La Voz
La Voz’s transformation toward an AI First model
We supported La Voz from defining its AI First strategy to transforming processes and implementing new technology capabilities, combining Speed AI, agile development and applied artificial intelligence.
- Client
- La Voz
- Industry
- Media
- Country
- Argentina
- What we did
- AI First strategy, Fractional CTO and applied AI
- Year
- 2026
- AI First
- A shared strategy to guide the transformation
- Agility
- Reduced internal SLA
- Agents
- New AI capabilities implemented
/ Challenge
Turning a vision for transformation into concrete operational changes
La Voz wanted to define how to incorporate artificial intelligence into the company’s evolution and turn that vision into initiatives that would deliver value across its departments.
The challenge covered both strategy and execution: identifying where to intervene, understanding business processes and developing the technological capacity needed to implement improvements continuously.
Moving forward meant connecting the board’s priorities with the teams’ day-to-day work and establishing a gradual path toward an AI First model.
/ Approach
Speed AI as a starting point to guide the transformation
We began with Speed AI, working with La Voz’s board to redefine its technology strategy around an AI First model. That first stage established a shared direction for the work that followed.
Then, through Scan AI and interdisciplinary teams, we mapped the company’s main processes and identified opportunities for improvement. That understanding helped us design new experiences for internal processes and services and guide the first changes.
Through Fractional CTO support, we connected that agenda with technology execution. We introduced agile practices and new development architectures to accelerate delivery and prepare for the implementation of AI solutions across different departments.
/ Solution
A transformation connecting processes, engineering and artificial intelligence
The work progressed gradually, connecting the strategic direction with changes to operations.
Redesigning internal processes and services
Based on the interdisciplinary assessment, we worked on the experience of selected processes and began implementing improvements to internal services. Bringing together business and technology specialists helped connect each department’s needs with the solutions to be developed.
Greater capacity for technology execution
We introduced agile development practices, delivery tracking and AI assistance tools for the technology team. This work was complemented by improvements to architecture, infrastructure and data management to support the evolution of services.
Initial applied AI capabilities
On that foundation, we developed assistance tools and agent-based models. Deliverables include a multi-agent tool environment and an editorial review agent, supported by an AI usage policy and team training.
Initiatives continue to advance according to their maturity, from tests and pilots to implemented tools.
/ Results
AI First: A shared strategy to guide the transformation
The process connected the AI First strategy with concrete changes in how technology solutions are developed and delivered. The team reported faster development, a higher volume of resolved tickets and a reduction in its internal SLA.
La Voz also has new AI tools and a set of planned initiatives to continue extending these capabilities across different departments.
Agility: Reduced internal SLA
Agile practices, new architectures and AI-assisted development increased delivery and reduced the internal resolution SLA.
Agents: New AI capabilities implemented
The multi-agent environment, editorial review agent and AI usage policy are concrete deliverables that support the adoption of these tools.
Greater delivery capacity
New engineering practices and AI-assisted development increased the speed of work and the number of resolved tickets.
The next stage
The transformation continues with the development of a platform designed to provide access to different AI models and manage their consumption efficiently.
The aim is to expand the capabilities available to teams and develop the agent strategy further, with control over resource usage and operating costs.
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