In the interview with Martin Migoya, Chairman and CEO of Globant, the discussion centers on how AI is transforming the business landscape and delivering tangible ROI for enterprises. Migoya emphasizes that AI represents a massive technological revolution that is here to stay, enhancing rather than replacing human capabilities. He categorizes AI applications in business into two main types: straightforward use cases like customer service automation, where AI handles routine tasks and humans focus on complex issues, and more complex scenarios where AI runs processes autonomously with human supervision, requiring companies to rethink and redesign their workflows.
Globant approaches AI integration by leveraging a platform called Globant Enterprise AI, which connects to over 140 different AI models and integrates seamlessly with corporate information systems such as SAP and Salesforce. This platform enables the creation of agentic workflows—AI agents designed to solve specific business problems. Migoya highlights the importance of flexibility in choosing the best AI model for each task rather than relying on a single solution. Additionally, once an AI agent is developed for a particular problem, it can be adapted and deployed across multiple companies facing similar challenges, thereby scaling the solution efficiently.
Several practical use cases illustrate how Globant applies AI to real-world business problems. For example, in e-commerce, AI agents manage customer service inquiries by verifying product issues through image analysis and recommending appropriate resolutions, with humans stepping in only when necessary. In procurement for energy companies, AI automates the process of sourcing parts by checking inventory, vendor contracts, and managing requests for proposals. In software development, Globant’s AI-powered coding agent, Koda, accelerates the creation and migration of software by reusing existing code and adhering to corporate standards, significantly reducing time and cost.
Migoya stresses that AI systems are probabilistic and require human oversight to ensure accuracy and prevent errors such as hallucinations. The key to reliable AI performance lies in providing the right context and prompts, which is often the most challenging aspect of implementation. He envisions a future workflow where AI agents perform the bulk of tasks, and humans act as supervisors or auditors, ensuring quality and alignment with business needs. This shift represents a new model of professional services, where AI-generated outputs are monitored and refined by human experts.
Finally, Migoya discusses how Globant is evolving its pricing model to reflect AI’s consumption-based nature, moving from traditional hourly or fixed-price models to subscriptions based on supervised token usage. He acknowledges that while AI adoption is progressing rapidly in some areas, many companies still face significant challenges navigating the complex AI ecosystem. Globant aims to simplify this journey by providing a clear playbook and enterprise-grade platform to accelerate AI integration, helping businesses realize the transformative potential of AI while managing risks and complexities effectively.
