Insights

Redapt | AI/ML (3)

Blog

5 Business Cases for Developing an AI Strategy Today

In today’s economy, every organization has access to a steady flow of data. Thriving businesses utilize that information not just to make smarter decisions, but to help tackle challenges they are...

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Blog

Healthcare Professionals Turn to Health Bots for Help Through COVID-19

As the number of cases of the coronavirus (COVID-19) continues to rise across the globe, so do the number of phone calls to healthcare providers. Health professionals everywhere are scrambling to...

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Blog

What IT Leaders Must Do to Succeed with AI, ML, and Analytics

A few months ago, the Wharton School of the University of Pennsylvania published the article Four Ways Leaders Can Gain Value from AI and Advanced Analytics.

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Blog

How Healthcare Enterprises Are Leveraging Predictive Analytics

According to Axios, in 2018 alone, Americans spent an estimated $3.65 trillion on healthcare. For some context, that’s more than the total GDP of Brazil.

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Blog

Where Will Artificial Intelligence Take Enterprises in 5 Years?

Robots are coming for your money.

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Blog

3 Inspiring Examples of AI in the Retail Industry

As artificial intelligence (AI) solutions become more prevalent in business, it’s worth taking a look at how the technology is already helping to reshape the retail industry.

To that end, here are...

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Blog

How Growing Businesses Should Address Machine Learning Bias

As Artificial Intelligence (AI) and Machine Learning (ML) continue to make their way into more and more enterprises, it’s worth examining the trends that are shaping data analytics and how those...

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Blog

3 Tools To Help Your Enterprise With AI Adoption

From automation and data analysis to internal communications and customer service, adopting artificial intelligence (AI) into your enterprise can enhance your entire operation.

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Blog

How To Get Your Enterprise Ready For AI Adoption

As we’ve covered in a recent blog post, more and more enterprises are adopting AI in some form or fashion. In general, there are four reasons why:

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Blog

Getting Your Data Ready to Leverage the Benefits of Machine Learning

80% of time is spent preparing data, the other 20% is spent complaining about preparing the data.

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