A global McKinsey survey, The State of AI 2025, shows that nearly 60% of companies are still in experimentation or proof-of-concept stages, while only 7% have successfully deployed AI tools in an integrated way across their organizations.

AWS re:Invent 2025 reflected this reality and marked a turning point in how organizations will adopt AI, autonomous agents, data, and cloud capabilities throughout 2026. This year’s edition focused heavily on tools that help companies move their AI strategy from conceptual to fully productive, with announcements that directly impact costs, development speed, and enterprise-grade AI capabilities.

Below we share the key highlights and why they matter for your strategy.

Event Highlights

1) Amazon Nova 2 + Nova Forge

AWS introduced the next generation of multimodal models and a platform to build custom models over your own data, with less effort and greater control. Impact: accelerates the development of industry-specific AI solutions and shortens adoption cycles.

2) The rise of Agentic AI (enterprise agents)

AWS announced new capabilities in Bedrock AgentCore to build agents that can execute complex end-to-end tasks and make decisions in corporate contexts.

Impact: enables deep automation of processes (operations, development, support, security), freeing up resources and speeding up response times across enterprise environments.

3) Next-generation infrastructure

The new Graviton5 processors for EC2 deliver up to 25% more performance than the previous generation while improving energy efficiency, cost, and sustainability.

For AI-specific workloads, AWS launched the new Trainium3 chips, offering 4× performance and 40% better energy efficiency compared to the previous generation.

Additionally, AWS announced ongoing development of Trainium4, expected to deliver 3× to 6× performance improvements.

Impact: better cost-to-performance ratio—especially important for organizations running models, data-intensive pipelines, or large-scale databases. Enables modernization and migration paths with tangible savings.

4) Database Savings Plans

AWS introduced new savings models for a variety of data services, including Aurora, RDS, DynamoDB, ElastiCache, and DMS, among others. These Savings Plans can deliver substantial discounts—up to 35%—with one-year usage commitments.

Impact: immediate opportunity to optimize infrastructure costs in 2026, especially for workloads with stable and predictable database consumption.

5) Evolution of the enterprise AI stack

AWS expanded its governance, security, monitoring, and developer-experience capabilities for building models using Bedrock and SageMaker.

Impact: makes it easier to move from PoCs to real, production-ready solutions with proper control and compliance—critical for large-scale AI adoption in medium and large organizations.

Why this matters for your organization

· Concrete savings in 2026 thanks to Database Savings Plans and more efficient next-generation chips.

· Greater speed: optimized agents and models reduce operational timelines.

· Real competitiveness: organizations implementing applied AI will outperform those that remain in experimentation.

· Security and control: the new stack strengthens governance, compliance, and responsible AI production.

Suggested use cases by industry

Retail

·         Autonomous agents for replenishment, dynamic pricing, and omnichannel support

·         Custom models for demand forecasting

Fintech / Financial Services

·         Agents for fraud monitoring, reconciliations, and risk management

·         Nova Forge–powered models for credit analysis

Industry / Manufacturing

·         Predictive maintenance automation

·         Operational process optimization with specialized agents

If any of these announcements seem especially relevant or you’d like to explore how they apply to your specific context, feel free to reach out.