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Conversica Survey Shows Chatbot Customer Experience Significantly Impacts Vendor Evaluation for One-Third of B2B Buyers

Conversica, Inc., a leading provider of AI-powered conversation automation solutions for enterprise revenue teams, announced the findings of a new survey titled Chatbot Experience: How Satisfied Are Enterprise Buyers? The study found that while the majority of B2B buyers use chatbots when considering a business purchase (60%), the chat experience does not meet their expectations.

“State of AI in the Enterprise” Report, 5th Edition, Uncovers Four Key Actions to Maximize AI Value

The Deloitte AI Institute’s fifth edition of the “State of AI in the Enterprise” survey, conducted between April and May 2022, provides organizations with a roadmap to navigate lagging AI outcomes. Twenty-nine percent more respondents surveyed classify as underachievers this year, yet 79% of respondents say they’ve fully deployed three or more types of AI. It is clear despite rapid advancement in the AI market that organizations are struggling to turn implementation into scalable transformation. This year’s report digs deeper into the actions that lead to successful outcomes — providing leaders with a guide to overcome roadblocks and drive business results with AI.

Domino Data Lab Announces Hybrid MLOps Architecture to Future-Proof Model-Driven Business at Scale

Domino Data Lab, a leading Enterprise MLOps platform trusted by over 20 percent of the Fortune 100, announced its new Nexus hybrid Enterprise MLOps architecture that will allow companies to rapidly scale, control and orchestrate data science work across different compute clusters — in different geographic regions, on premises, and even across multiple clouds.

Automation Is An Essential Priority for the Future of Enterprises

In this sponsored post, Eric Herzog, CMO, Infinidat, discusses how virtually every IT decision-maker is looking to automate at some level, either today or in the future. Starting the autonomous automation of enterprise data and storage can catapult an organization forward and give its leaders valuable learnings and insights into the path of automation, which will only expand on the horizon.

10 Must-Have Capabilities of an Enterprise AI Platform

[SPONSORED POST] With the ten must-have capabilities of an Enterprise AI platform outlined in this paper from Veritone, organizations can position themselves for rapid adoption of AI and ML at scale without requiring custom “from-scratch” model development, extensive AI expertise, or single-model dependency. Data-driven organizations use AI and ML, either natively within applications or infused into applications, to obtain better insights into the content that drives their business and automate content-centric processes for greater efficiency. But the proliferation of AI projects, ML models, APIs, and data sets to enable these processes present serious challenges that stand in the way of successful AI and ML deployments.

10 Must-Have Capabilities of an Enterprise AI Platform

With the ten must-have capabilities of an Enterprise AI platform outlined in this paper from Veritone, organizations can position themselves for rapid adoption of AI and ML at scale without requiring custom “from-scratch” model development, extensive AI expertise, or single-model dependency.

The 3 Reasons Enterprises Need an AI Operating System for Intelligent process Automation

This new whitepaper, “The 3 Reasons Enterprises Need an AI Operating System for Intelligent process Automation,” from Veritone highlights how evolving technology meets enterprise demand for agile, intelligence-based solutions in the shape of AI-based operating systems (OS) across three areas: (i) AI OS for automation of human work; (ii) AI OS for process automation across all data sources; and (iii) AI OS for democratization of AI across the
enterprise.

The 3 Reasons Enterprises Need an AI Operating System for Intelligent process Automation

This new whitepaper from Veritone highlights how evolving technology meets enterprise demand for agile, intelligence-based solutions in the shape of AI-based operating systems (OS) across three areas: (i) AI OS for automation of human work; (ii) AI OS for process automation across all data sources; and (iii) AI OS for democratization of AI across the
enterprise.

How Feature Stores will revolutionize Enterprise AI

In this contributed article, Monte Zweben, CEO and co-founder of Splice Machine, discusses Feature Stores which are a new MLOps technology being adopted by cutting-edge companies like Uber, Airbnb, and Netflix, and for good reason. A Feature Store is a system made specifically to automate the input, tracking, and governance of data into machine learning models.

Driving ROI Through AI

This new report from ESI ThoughtLab was conducted alongside our friends over at DataRobot as well as a coalition of other AI leaders. The report shows that despite high adoption rates of AI in enterprises, ROI in AI still remains a work in progress and will take skill, scale, and time.