Artificial intelligence is increasingly moving beyond citizen-facing applications and into the internal systems that support public-sector employees. Atos has been selected by Barcelona City Council’s Municipal Institute of Innovation and Technology (BIT) to help modernize the technological services used by thousands of municipal professionals, combining automation, data analytics, knowledge management and generative AI to improve day-to-day digital support.
The project reflects a broader shift in enterprise IT: internal technology support is evolving from a reactive help-desk model toward services that can automate routine requests, anticipate problems and give employees faster access to information.
Atos will work with BIT, the organization responsible for leading Barcelona City Council’s digital transformation, to evolve customer care and technology support services for municipal employees.
The planned changes include expanded self-service capabilities, new in-person service spaces, tools designed to accelerate incident resolution and data-analysis systems intended to identify recurring needs and opportunities to improve support services.
Artificial intelligence is also expected to play a role, particularly in accessing organizational knowledge and supporting service teams. Atos said the project will explore generative AI capabilities alongside advanced knowledge management and automation of repetitive processes.
From Help Desk to Intelligent IT Service
Traditional IT support typically operates after a problem occurs: an employee encounters an issue, submits a ticket and waits for a support team to diagnose and resolve it.
That model is increasingly being challenged by automation and AI.
Enterprise service management platforms can now automate routine requests, route incidents based on context, recommend solutions and surface relevant knowledge before an employee needs to contact an agent. Generative AI adds another layer by allowing workers to interact with organizational knowledge through natural-language interfaces.
For a public administration with thousands of employees, even relatively simple improvements can have significant operational consequences.
Automating password-related requests, access questions, common software issues or routine service procedures can reduce the volume of work handled manually by support teams. More complex incidents can then receive greater attention from human specialists.
The objective is not necessarily to eliminate human support, but to reserve it for situations where human judgment adds the most value.
Generative AI Enters the Internal Workplace
The inclusion of generative AI is particularly significant because enterprise adoption is increasingly shifting from experimentation toward specific workflow applications.
In Barcelona’s case, the technology is being considered for knowledge access and support operations rather than positioned as a general-purpose AI deployment.
That distinction matters.
Generative AI can potentially help employees locate information spread across policies, technical documentation and service procedures. It can also assist support teams in finding relevant information more quickly when responding to incidents.
But public-sector environments introduce additional requirements around data governance, security, accuracy and accountability.
AI-generated answers need to be grounded in authoritative organizational information, while access controls must prevent employees from retrieving information they are not authorized to see.
As a result, the value of generative AI in internal IT will depend not only on model capabilities but also on the quality of the underlying knowledge architecture.
Data Could Shift IT From Reactive to Proactive
Another important component of the project is advanced data analysis.
Instead of viewing support tickets as individual incidents, organizations can analyze aggregated service data to identify recurring problems, bottlenecks and emerging employee needs.
For example, repeated incidents involving a particular application could indicate a training gap, configuration problem or broader system issue. A rise in requests around a particular process could signal that the process itself needs to be redesigned.
This turns IT support data into an operational intelligence resource.
The same principle is becoming increasingly common across enterprise technology, where organizations are attempting to connect service management data with employee experience, security, application performance and business operations.
For Barcelona City Council, that approach could help BIT identify improvements before they become widespread employee frustrations.
Public-Sector Digital Transformation Gets More People-Centric
The project also highlights a change in the definition of digital transformation.
Public-sector modernization is often associated with digitizing citizen services, moving applications to the cloud or replacing legacy infrastructure. Internal employee experience is equally important, however, because municipal workers depend on those systems to deliver services to citizens.
If employees spend less time navigating cumbersome technology processes, they can potentially spend more time on their core responsibilities.
BIT manager Emili Rubió emphasized this people-centric dimension, arguing that digital transformation depends not only on the platforms an administration uses but also on the experience provided to the people working within it.
Atos director in Catalonia Juan Carlos Díaz said the project will combine innovation, automation and artificial intelligence to evolve the digital experience of municipal professionals.
The Enterprise AI Question Is Moving to Operations
The Barcelona project illustrates where enterprise AI adoption may be heading next.
Rather than treating AI as a standalone technology initiative, organizations are increasingly embedding it into established operational workflows.
For IT departments, that means AI-assisted service desks, automated workflows, intelligent knowledge search, predictive analytics and increasingly autonomous resolution of routine tasks.
For employees, the experience could eventually become simpler: describe what is needed in natural language, receive an immediate answer or automated service, and involve a human specialist only when the issue requires deeper intervention.
That model could be particularly valuable for large public organizations managing complex technology estates and diverse employee groups.
The challenge will be ensuring that automation improves service quality without creating new layers of complexity. Effective implementation will require strong data governance, reliable knowledge sources, clear escalation paths and human oversight.
If those foundations are in place, Barcelona’s initiative demonstrates how AI can become less about experimentation and more about quietly improving the digital infrastructure employees use every day.
Market Landscape
The project sits at the intersection of several enterprise technology markets:
- AI-powered IT service management: Automating support requests and assisting service agents.
- Generative AI: Providing natural-language access to enterprise knowledge and support information.
- Knowledge management: Organizing institutional information so employees and AI systems can retrieve it effectively.
- Intelligent automation: Removing repetitive manual processes from internal services.
- Employee experience technology: Improving how workers interact with enterprise systems.
- IT analytics: Using service data to identify recurring problems and anticipate demand.
The competitive landscape includes platforms and ecosystems from Microsoft, ServiceNow, Salesforce, SAP and other enterprise technology providers, alongside global IT services companies such as Atos that integrate multiple technologies into large transformation programs.
The differentiator increasingly will not be access to an AI model alone. It will be the ability to connect AI with an organization’s existing workflows, data, knowledge and governance systems.
Top Insights
- Atos will modernize Barcelona City Council’s internal technology services, targeting faster support, simpler processes and a more accessible digital experience for municipal employees.
- Generative AI will support knowledge access and service operations, illustrating how public-sector AI adoption is moving into internal workflows.
- Automation can reduce repetitive IT workloads, allowing support teams to focus human expertise on more complex employee technology problems.
- Data analytics could make municipal IT more proactive, identifying recurring incidents and emerging employee needs rather than responding only after problems occur.
- AI governance will be critical, particularly around knowledge accuracy, access controls, security, privacy and human oversight in public-sector environments.
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