While 61% of Spanish companies have already welcomed AI into their workflows—according to insights shared at the event—a striking bottleneck remains: only 17% have backed it with the formal strategy and data governance required for advanced adoption.
At AWS Summit Madrid 2026, the atmosphere was charged with a single, urgent realization: We have officially transitioned from a wave of curiosity to a need for execution. Closing this gap requires moving past the “hype” and solving the hard architectural truths beneath the surface.
As an AWS Premier Tier Partner and holder of the AWS AI Services Competency, Globant joined the summit to share a clear point of view: the companies that will lead the next wave of transformation are not the ones testing AI in isolation, but the ones building the right foundations to scale it across the business.
From experimentation to measurable impact
According to AWS keynote data, closing the AI adoption gap could unlock an additional €191 billion in economic value across Europe. The key takeaway is simple: AI value is no longer defined by the sandbox. It is defined by execution, governance, and the ability to turn technology into hard business outcomes, driving AI business value transformation across industries.
What stood out at the summit
- AI is moving into production
Generative AI has evolved past the trial stage. The focus is now on scalable, secure, enterprise-grade implementations. We saw this live with case studies like OutSystems, which deployed the Amazon Bedrock connector to launch 19,000 autonomous AI agents into production in just five months, slashing development costs by 30%. These examples highlight the growing impact of AWS generative AI solutions in the enterprise. - Reinventing the Developer Experience
A massive spotlight was put on engineering velocity. AWS introduced Kiro, a breakthrough AI developer assistant that converts natural-language prompts into deep technical specifications and automatically packages them into ready-to-ship code. Alongside Amazon Q—which enterprise adopters like 3M are using to cut sales meeting preparation time from 5 hours down to minutes—the tools shown proved that developer productivity is skyrocketing, demonstrating how AI can improve developer productivity at scale.. - Cloud and Data Remain the Foundation (“No Data, No AI”)
The summit reinforced a core architectural truth: without modern data pipelines, AI cannot deliver at scale. To alleviate data fragmentation and eliminate storage bottlenecks, AWS rolled out Amazon S3 Files, allowing engineering teams to mount high-performance S3 buckets directly as local file systems within EC2 or Lambda instances. Legacy modernization was also front and center, highlighted by Mercedes-Benz, which utilized AI to autonomously migrate ancient COBOL code into modern Java, cleanly deprecating 3,000 legacy applications. - Sovereignty and Local Infrastructure Matter
AWS underscored its massive, long-term commitment to the Spanish market, highlighting its €33.7 billion investment pipeline in the Aragon data center region through 2035—a project slated to support 30,000 jobs annually and inject €32 billion into Spain’s GDP. Crucially for regulated industries, the AWS European Sovereign Cloud is now officially live and physically isolated, operated exclusively by EU residents to make sovereign AI a turn-key operational reality. - Multi-Model Flexibility and Agentic AI
Enterprises want choice and control. The blockbuster technical announcement of the General Availability (GA) of OpenAI GPT models natively inside Amazon Bedrock proved that the market demands a multi-model approach. Coupled with Amazon Bedrock Agent Core and the new AWS Lambda Durable Functions (which allow autonomous agents to pause complex workflows for hours or days without racking up idle computing bills), agentic AI has officially moved from concept to operational reality.
The mindset shift companies need
The biggest challenge is no longer access to technology; it is the organizational mindset required to use it well. In fact, 60% of businesses still cite a lack of digital skills as their main bottleneck, highlighting the challenges of AI adoption that many organizations continue to face.
Advanced AI adoption requires a structured framework:
- Executive sponsorship to break silos
- Clear governance and compliance protocols
- A focused use-case strategy tied to business value
- Modern data foundations (moving away from legacy systems)
- Continuous investment in skills and employee reskilling
The companies that succeed will be the ones that treat AI as a core business capability, not just an isolated technology layer.
How Globant helps turn AI into business value
At Globant, we help organizations move from AI ambition to execution. Our approach combines cloud, data, and AI expertise with deep industry knowledge to design solutions that are ready for real-world impact.
We deliver this through:
- AI Pods: AI-native service units where agents execute, experts supervise, and enterprises receive governed outputs at scale.
- Industry-specific AI solutions: Custom frameworks designed to tackle unique sector challenges, from financial services to retail.
- End-to-end implementation: Comprehensive support guiding your architecture from initial strategy and data ingestion up to final production.
- Strong AWS foundation: Leveraging our Premier Tier partnership to deploy multi-model architectures securely, efficiently, and compliantly.
Whether the goal is to modernize operations, improve customer experience, or unlock new business models, we work with clients to make AI practical, scalable, and measurable.
Reinvention in action
Explore how Globant, powered by AWS, is driving tangible business outcomes for enterprises worldwide. Discover our real-world success stories below.
How Interbanking-Frisvy Leveraged AWS and Generative AI for Enhanced Document Processing
Santander’s Cloud Leap with Globant & AWS
Globant accelerates USGBC’s adoption of sustainability performance management
Looking ahead
AWS Summit Madrid 2026 made clear that the future of AI belongs to organizations that can combine the right infrastructure, data, and execution model.
At Globant, we are ready to help clients navigate that shift and turn AI into a real competitive advantage.
