Strengthen the manufacturing supply chain with task specific GenAI tools and Microsoft AI

Manufacturing IT leaders are working to overhaul aging, rigid supply chains, with global geopolitical events adding still more urgency to that task. Priorities include: Optimizing demand planning tools to better forecast demand changes Reducing lag time in responding to supply chain disruptions Automating tasks from manufacturing to logistics Generative artificial intelligence (GenAI) capabilities can help…

Use cloud computing to accelerate GenAI adoption in healthcare with Microsoft AI

Certain healthcare organizations have been slow to embrace cloud computing despite its proven benefits, largely due to security concerns. But cloud caution will also likely hinder the healthcare sector’s adoption of Generative AI (GenAI) applications. Healthcare IT leaders can make a business case to optimize the organization’s cloud and GenAI investments to enable GenAI applications.…

Pharmaceutical IT leaders: Speed drug discovery and development with data lakes

In pharmaceutical and life sciences companies, data is vast, diverse, and growing. It includes such varied forms as clinical trial data, genomic sequences, assay biology, electronic health record (EHR) data, regulatory and compliance information, and much more. Without a unified data foundation, this vital data remains siloed and fragmented, hindering collaboration, innovation, and insights in…

Humanizing payor-provider interactions one task at a time

Healthcare providers have a clear and urgent requirement: they want payers to process authorizations, claims, and payments quickly and accurately. They have been long burdened by cumbersome, outdated data submission and bureaucratic processes. But healthcare payer IT leaders are saddled with big, expensive, and lengthy change processes – both on provider portals and on the…

Three key areas where healthcare IT leaders can deploy AI to improve patient outcomes

Healthcare providers face formidable challenges in applying AI capabilities to patient care. Efforts to do so are testing the current regulatory framework. For example, the U.S. Food and Drug Administration (FDA) is actively involved with stakeholders to create relevant policies that facilitate AI innovation while protecting patient safety. Healthcare IT leaders can begin using AI…