AI Articles and Analysis about Data management

We previously covered the top machine learning applications in finance, and in this report, we dive deeper and focus on finance companies using and offering AI-based solutions in the United Kingdom. The UK government released a report showing that 6.5% of the UK's total economic output in 2017 was from the financial services sector. As of now, numerous companies claim to assist financial industry professionals in aspects of their roles from portfolio management to trades.

The healthcare domain seems ripe for disruption by way of artificial intelligence in the form of predictive analytics. Accenture estimates the AI in healthcare market will reach $6.6 billion by 2021.

Today, two highly discussed disruptive technologies are artificial intelligence and blockchain. In this piece, we aim to highlight projects where AI and blockchain might be used together to support the B2B environment.

Episode Summary: Companies with wells of data at their disposal may find themselves asking how they can use them in meaningful ways. Generally speaking, a clean set of data is the foundation for AI applications, but business owners may not know how exactly to organize their data in a way that allows them to best leverage AI. How exactly does a business transition from having data with the potential for usefulness to having data that’s going to allow for an accurate, helpful machine learning tool—one that can actually help solve business problems?

In this episode of AI in Industry, we speak with Brendan Kohler, the CTO of Co-founder of Boston-based startup Sentenai. Brendan speaks about how businesses today can effectively leverage the data being collected by their existing IoT and automation systems. Though example applications and use-cases, Brendan elaborates on what kinds businesses might use this technology today and what they can expect in the near future.

Implementing artificial intelligence into an existing business is about more than algorithms. In fact, many AI researchers believe that algorithms are the easiest part of an artificial intelligence implementation.

There is a consensus among industry experts (both from our own insurance AI secondary research, and according to a 2017 Accenture survey report) that AI is going to be a key driver in making insurance products "smarter" in the coming 2-3 years.

While customer service is making its way to Facebook Messenger and other burgeoning platforms - a massive percentage of customer support inquiries are handled the way they have been for years: Over the phone or on chat.