Key takeaways

• Government contact centers face the same operational challenges as enterprises, as well as the extra pressure from elections, regulation and the need to prove value to taxpayers
• Citizens compare government interactions with their experiences at banks, retailers and healthcare providers, so outdated channels and processes are increasingly visible
• Generative AI can turn public information, training material and call recordings into human-like virtual assistants and powerful agent-assist tools
• By improving citizen outcomes, efficiency and back-office workflows, contact centers can become growth and value engines for governments
• The future is an ecosystem of AI agents and specialist partners, with human staff evolving into supervisors and curators of AI-driven experiences

Joseph Solt, Director of CCaaS AI Sales and Strategy at HCLTech, spends much of his time working with public sector organizations on the front line of citizen engagement. In a recent episode of the HCLTech Trends and Insights podcast, he explored how government agency contact centers are changing, and what it will take to keep pace with citizen expectations in the GenAI era.

From rising enquiry volumes and staff shortages to new AI-powered capabilities and mounting regulatory demands, the contact center has become a strategic focal point for public services. For Solt, the key message is this is not a minor technology upgrade but “really a revolution” in how government interacts with citizens. Agencies that lean in will set a new benchmark for service. Those that wait risk falling further behind with every election cycle.

Unique challenges facing government contact centers

Government agency contact centers share many of the same pressures as their enterprise counterparts. Solt points to “increasing volumes across all the different channels and social media, staffing shortages [and] trying to overcome the costly recruitment and training cycles needed for new contact center agents.” At the same time, teams are expected to improve service levels and performance KPIs while demographics, expectations and technology all shift rapidly.

But the public sector also carries additional burdens that make transformation harder. Priorities can change dramatically “every election cycle,” with new leadership bringing “different goals, different priorities and maybe campaign promises” that agencies must then honor through their services. Many departments must also meet “strict compliance” requirements, “things like FedRAMP that they need to adhere to,” and justify spend with a “very strict and demonstrable value to citizens and taxpayers for everything that they do.”

Perhaps the biggest challenge, though, is that citizens don’t separate their expectations for public and private services. “The same citizens who are calling these government institutions are also the consumers calling the enterprise business,” explains Solt. Someone might “pick up the phone and call their local city line to report a missed trash pickup,” then hang up and call a bank about a card dispute or use a retailer app to track a delivery. Naturally, “we are comparing those experiences…we just want that contact center solution to work, to help us make our lives easier, doing our tasks efficiently.”

Governments have historically struggled when “they haven’t leaned in, they haven’t modernized...and that becomes glaringly obvious to their citizens.”

Using Generative AI to unlock public data and improve citizen journeys

Government agencies are uniquely rich in data: policies, forms, letters, FAQs, guidance and decades’ worth of interaction history. Generative AI (GenAI) makes it possible to turn that static content into dynamic, conversational experiences.

“Generative AI can be used in a lot of different ways within the contact center space,” says Solt. Crucially, “government agencies have mountains of data that’s already available and therefore can be utilized by these GenAI engines.” Publicly available information, such as “FAQs and forms and letters and all this content,” can effectively serve as a ready-made knowledge base. With the right guardrails and integrations, “you can use that to create human-like experiences...voice bot [and] chat bot types of solutions that are completely AI driven, based off all the data that you already have available.”

Internal assets like training materials, agent scripts and manuals “can be consumed by GenAI to help ensure that [the] engine is using the same bespoke business processes and information that your human agents are.” Even contact center recordings can feed into “instructions and guardrails” so AI assistants “act the same way as your human agents.”

Solt also highlights more advanced capabilities such as computer vision. Instead of asking a caller to read out multiple fields from a form or a ticket, “use the AI engine to just send it that picture and it can ascertain the information it needs, instead of this long, drawn-out step-by-step process.” This creates “that level of efficiency within these types of solutions,” reducing friction for citizens and freeing staff to focus on more complex cases.

Ultimately, “AI does a really good job of consuming large amounts of data,” he notes. The more agencies can securely share with their AI engines, the more those tools can identify patterns in call drivers and resolution steps, assist with “next best actions and helpful hints” and support both citizens and agents in real time.

From service channel to strategic value engine for the public sector

A previous podcast in the HCLTech series explored how enterprise contact centers are transforming into growth engines. Solt believes that the same principle applies to government, though growth is more about public value and outcomes than revenue.

One of the most important opportunities is simply to “meet [citizens] where they are,” whether that’s “on a voice channel or a chat channel or on social media,” and to do so “in a connected, reusable type of way.” By creating “conversational, personalized, helpful, efficient types of solutions,” agencies can make it easier for people to access services, complete tasks and resolve issues; strengthening trust and satisfaction.

Behind the scenes, AI can also transform the day-to-day experience and productivity of human agents. Using data to power “agent assistance,” real-time next-best action guidance or “helpful hints…as they’re talking to citizens” makes each agent “more efficient.” Capabilities like real-time language translation help shorten handle times and support more inclusive service, while smarter routing ensures enquiries reach the right expert faster; “immediately inject[ing] a level of savings into your overall contact center.”

Solt emphasizes that the impact extends beyond the call itself. Every citizen interaction “creates a level of process behind the scenes,” such as a ticket to investigate, a tow truck to dispatch, a court date to schedule or updates to multiple systems and agencies. These back-office procedures are fertile ground for AI-driven orchestration and automation. By “tracking…and coordinating of all those things” with AI, agencies can move from a narrow view of voice and chat to “really starting to drive value down through all of the back-office procedures as well.”

The autonomous, Agentic AI future of government contact centers

Looking further ahead, Solt sees an even more radical shift on the horizon. He notes that Gartner predicts that “by 2029 Agentic AI will resolve 80% of consumer service issues without any human intervention needed at all.” While that “sounds like science fiction,” he believes this outlook is “pretty conservative” and that it will be achieved sooner.

“Our north star for the contact center is a vision to have an autonomous solution...with [a] framework of AI agents that are trained in very specific skill sets [in a] network that’s working together.” These AI agents would “control the agent desktop, integrate to CRM and other back-office systems and solutions,” using large language models, computer vision and other capabilities “to replace the need for historic IVRs, voice bots and chat bots, while significantly reducing the amount of interaction needed from human beings.”

In that model, “your human agents basically become supervisors or curators of the AI content,” only stepping in for complex or sensitive situations, as well as fine-tuning prompts and policies and overseeing quality and fairness.

Importantly, the journey doesn’t have to be all-or-nothing. Agencies can take “tangible iterative steps” that gradually move them along this path, starting with targeted use cases like AI-assisted FAQs, agent-assist or back-office workflow automation, before then expanding as trust, skills and governance mature.

What will become increasingly visible, says Solt, is the gap between the “organizations and the agencies that start to lean in versus the ones that continue to sit on the sidelines.”

Why ecosystem partnerships will define the next era

The contact center “revolution” is evolving rapidly and represents both a “complete paradigm shift” and a real source of pressure for government agencies. Many face “staffing limitations” or “may not have the skill sets to be able to consume all those types of things” across GenAI, Agentic AI, cloud architectures and 24/7 operations.

To navigate this complexity, ecosystem partnerships will be critical. Agencies need providers that can not only “create the cutting-edge citizen experiences” and “help your human agents,” but also manage secure cloud infrastructure, deliver “24/7 managed services and monitoring” and even offer fully hosted or outsourced solutions where appropriate. For smaller state and local agencies in particular, this support can bridge limited capital and skills, allowing them to focus on their core mission, while specialist partners “focus on the contact center for you.”

In the coming years, the most successful public sector contact centers are likely to be those that pair bold experimentation with strong governance and the right ecosystem of partners; turning today’s operational headache into tomorrow’s strategic asset for citizens.

FAQs

1. Why are citizen expectations for government contact centers changing?

Citizens now interact daily with highly polished digital experiences from banks, retailers and healthcare providers. When government contact centers lag behind in channels, speed or ease of use, the gap is more visible and more frustrating than ever.

2. How can Generative AI make public services more accessible?

Generative AI or GenAI can turn complex policies, forms and FAQs into conversational assistants that speak citizens’ language. Voice and chat bots can guide people step by step, while real-time language translation supports those who prefer or require other languages. Combined with computer vision, such as reading information from a photographed form, these tools reduce the cognitive and administrative burden on citizens.

3. What’s a practical first step for agencies starting contact center modernization?

A sensible starting point is to map your top contact drivers and identify high-volume, repetitive enquiries, such as basic eligibility questions or form-related queries. Agencies can then pilot AI-powered self-service or agent-assist for a small set of use cases, using existing FAQs and scripts as a knowledge base. This delivers quick wins while building internal confidence and governance frameworks.

4. Will AI replace human agents in government contact centers?

AI will increasingly handle routine enquiries and orchestrate back-office tasks, but human agents will remain central, especially for complex, sensitive or high-stakes interactions. The role will shift as humans become supervisors or curators of the AI content, focusing on empathy, judgment, oversight and exception handling, while AI manages much of the repeatable work.

5. How should government agencies choose the right ecosystem partners?

Agencies should look for partners with a proven track record in both public sector compliance and modern contact center technologies. Important capabilities include secure cloud hosting, 24/7 monitoring and support, expertise in GenAI and Agentic AI, and the ability to integrate with existing systems. Equally important is a collaborative approach to governance, change management and skills development for internal teams.