Features

Features

• Why Intuit aims chatbot design at a narrow set of tasks

  A data scientist at Intuit details the finance software vendor's approach to building chatbots -- and explains why it's limiting them to some basic customer service activities.  Continue Reading

• How to keep your implementation of AI free from algorithm bias

  When implementing AI, it's important to focus on the quality of training data and model transparency in order to avoid potentially damaging bias in models.  Continue Reading

• AI virtual assistant tools prove better for customer service than chatbots

  AI virtual assistant software is increasingly surpassing chatbots and natural language search, as enterprises see deeper value in enabling true conversation.  Continue Reading

• Humans and AI tools go hand in hand in analytics applications

  Companies are keeping data analysts and other workers in the loop with AI applications to check the results generated by automated algorithms for accuracy, relevance and missing info.  Continue Reading

• Artificial intelligence in business strategies, uses

  SearchEnterpriseAI delivers news, tips and strategic advice on applying artificial intelligence technologies in the enterprise to improve products, services and operations.  Continue Reading

• Defining enterprise AI: From ETL to modern AI infrastructure

  The promise of enterprise AI is built on old ETL technologies, and it relies on an AI infrastructure effectively integrating and processing loads of data.  Continue Reading

• IT, finance and marketing have uses for AI -- do you?

  AI in healthcare improves patient outcomes. AI in IT aids employee compliance and security. AI in logistics, AI in marketing, AI in finance -- learn how your company can use AI.  Continue Reading

• Slow pace for AI implementation is a prudent business strategy

  Enterprises eyeing AI development need to keep expectations under control and make sure projects align with business priorities to get real value from the technology.  Continue Reading

• AI functionality limited today but could be a game-changer

  Limited AI capabilities could soon give way to technology that is truly transformative for enterprises, surpassing the overhyped functionality that we see today.  Continue Reading

• Big data throws bias in machine learning data sets

  AI holds massive potential for good, but it also amplifies negative outcomes if data scientists don't recognize data biases and correct them in machine learning data sets.  Continue Reading

• Insurer's machine learning use case: Changing driver behavior

  Machine learning tools can be put to use for more than targeted marketing and product recommendations. Auto insurer HiRoad is using them to help create safer drivers.  Continue Reading

• Machine vision makes paper a thing of the past for insurers

  The insurance industry is buried in paper-based processes. Former MetLife CIO Gary Hoberman aims to change that with a platform that runs on AI and machine vision.  Continue Reading

• How to do a machine learning platform comparison

  Experts share their top criteria for choosing the right machine learning vendor in a market that has become crowded and confusing in the last couple years.  Continue Reading

• Chatbot applications must get better at chatting to engage users

  Today's AI chatbots are good at taking orders and delivering scripted responses, but experts say tomorrow's chatbots need to be more conversational in order to deliver bigger value.  Continue Reading

• Wayfair's chief architect talks AI-driven innovation, impactful IT

  Wayfair sells home furnishings, but under the covers, it's a tech juggernaut. Chief Architect Ben Clark explains how AI-driven innovation propels the business.  Continue Reading