Enterprise applications of AI
A large percentage of enterprises have already implemented some type of artificial intelligence software to improve their business, be it chatbots for customer service or machine learning for predictive analytics. On this page, you'll find information about those enterprise applications of AI and many more emerging uses of AI.
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Enterprise applications of AI News
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October 11, 2019
11
Oct'19
A chemical company simplifies workflows using RPA
Software from Automation Anywhere, an RPA vendor, was easy for Eastman Chemical Company employees to use at a desktop level to automatically handle daily tasks.
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October 08, 2019
08
Oct'19
Adoption of AI in healthcare grows quickly, survey finds
The adoption of AI in healthcare is continuing to grow as the technology becomes more refined. Healthcare organizations are expecting to see returns in their AI investments.
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October 03, 2019
03
Oct'19
Cornell Tech puts computer vision into practice on clothing
A team at Cornell Tech built a clothing recognition dataset, and recently turned to Samasource, which provides AI training data services, to annotate tens of thousands of images.
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October 02, 2019
02
Oct'19
Pride and nerves delay AI adoption in the enterprise
A new study shows that AI adoption in the enterprise is slower than it ought to be. Experts point to a lack of education, the need for explainable AI, and even executive pride.
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Neural network applications in business run wide, fast and deep
Neural network uses are starting to emerge in the enterprise. This handbook examines the growing number of businesses reporting gains from implementing this technology. Continue Reading
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AI converts consumer analytics into potent sales weapons
Surveys, social media monitoring and loyalty cards are just some of the ways to collect customer data. Consumer analytics can help businesses analyze that data. Continue Reading
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Digital finance technologies at epicenter of CFO transformations
Technologies like AI, analytics, bots, big data and blockchain could transform the finance function into a valued strategic partner for companywide digital transformation. Continue Reading
Evaluate Enterprise applications of AI Vendors & Products
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3 intelligent process automation use cases and how they work
Enterprises are pursuing intelligent process automation to take their digital transformation and RPA applications to the next level. Here's a look at three use cases. Continue Reading
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Deep learning and neural networks gain commercial footing
Deep learning and neural networks are picking up steam in applications like self-driving cars, radiology image processing, supply chain monitoring and cybersecurity threat detection. Continue Reading
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Human-AI collaboration produces top results
Humans and machines have different -- and often complementary -- strengths and weaknesses. That's why we're not seeing automation leading to mass job losses, at least for now. Continue Reading
Manage Enterprise applications of AI
Learn to apply best practices and optimize your operations.
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AI in content management revolutionizes unstructured data
Managing content and data can take business process from unrefined to streamlined. Enterprises can slowly apply technologies to climb the ladder of cognitive content intelligence. Continue Reading
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RPA security best practices include access control, system integration
Robotic process automation can revolutionize enterprise workflows, but if RPA security risks aren't controlled, bots could end up doing more harm than good. Continue Reading
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Using enterprise intelligent automation for cognitive tasks
RPA is no longer comprised of simple chatbots or repetitive programmed tasks. Enterprises are looking at RPA to move up the ladder of cognitive automation. Continue Reading
Problem Solve Enterprise applications of AI Issues
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Collaborative robots' safety stalls enterprise implementation
Cobots are promising big gains, especially in enterprises utilizing manual labor. However, due to a number of safety concerns, human workers are still at risk. Continue Reading
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How to solve deep learning challenges through interoperability
The challenges of training and overseeing advanced neural networks is leading to an implementation bottleneck in deep learning technology. Continue Reading
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The future scope of chatbots begins with addressing flaws
Chatbots are hot software in the enterprise, but to maintain longevity and relevance, developers need to take a look at the barriers to entry, interface options and NLP issues. Continue Reading