When you think about industries known for outstanding customer service, government may not spring to the top of the list. Because government agencies don’t face the same competitive pressures as private-sector businesses, they’ve historically had little incentive to devote time and resources to improving experiences for their constituents. But today, public-sector organizations are facing pressures to modernize their services and improve experiences for both citizens and employees, and artificial intelligence (AI) is leading the way in driving progress towards their goals.

Keeping up with constituents

When the pandemic forced brick-and-mortar service providers to close their doors, traditionally in-person services in industries such as banking, dining, education, and even healthcare quickly became widely available via digital platforms. This development produced a dramatic shift in customer expectations, and suddenly the concept of taking time off work to stand in line at a government office came to be viewed as a glaring anachronism.

As Sha Hwang and Annelies Goger of the Brookings Institution recently noted, “The frustration many Americans experience in even the most basic interactions with government—like renewing a driver’s license or filing taxes—fractures trust in our institutions, which is already near historic lows.” In an effort to turn the tide, United States President Joe Biden signed an executive order calling on federal agencies to make services—particularly digital services—easier to use, more modernized, and more transparent.

Retaining top talent

Another unforeseen outcome of the pandemic is the “Great Resignation,” the wave of post-lockdown job changing that began in the spring of 2021—driven primarily, as a Gallup survey revealed, by workers who identified as being “not engaged” or “actively disengaged”. While quit rates within the federal government remained relatively steady, the Rockefeller Institute of Government reports that the employment level in state and local government is still 928,000 below where it was before the pandemic hit.

The Great Resignation became a wake-up call to employers across industries about the importance of employee experiences as workers proved their willingness to seek elsewhere for stimulating work. Government agencies hoping to retain their own top talent are recognizing a vested interest in building experiences that inspire and engage the people who keep their services running.

Given the current state of affairs, government organizations on all levels—federal, state, and local—need strategies that elevate both citizen and employee experiences while optimizing the use of their resources.

What is total experience (TX)?

Total experience for government entities, according to Gartner, combines the disciplines of user experience (UX), citizen experience (CX), employee experience (EX) and multiexperience (MX) into one holistic approach toward service design and delivery. A TX strategy ensures that resources across CX, EX, UX and MX disciplines collaborate to uncover new opportunities for improved service delivery that increases both citizen and employee satisfaction and improves the government’s mission outcomes.

The approach made the research firm’s list of Top 10 Government Technology Trends for 2022, on the grounds of its ability to drive progress towards the high-priority goals of retaining top talent and improving the delivery of citizen services. Principal Research Analyst Apeksha Kaushik recently commented, “Governments must move from a siloed approach to a cohesive strategy encompassing employee experience and citizen experiences across multiple platforms, channels, and technologies in the most intuitive user experience.”

The role of AI in improving TX

As government organizations explore strategies for achieving their TX goals, many are looking to the private sector for inspiration, and many of those inspiring stories center around the use of artificial intelligence. In businesses across industries, technologies such as machine learning, natural language processing (NLP), and natural language understanding (NLU) are enabling transformative experiences that benefit customers and employees alike. Here are just a few examples of AI-driven technologies that are helping businesses build a better TX.

Customer-facing chatbots

Chatbot technology has come a long way in recent years, and customer service teams in industries as diverse as banking, travel, and telecom are reaping the benefits. Chatbots enable customers to self-serve in fulfilling simple requests like resetting passwords or scheduling appointments. Because the bots are available 24/7, users can access services at their own convenience and avoid waiting on hold. On the employee side, agents are freed from rote tasks and can focus their attention on more complex cases that call upon their expertise as well as their people skills.

Intelligent process automation

Intelligent process automation uses AI-driven tools such as intelligent document processing, process mining, and predictive analytics to help organizations gain greater understanding of and control over their operations.

• Process mining delivers the data-driven insights teams need to remove bottlenecks and streamline workflows.
• Intelligent document processing extracts the data locked away in documents and feeds it directly into business processes to speed up workflows.
• Predictive analytics enables businesses to perfect process performance and optimize the use of resources.

Intelligent process automation enables employees to benefit from faster, smoother processes that minimize the need to track down paper trails or troubleshoot procedural breakdowns, while customers benefit from faster overall service delivery.

Customer sentiment analysis

When customers contact a business, machine learning and NLP tools can “listen in” to determine the caller’s intent, evaluate their emotional state, and even detect possible fraudulent behavior. For example, Deloitte’s Behavioral and Emotion Analytics Tool (BEAT), developed for the financial services industry, monitors voice interactions to devise a “risk score” based on word choice, rate of speech, and other factors. The higher the score, the more the agent can be on alert for a potential complaint or possible fraudulent activity.

Identity proofing and affirmation

For industries at high risk for fraud, such as banking and insurance, offering mobile services such as customer onboarding and claim filing presents the dilemma of how to ensure that users are who they claim to be. With identity proofing and identity affirmation, users provide proof of their identity via identification (ID) cards, photos, and supporting documents, and AI-based tools step in to read, verify, and authenticate the submissions, including facial matching against a real-time “selfie.” Employees are freed from the tedious task of reviewing and verifying customer documents, and customers can enjoy historically in-person-only services with a few taps on their smartphones.

Government use case: Mobile identity verification for DMV offices

One government interaction nearly everyone can relate to is applying for or renewing a driver’s license at the U.S. Department of Motor Vehicles (DMV). As ABBYY recently told Federal News Network, “Everybody has had the experience of going into the department of motor vehicles and standing in line. It doesn’t mean you didn’t receive good service. But standing in line or taking time off work can be a big challenge and inconvenience.”

A secure mobile application can eliminate the need to go to the DMV office and wait, as long as it solves the key problem of enabling applicants to securely verify their identities. Document-centric identity proofing and affirmation allows users to submit photos of key documents, including IDs and utility bills, and take real-time selfie photos for comparison.

The California DMV has adopted this approach for its services, and the results have been impressive. “We’ve gone from 28 minutes per Real ID transaction to about 10 minutes,” Ajay Gupta, chief digital transformation officer at the California DMV recently told GCN. “AI-driven pre-screening is one of the reasons why we are able to do that. It also reduced customer visits because there are reduced returning customers due to incomplete documentation.”