Where is your organization seeing traction using Deep learning or machine learning? Was there a specific task or process you optimized through AI?

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CTO in Software, 11 - 50 employees
Our experience isn't (currently) direct, but a couple of the biometric authentication partners that we're using are leveraging deep learning techniques and models to deliver an AI optimized answer on whether a given biometric factor is a match or not.
Exec. Director - AI Industrialization & Platforms in Software, 10,001+ employees
We are using deep learning to understand the intent of the customer at every touchpoint based previous interactions and other data attributes.
Director - Transformation in Software, 1,001 - 5,000 employees
Audit and compliance, fraud prevention and procurement.
VP of Global IT and Cybersecurity in Manufacturing, 501 - 1,000 employees
Routine tasks, other areas of automation.
Head of Patient Services IT in Healthcare and Biotech, 5,001 - 10,000 employees
We are just beginning and defining the use cases to leverage machine learning to improve patient experience. No current plan for Deep learning in my space.
in Software, 10,001+ employees
We are in earlier stages of ML to predict customer attrition, new money calculation and fraud prevention using regression and classification. At this point our focus is on data prep and building a robust pipeline to achieve better results. We are yet to tap into deep learning.
Co Founder & CTO in Software, 2 - 10 employees
At Foodbot AI we provide services like a loyalty program, table reservations, online ordering, etc. via conversational chatbots over the facebook messenger platform. Contrary to content grouping in mobile apps and websites, in chatbots the user interacts with the Bot via human-like conversations. To predict user intents, sentiments, etc. we use AI and take the respective action. Thus, without any human sitting on the business side we are able to convert our leads into users and make them use the available services.
Senior VP, Global CTO Hybrid IT in Software, 10,001+ employees
We use AI/ML to better understand what's occurring in their environment through a rich telemetry stream provided by the customer that enables us to compare their experiences to the 300 trillion data points we have stored spotting problems that others have encountered and closing new ones based on a team of data scientists and subject matter experts. The end result is improved customer experience and insights. Happy to talk to you further.
CTO in Software, Self-employed
We are using machine learning to do NLP and entity extraction from customer interactions to build relationship graphs between entities (users, customers, companies, products, deals/opportunities). We are using 3rd party software for sentiment analysis to tag the interactions, personality profiling to tag the users and customers and another third party piece of software to suggest content for users to send to customers. All are based on ML algorithms. We are also developing an engine to recommend the next best interaction between a user and a prospect / customer based on the data and tags resulting from the above. This engine allows external systems to in inject suggested interactions into the candidate set to be evaluated for presentation to the users, along side the ones generated internally by the engine. Because of constraints around access to the data and its sensitivity, the first first iteration of the engine is based on rules and heuristics. It is establishing the feedback loop between the interactions suggested, if the user accepted or rejected them, the time to the user actioning the suggestion, and the outcome. The objective is to have a future version that uses this data for unsupervised ML that will allow the engine to train itself on each client data set. This last piece is currently highly experimental, and we are unsure of the ability of the unsupervised ML to deliver acceptable results.
Managing Director Middle East in Software, 501 - 1,000 employees
As a provider of machine and deep learning solutions we are very fortunate to be based in the UAE. We are seeing significant traction and appetite for solutions that make use of AI and we have already built solutions around Smart Waste Management and Smart Parking. The opportunities we see are around monetizing services that operate outside of the commercial economy. Examples include police and civil defence.

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CTO in Software, 11 - 50 employees
No, we haven't published corporate guidance establishing guardrails for use of commercial generative AI services.
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