AI Articles and Analysis about Data management

We've spoken to many leaders in healthcare and pharma over the last half a decade, and when it comes to AI, the most pressing challenge that healthcare and pharma leaders report is that they're unsure of how to streamline and structure their data in a way that lets them build machine learning models. Healthcare companies are stuck in the data consolidation phase of their potential AI initiatives while vendor after vendor is trying to sell them on a new application that the company might not even be close to ready for.

Episode Summary: There's a lot of venture money pouring into artificial intelligence in healthcare. From pharma to hospitals and beyond, the potential applications in healthcare are promising. 

Even during a time when the buzz around AI and digital data storage is prominent, there are still some companies with large amounts of backlogged data that are taking up space in their databases, but not providing enough value. Large stores of enterprise and customer data can be valuable to insurance companies for optimizing their business operations and gaining analytical insights on how their business decisions affect company growth.

IT services firms are doing their best to keep up with the changing landscape as AI begins to dominate the tech conversation. Many IT services firms have recently started branding themselves as AI companies without having the requisite talent to back up their claims. In reality, many of the older IT services companies are struggling to hire PhD graduates in machine learning who would rather use their skillset at global AI firms like Google and Amazon.

This week we interview a leader at Facebook. Jason Sundram is the lead of World.ai at Facebook, which is one of their efforts to work with public data around roads and population and other projects of that kind. But Sundram is also highly involved in the Boston office here, where Facebook will soon have around 650 employees. Many of them focus on data science and artificial intelligence.

Militaries around the world are starting to make increasing investments in artificial intelligence and machine learning capabilities. The top military defense contractors in the US, Europe, and Israel are all working on AI software to sell into the defense sector. That said, the military adoption of AI is as of right now slow in comparison to that of contractors.

The insurance sector is highly competitive, and there seems to be a consensus among experts that customers in the industry favor insurance products that are tailored to their unique needs. Large insurance firms could deliver personalized customer experiences and improve their operational efficiency by adopting AI.

The Patient Protection and Affordable Care Act (ACA) has significantly changed the landscape for how healthcare providers can be reimbursed by insurers. They are now reimbursed based on the guidelines set by Value-based Purchasing (VBP) models. This type of payment model reimburses the healthcare provider based on the quality of their work with the insured patient.