Frontline workers are the foundation of every industry—from retail and healthcare to hospitality and field services. Yet for years, they’ve been asked to increase productivity and deliver more value, faster, often with tools that weren’t designed for the specific realities of frontline work. Today, that dynamic is shifting. When AI is applied in practical, governed
Sustainability is about survival. We want our businesses and communities—our species and planet—to carry on without running out of essential resources. Sustainability drives such important outcomes for business and society that it has become a compelling organizational priority. Microsoft has ambitious plans around sustainability.
Financial services institutions are increasingly using artificial intelligence (AI) to automate and augment their decisions. But when it comes to which AI algorithms to use, fairness and transparency must factor into the equation. Black box AI: a cautionary tale Some of the algorithms under heavy consideration today are called “black box” algorithms.
Much like Microsoft’s mission to empower every person and every organization on the planet to achieve more, the mission of the American Hospital Association (AHA) is succinct and straightforward: to advance the health of individuals and communities.
The financial services industry worldwide recognizes sustainability as both risk and opportunity. With a real global need, growing regulatory pressures, a clear moral mission, and unstaunched innovation, sustainability is proven to be a massive growth play. The green bonds market is on a roar and banks are raising their sustainable finance objectives, while investors hunger for green assets over brown.
In the wake of COVID-19, finance organizations across all industries have been working to move from crisis management mode into building resiliency for the future. Mat McBride, finance leader for Microsoft’s Cloud and Gross Margin, recently sat down with us for a virtual conversation.
Today, everyone is digging out from the initial impact of the COVID-19 pandemic. In doing so, we’re collectively defining a new order for how health and medical services will look and operate going forward. This effort is not without its challenges. In the United States, hospital operating margins are down 96 percent since the start of the year.
2020 is a time of challenge and opportunity for small businesses who want to prioritize their digital transformation journeys. Fortunately, tools that weren’t seen as feasible for small businesses due to costs and resources are now becoming the norm for SMBs.
Machine learning holds the promise of saving time and money while increasing accuracy and efficiency across a variety of business use cases – but there can be pitfalls on the road to implementation.
The Microsoft team is increasingly focused on tailoring solutions for the healthcare industry, as evidenced by our recent announcement of the Microsoft Cloud for Healthcare. This dedication includes creating solutions that make it easier for healthcare payors to run their business efficiently and deliver high-quality experiences to members.
The traditional methods banks use to address Anti-Money Laundering (AML) have been failing for some time. Financial crimes and fraud, like Ponzi schemes, are slipping through the cracks because criminals, with enough time and patience, can seemingly find their way around any security measure.
Declining oil prices are creating challenges for their economy which derives 90% of its revenue from oil and natural resource production. The State has turned to Microsoft with a need to adapt education and workforce skilling, reduce costs, and streamline operations.
Ten or twenty years ago, the future of retail was online shopping. Today, it is building seamless connections between physical locations and online stores so that customers can easily shop, order goods, or pick–up items from a store or curbside service. Quarantines and social distancing only highlight the importance of building retail operations that start and end with the customer, online and off.
