How Globant Uses Make to Empower 30,000 Employees to Build AI Automations
Globant democratized automation across 30,000+ employees using Make, enabling non-technical teams to independently build solutions worth hundreds of thousands of euros in engineering time while freeing technical staff for complex work.
Impact
30,000+
Employees empowered to build automations
hundreds of thousands of euros
Engineering time value delivered by non-technical teams
Challenge
Technical teams had become organizational bottlenecks, with non-technical employees unable to implement solutions without engineering support, slowing delivery across the business.
Solution
Democratized Make automation across 30,000+ employees, enabling non-technical teams in marketing, operations, and more to independently build and deploy solutions.
Tools & Technologies
What Leaders Say
“Technical resources cannot be the bottleneck of an organization. It cannot be the bottleneck of problem-solving.”
“AI and automation are like brothers. You cannot think about automation without AI today, and you cannot think about AI without automation.”
Sign up to read complete case studies, access detailed metrics, and unlock all use cases.
Full Story
Globant, a global digital transformation company with 30,000+ employees, faced a structural bottleneck: technical staff had become the gatekeepers of problem-solving. When marketers, SEO specialists, and product leads hit operational challenges, they had to queue up requests for engineers — slowing delivery and frustrating both sides.
Daniel Gonzalez, Head of Innovation and AI at Globant GUT, set out to break this dynamic. His solution was to democratize access to Make's automation platform across the entire organization, giving non-technical employees the tools to build their own solutions without writing code.
The rollout spanned teams across marketing, content, operations, and international markets. Employees who had never written code began shipping automations that directly impacted client outcomes. Solutions that previously required engineering sprints were delivered in days or hours.
The business impact was significant: non-technical teams delivered automation solutions equivalent to hundreds of thousands of euros in engineering time, while technical staff shifted from routine requests to high-complexity work. Gonzalez views AI and automation as inseparable — neither works as well without the other.
Amazon Bedrock