3 enterprise AI success stories

How Beacon Street Services, Company Nurse, and Devon Energy are using artificial intelligence and machine learning to improve sales and marketing, identify and protect sensitive information, and automate oil drilling operations.

3 enterprise AI success stories
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Artificial intelligence (AI) and machine learning (ML) might be high in the hype cycle at the moment. But that doesn’t mean organizations are not realizing tangible gains from deploying products that leverage the technologies.

Here are three examples of how AI and ML are improving internal business processes and paying off for enterprises.

Boosts for sales and marketing

Beacon Street Services needed to have a “single source of truth” for all its company’s data, to ensure consistency and accuracy across its applications. The company is the services arm of Stansberry Holdings, which produces financial publications exclusively through purchased subscriptions.

Having collected and stored massive volumes of data using Snowflake, the cloud-based data warehouse service, Beacon Street Services wanted to use that data to help its sales and marketing teams improve on previous tactics and processes of selling subscriptions.

“Our marketing and sales teams saw an opportunity to improve on sales processes by applying a data science approach,” says David Kline, vice president of engineering at Beacon Street Services. “With this approach, we hoped to better identify buying criteria to help the marketing team run more effective campaigns.”

Taking the historical user data the company had in its Snowflake data warehouse and loading it into an enterprise AI platform it deployed from DataRobot beginning in 2019, it was able to build a series of models quickly and automatically, using dozens of the latest data science algorithms. With these models, it identified buying criteria to help the marketing team run more targeted and effective campaigns.

The company now continues to feed large amounts of data into the AI platform from the data warehouse, Kline says.

As a result of the new process, Beacon Street Services saw a 10% increase in sales and is on track to realize $15 million in additional annual sales directly attributable to the AI platform. Since implementing the platform, the company has seen 30 to 35 times return on investment in revenue gains and cost decreases, Kline says.

“For example, for one individual project we had to manually go through previous transactions to determine the risk of chargebacks following automatic subscription renewal and create a risk evaluation model, Kline says. “Not only was this process automated using AI, but we now have the benefit of proactively handling upcoming transactions.”

In addition to seeing improved accuracy and optimized marketing campaigns using AI, the DataRobot platform also provided significant time savings. Previously, it would take as long as six weeks to develop a model, with no guarantees that the optimal algorithm was selected. With the enterprise AI platform, that time to develop and deploy models that used more appropriate algorithms was reduced to just one week.

A side benefit is that the company’s IT team is spending less time analyzing data and more time working on potentially valuable projects for the business.

Classifying documents for better security

Company Nurse, which provides Covid-19 health screenings, workplace injury reporting, and nurse triage services for employers, is leveraging AI on several fronts.

One project involves enhancing the process of classifying documents. Company Nurse in 2020 deployed a platform from Concentric called Semantic Intelligence, to protect private workers’ compensation data on behalf of its customers and their end users.

The system autonomously discovers Company Nurse’s critical unstructured data, providing an opportunity to mitigate data sprawl and reduce threat surfaces.

As part of its service to customers, Company Nurse completes incident reports for workers’ compensation, providing appropriate care advice to injured workers and managing providers for referral. The information in the reports and forms includes significant amounts of unstructured data, says Henry Svendblad, CTO at the company.

By using the AI-powered system from Concentric, Company Nurse can protect private information in the documents without the need for staff to manually go through the data. The platform automates unstructured data security using deep learning to categorize data, uncover business criticality, and reduce risk.

Semantec Intelligence uses the baseline security practices seen for each category of data to calculate a “risk distance” from the baseline for each individual document. The risk distance uncovers events such as inappropriate sharing of information, risky storage locations, and incorrect classifications.

Copyright © 2021 IDG Communications, Inc.

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