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There’s more to successful AI adoption than picking the right technology. Business leaders should be aware of the technical requirements of the initiative they’re undertaking, and few of those requirements are as important as data.

This article was originally written as part of a PDF report sponsored by expert.ai, and was written, edited and published in alignment with our transparent Emerj sponsored content guidelines. Learn more about our thought leadership and content creation services on our Emerj Media Services page.

This is a contributed article by The Future Society, edited by Emerj and authored by Samuel Curtis, Sacha Alanoca, Nicolas Miailhe, Yolanda Lannquist, Adriana Bora. To inquire about contributed articles from outside experts, contact [email protected]

Large insurance companies have been experimenting with AI since the middle of the 2010s, piloting chatbots and collecting telematics data for future AI projects. The insurance industry more than many others relies on the collection of data to make critical business decisions.  Whether writing policies, or processing claims efficiently the way insurers employ data will determine the lifetime value of the customer.  

The financial sector was among the first to adopt artificial intelligence in business by automating fraud prevention with anomaly detection technology. Now financial institutions, including lenders, stand to benefit from automating back-end processes by digitizing documents and eliminating manual data entry.

In the past, we’ve explored the need for insurance companies to adapt to millennial buying preferences through customized policy offerings and a more personalized customer experience. AI could help to these ends, but how could insurance carriers reach this point of AI transformation?

Financial institutions have challenges around data accessibility. They want to leverage their large amounts of data so their employees, such as customer service agents, can find the information they need quickly.

Many of the key processes in industries such as banking and insurance are still done on paper. That said, many large enterprises seem to be in the process of digitizing parts of these processes in order to prepare for forays into automation and artificial intelligence.