Self-service should be designed with purpose, not as an afterthought. Contact Centers should work with agency customer experience teams to analyze real call data to identify the top 100 contact drivers and then design tools to allow customers to resolve issues without requiring human intervention. Effective self-service means getting people to a resolution on the first interaction. To be successful, self-service solutions must reflect real user behavior and needs, not internal agency assumptions.
Invest in Internal Agentic AI Tools
Agentic AI is not just for customer-facing applications; it is a powerful internal tool that transforms how agents work, especially in real time. Modern agent assist tools support staff during live calls by surfacing relevant knowledge articles, recommending next-best actions, summarizing case history and call sentiment and offering rapid responses. By reducing cognitive load, contact centers staff can work smarter, respond faster and deliver more consistent service while focusing on the human side of service – empathy, listening and trust-building.
Shift to Cloud-Native, Configurable Tools
To accelerate deployment and reduce risk, contact centers should shift to cloud-native solutions – or technology solutions specifically created to run on cloud computing platforms – that are flexible and configurable. Unlike traditional legacy systems, these tools can often be launched in days and adapted over time to meet evolving needs. Prioritizing cloud-native platforms not only enables smoother integration across departments and ensures that modernization efforts are future-ready, but it can also reduce the data center footprint and is a lower cost of ownership. However, this shift requires intentional change management to ensure buy-in and minimize disruptions to staff and service delivery.
Effective Rollout of AI Tools
AI systems require thoughtful onboarding, context and continuous feedback loops to be effective just like humans do. Interviewees emphasized the importance of strong knowledge bases, user-centered design and seamless collaboration between customer experience, IT and contact center teams. This collaboration is especially critical when rolling out new tools or processes. Clearly communicating how potential tools can help agents perform their work, incorporating input from frontline staff during development and testing ensures the tools are useful, boosts adoption and reduces friction. When employees feel supported and part of the process, it can lead to more consistent, empathetic and effective service delivery. In short, investing in the employee experience is foundational to achieving better outcomes for the public.
Implement Robust Governance Structures
Agencies must establish clear leadership and accountability structures for both contact center operations and modernization efforts. This includes designating responsible teams or individuals to oversee strategy, coordinating across departments and ensuring alignment with broader CX, IT and digital transformation goals. Without strong governance, even the best tools and strategies can falter in execution. Effective governance also ensures that customer insights and operational data inform agency-wide decision-making, not just contact center metrics.
Invest in Workforce Upskilling
Providing continuous training and support is essential to prepare employees for modern contact center environments. As roles evolve and AI becomes further integrated into daily workflows, staff must be equipped with new skills in order to use the tools and understand how to evaluate and act on the content generated by these technologies, how to handle complex exceptions and how to manage high-value, emotionally sensitive interactions. Importantly, upskilling does not need to be resource intensive. Agencies can begin with small-scale efforts such as deploying microlearning modules or hosting internal town halls to build AI literacy and reduce uncertainty among staff. Interviewees also emphasized that frontline agents – especially those working through contractors – often require different engagement strategies, targeted change management and clear, consistent feedback mechanisms to deliver the high-touch service the public expects.
Rethinking Metrics Beyond a Checklist
Call center leaders and staff need to look at metrics such as average handle time and ticket closures beyond a “checklist” lens – these metrics simply open the door for understanding a problem, not the final point. Collecting significant amounts of data without better customer sentiment analysis and storytelling to drive decision-making is not efficient or effective in resource-constrained environments. Instead, agencies should ask, “Did we solve your problem?” and adopt trend-based coaching approaches to drive better agent performance. AI analytics tools, which can monitor every call and aggregate the data to true analysis of sentiment, can reveal the root causes and thereby help agencies come up with better solutions.
Build a Tiered Contact Center Model
A modern contact center must operate with a tiered model: Tier 1 and Tier 2 interactions can increasingly be managed by virtual agents or self-service tools. Tier 3 interactions (i.e., those that are complex, sensitive, or emotionally charged) should be escalated to human agents. By the end of this decade, most routine inquiries, including those that require empathy, nuance and discretion, will be resolved through advanced AI, while human agents will increasingly focus on exceptional cases where human judgment remains essential. The success of this model depends on well-designed, transparent escalation paths. Emerging large language models power agentic AI that enables virtual agents to go beyond basic guidance – these tools can also serve as proactive digital assistants, guiding users through next steps, explaining decisions, providing information and even completing transactions.
Enhance Knowledge Management
Centralizing and maintaining up-to-date knowledge repositories is essential to ensure consistent and accurate responses across all contact channels. AI can then be applied to automate knowledge delivery – both to customers and agents – so that the right information surfaces at the right time. Good knowledge management not only improves service quality but also reduces training time and increases agent confidence.
Establish an Effective Change Management Program
As noted above, an effective change management program both within the agency and with the public is key to successfully integrating emerging technologies and tools. This means engaging employees, especially those on the front lines, early in the process to shape the design and rollout of new tools. Leadership must visibly demonstrate support of the change. Clear, consistent communication that explains the purpose and benefits of the transformation can help reduce resistance and build trust.
As previously highlighted, call center leadership must also prioritize employee training and create the necessary feedback loops to continuously improve operations, service quality and the integration of emerging technologies based on employee and customer feedback. These efforts must be ongoing to help call center employees shift behaviors, successfully adopt emerging technologies and tools, and deliver better service.
Engage the Public
Finally, there is a need to educate the public as new technologies are introduced. Self-service tools, virtual agents and AI-based systems only succeed if customers understand how to use them and trust that they will work. Clear communication, thoughtful directions and marketing, and user-centered design are essential to ensure adoption and build confidence. An effective change management program both within the agency and with the public is one of the critical success factors.