AWS Cloud Enterprise Strategy Blog
Category: Artificial Intelligence
Leveraging AI and Cloud for Supply Chain Resilience
A single supply chain disruption today can erase millions in revenue and years of carefully built customer trust. While most organizations struggle with the balance between lean operations and reliability, some companies have discovered a different path. These market leaders have replaced traditional buffer strategies with a more responsive, efficient way to manage supply chains. […]
From Automation to Agency: Leading in the Era of Agentic AI
AI agents are as transformative as the advent of the internet. They will change how we organize work, manage operations, and drive value A question I often hear from AWS customer executives is how they should think about leading in this new era. I use the same mental models I use to lead my most […]
Responsible AI: From Principles to Production
As organizations deploy generative AI technologies, they face challenges including lack of expertise, fragmented governance, unclear accountability, and immature tooling—issues that can be addressed through an integrated framework of governance mechanisms, repeatable processes, and embedded safeguards.
Gamifying Digital Transformation: Drive Adoption Through Engagement
Digital transformation can offer organizations improved efficiency, enhanced customer experiences, and the ability to stay competitive, but the journey is often fraught with challenges. One key hurdle is motivating employees to embrace new technologies and ways of working. An innovative approach to overcoming these challenges is gamification, a strategy that uses game-like elements to engage […]
Innovating with AI in Regulated Industries
AI drives efficiency and better customer experience in insurance, if done transparently with strong governance to ensure fairness, ethics, and compliance.
Fuel Your Data with Generative AI
Automate tedious tasks, gain faster insights through conversational analytics, and innovate using synthetic data – accelerating time-to-value from data assets.
Overseeing AI Risk in a Rapidly Changing Landscape
With AI’s rapid evolution, boards face multi-faceted risks requiring diverse oversight, technical expertise, agile risk-mitigation, clear values guiding deployment, and robust cybersecurity – proactively managing uncertainties while capturing AI’s transformative potential.
Development Productivity in the Age of Generative AI
“Productivity is being able to do things that you were never able to do before.” —anon With generative AI grabbing almost every organisation’s attention, watching how they use the technology is interesting. Today most AWS customers are focused on achieving productivity gains (e.g., making information easier to acquire and digest for customer service staff). A […]
Responsible AI Best Practices: Promoting Responsible and Trustworthy AI Systems
The emergence of generative AI has brought about transformative possibilities and the potential to benefit how we work, live, and interact with the world. However, it is crucial to recognize the responsibility that comes with such powerful technology. When I speak to executives today, there is a lot of enthusiasm and excitement to get started […]
Is Your Data Foundation Solid, Future-Proof, and Value-Added?
Organizations need a powerful infrastructure to realize the full value of their data. The purpose of this infrastructure is to organize data, ensure its quality, manage metadata and create a central catalog where the organization’s data can be queried. This infrastructure, called the data foundation, enables organizations to have clean, organized, and easily accessible data […]