Globant moves enterprise technology services to an outcome-based AI model
Companies are moving from experimenting with artificial intelligence to integrating it directly into their operations, but the cost and complexity of deploying these services remain barriers to adoption.
Globant is proposing a different model with AI services that can be contracted and deployed on demand, with pricing tied to outcomes or consumption rather than the number of professionals involved.
Artificial intelligence is beginning to change not only how companies develop technology, but also how they procure these services. The traditional model, based on projects, work hours and professional teams, is giving way to an alternative in which the outcome delivered becomes the primary basis for contracting.
Against this backdrop, Globant introduced Glob.AI, an AI-powered technology services platform that allows companies to access enterprise-grade services through a self-service model and pay for what they produce, either by outcome or consumption.
AI Pods bring artificial intelligence to technology services.
The offering is built around AI Pods, service units powered by groups of artificial intelligence agents and supervised by human experts. Each Pod specializes in specific tasks and industries, combining the speed of agents with defined and controlled processes.
”For more than 20 years, Globant has remained at the forefront of every major technological evolution, and AI is no exception. Glob.AI is our next major step,” said Martín Migoya, CEO and co-founder of Globant.
The executive said the model is designed to reduce unnecessary token consumption and manual oversight through parallel agents, workflows and deterministic processes.
The model changes the rules of technology contracting.
Glob.AI incorporates a governance layer that combines AI agents with Globant’s experience in enterprise services. The agents perform the tasks, while experts oversee the results and guide the process.
The model relies on defined and repeatable processes, along with a pricing structure in which customers pay for outcomes validated by experts or for actual consumption. Customers are not charged for hours worked, the number of professionals assigned, AI errors, rework or wasted cycles.
Globant also says Glob.AI can achieve at least 30% higher productivity than the traditional approach of pairing an engineer with AI tools.
The platform also incorporates governance mechanisms that allow customers to define which models they use and where those models run, while their data is not used to train external models.
”AI is not just making the same projects faster: it is making thousands of projects that were previously unviable possible,” said Guibert Englebienne, co-founder of Globant.
According to the executive, the company aims to make technology services available instantly and transparently, with customers paying only for the results.
Glob.AI introduces continuous, on-demand technology services.
Companies that join the Glob.AI waitlist will receive early access to a catalog of agent-based workflows capable of building and deploying solutions for enterprise systems and different industries.
The offering also includes partnerships with technology companies such as Anthropic, AWS, Vercel, OpenAI, Adobe, Microsoft Azure, Google Cloud Platform, SAP and Salesforce.
The shift also changes how projects are executed. While traditional processes can require months of analysis, requests for proposals and procurement cycles before work begins, Glob.AI is designed to allow users to log in and start building enterprise software directly from the platform.
The service is designed as a continuous process in which improvements and new versions are incorporated directly into the platform, while customers can track progress in real time.
Early results show applications across industries.
Globant began offering its AI Pods in mid-2025 and says they are already being used by Fortune 500 companies in sectors including media, entertainment, professional services and finance.
Reported results include a 20% increase in throughput generation efficiency for FIFA, the deployment of AI across key LALIGA functions in three months, and a reduction of up to 40% in YPF’s hiring timelines.
The company also reports that PharmaMar obtained oncology research insights 15 times faster, while a leading commercial bank completed a COBOL migration in two months, compared with the 14 months projected under a traditional approach.
Glob.AI thus seeks to move enterprise AI adoption beyond individual technology projects toward an on-demand services model in which agents perform much of the work while experts maintain oversight of the results.
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