Tag: Machine Learning

Every enterprise leader I talk to right now is wrestling with the same three problems. They’re not unique to any one industry or company size; I’ve seen them appear in financial services, government, and healthcare. And they tend to show up together. The first problem is that most organizations don’t actually know what systems, tools and applications they have. Their technical estate is broad, poorly documented, and […]

AWS recently partnered with Harvard Business Review Analytic Services to understand the current state of agentic AI in organisations.1 The results were exciting and informative: While expectations are high, the path to value at scale has yet to be discovered. Outlined below is what we found creates the gap between appreciating AI’s importance and using […]

Agentic AI brings a subtle but consequential shift in how software is architected and delivered. Instead of organizing around applications or microservices, IT departments—together with end users—now develop automated workflows. The agents that implement these workflows may communicate with other agents as part of a more complex, orchestrated group of workflows. But the basic unit […]

Navigating technological upheaval requires foresight – this insightful guide explores emerging trends like AI, cloud, IoT, and data explosion poised to upend industries, urging executives to experiment and strategize proactively to stay ahead of disruptive forces.

Automate tedious tasks, gain faster insights through conversational analytics, and innovate using synthetic data – accelerating time-to-value from data assets.

Maximize AI’s value without breaking the bank – this guide explores cost-optimization strategies across the AI lifecycle, from model selection and data management to FinOps practices.

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.

Generative AI demands a pragmatic strategy to identify value, embrace agility, scale intelligently, experiment rapidly, and prioritize responsible deployment.

When facing a game-changing technology like generative AI, experimenting is a great way to learn what it can do and how to use it. And indeed, we at AWS see plenty of companies doing precisely that, becoming more sophisticated and able to ask more informed questions about where the technology is heading and what it […]

It’s the job of senior enterprise leaders to ensure that their organizations are ready for the future. Unfortunately the future is unclear to us—all the more so in this era of rapid change, uncertainty, and complexity. As with the weather, we can foresee the near future with some certainty, but as we look further ahead, […]