The State of AI 2019: Divergence

whitePaper | December 1, 2021

The health and vibrancy of our national economy depends on the health and vibrancy of our organizations. How an organization is staffed is a key driver of its health. Yet only one in three executives rates his or her company as “very effective” at reducing unsuccessful hiring decisions (Bravery et al., 2019). Thus, industrial-organizational (I-O) psychologists help organizations thrive by choosing the right talent for the right job at the right time, using the most accurate, cost effective, and fair tools available (Ployhart, Schmitt, & Tippins, 2017).

whitePaper | February 21, 2020

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whitePaper | February 15, 2023

Artificial intelligence (AI) is an enabling technology impacting the global economy and international trade. Combined with business-process-oriented automation and more efficient data flow exchanges, AI further promises to lift barriers to international trade, stimulate growth in global electronic commerce and allow for better predictions and associations to inform policy decisions.

whitePaper | August 25, 2022

Businesses are in different stages with their artificial intelligence (AI) technologies. Even today, after many years of evaluating AI, only one third of organizations have actually put AI into production (31%1 ). Organizations that started somewhat later are currently prototyping their AI solutions (20%). Companies that only recently came on board with AI are experimenting with AI technologies for their business cases (25%). And a relatively large portion (24%) have only just begun evaluating AI for their business cases.

whitePaper | August 23, 2022

This white paper describes the features and benefits of a machine learning-based resource optimization solution that helps the Dell High End Storage Field Services Team perform capacity planning more efficiently and with the potential to optimize resource utilization and overtime.

whitePaper | July 10, 2020

There’s no arguing that preventing failures and accidents is critical for industry. Unexpected incidents can grind operations to a halt for extended periods of time and necessitate expensive repairs. Just 12 hours of downtime for an oil production platform could cost six to eight million dollars in lost production opportunity alone. A single day of grounding for a plane costs roughly four to five million dollars. Because of these disruptions, industrial sectors are always on the lookout for newer, better maintenance methods, and the approach on everyone’s lips right now is predictive maintenance. While everyone agrees on the name, there is less consensus on what it means or how to implement it. But to truly unlock the potential of predictive maintenance, it needs to be paired with artificial intelligence (AI) and machine learning (ML).