Leadership Perspectives

As Amazon Web Services (AWS) Head of AI and Modern Data Strategy BD, Ben Schreiner is a trusted advisor helping customers unlock transformative growth. He and his team are focused on helping customers prepare to be competitive in the AI era. With 30+ years of global experience spanning enterprise tech, startups, and financial services, Ben provides a unique perspective on driving innovation through emerging technologies like AI.

Amazon’s AI investment strategy is long-term, intentional, and customer driven. At AWS, we’re making more capital investments than anyone else to meet the accelerating global demand for AI infrastructure. We’re investing across the entire AI stack, offering customers purpose-built chips like Trainium, model choice via Amazon Bedrock and strategic partnerships, and practical and production-ready tools like AgentCore and Kiro that move ideas to production faster.

What sets AWS apart is our belief in choice at scale. AWS is able to support customers with the entire lifecycle of AI adoption, regardless of if they want to build, buy, or both, our model-agnostic platform and expansive marketplace make it easy. Our global infrastructure footprint gives customers the flexibility to deploy AI where it makes the most sense for their business and data needs, with enterprise-grade security and governance built in from day one.

While some companies are scrambling to adopt AI, AWS bet early on AI and invested early in the infrastructure, tools, and partnerships our customers need to innovate securely and at scale.

AWS is the one-stop shop for agentic AI, whatever the business needs are.

We provide a complete platform for agentic AI, bringing together infrastructure, tools, and partner solutions to accelerate the deployment of autonomous agents that deliver real business value at scale.

We recently launched Amazon Bedrock AgentCore, a set of capabilities for deploying AI agents at enterprise scale. AgentCore is designed to address the real challenges businesses face when deploying agents in production. It includes the industry’s longest serverless agent runtime (up to eight hours), sophisticated memory systems that enable agents to maintain context over complex, multi-step processes, and robust identity and security features that ensure agents operate and integrate safely within your existing authentication frameworks.

Complementing this is a new tool called Kiro, which I’m particularly excited about. Kiro allows business leaders to literally use nature language to describe the solution they want to see, and our AI transforms that into a visual they can interact with and refine before generating functional application requirements for the development teams. This bridges the persistent gap between business vision and technical execution that has plagued industries for decades. The development team can then use these AI-generated requirements to rapidly build secure, scalable, enterprise-ready applications with all necessary documentation.

AWS has also recently launched a new AI agent category in AWS Marketplace, featuring hundreds of listings from partners across industries. These solutions span autonomous agents, supporting tools, governance guardrails, knowledge bases, and implementation services. Customers benefit from AI-powered semantic search to discover solutions by use case. They can deploy them using flexible procurement options such as pay-as-you-go, subscriptions, and custom enterprise pricing.

Across industries, customers are moving beyond experimentation and using AWS to drive real results. Whether it’s accelerating research in life sciences or streamlining retail execution in consumer goods, AI is helping organizations innovate and move faster with measurable impact.

In life sciences, the biggest opportunities for AI agents are compressing research and development (R&D) timelines, automating lab operations, and enabling more personalized care. For example, SAPIO Sciences is automating lab workflows with AI agents that design test plans and document results, freeing scientists to focus on experimentation. Also, Syngenta is using multi-agent systems built on Amazon Bedrock to deliver personalized seed recommendations that have increased crop yields by up to 5%.

For retail optimization specifically, our own Amazon shopping assistant serves tens of millions of customers, using AI for everything from size recommendations based on how different brands fit to our “Buy for Me” feature, where our shopping agent can complete purchases on other merchants’ websites. We’ve seen over 50,000 advertisers use our AI tools for campaign optimization in just Q1 alone.

StayinFront is leveraging AI in ways that optimize workflows and drive sales for its clients. Their latest entry, On-Device AI, shows just how seamless AI-driven solutions can be, providing their clients with instant results at the shelf. When those in the consumer goods industry can empower their teams to take immediate action, that supercharges a simple store visit and enhances productivity and efficiency overall. With AI-powered solutions like On-Device AI, these teams can do more with less effort.  

StayinFront is also leveraging Amazon Q Developer, an AI-powered assistant designed to assist developers and IT professionals throughout the software development lifecycle. Adoption of Q has proven to provide gains in efficiency and quality outcomes for software development. This directly benefits StayinFront’s customers by significantly reducing the time required to deliver customizations and feature requests. Additionally, it enhances the initial quality of their outputs, which in turn shortens QA timelines and boosts their effectiveness. 

Furthermore, Amazon Q Developer allows StayinFront to conduct faster and more robust security scans, ensuring that their solutions are secure from the get-go.