Strategic advice & alerts to leverage data analytics & new technologies

Leverage data and the technologies that generate it, from ML, IA, NLP, blockchain, IoT, and emerging tech; to data science, data visualization, predictive modeling; to data quality, data governance, and data architecture.

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The number of Internet of Things (IoT) devices — ranging from connected consumer products like smart speakers, TVs, refrigerators, and stoves to sensor-enabled industrial machinery and business equipment — continues to proliferate, but many of these devices lack strong built-in security features. This Advisor considers the application of AI and blockchain technologies for strengthening the cybersecurity capabilities of IoT devices and networking environments as well as future developments in this area.
Intelligent automation applications are reaching the point where both organizations and governments must create policies regulating the use of and the liability associated with using smart technologies.
This Executive Update investigates blockchain adoption in the transport industry; it also describes common challenges and provides practical recommendations for the future.
An important trend is the development of emotion recognition technology for speech-based systems with the goal of optimized customer engagement while providing an enhanced customer experience.
To mitigate cybersecurity threats, it is essential to understand the cycle of infor­ma­tion security governance and control: preparation, prevention, detection, response, and learning. This information security management cycle provides important guidance to organizations dealing with security incidents. However, in the con­text of Industry 4.0, these five tasks present different challenges. This Advisor explores the challenges of cybersecurity management.
Neural-symbolic artificial intelligence (AI) combines the pattern-recognition and pattern-matching capabilities of neural networks with the symbolic-reasoning functionality and transparency features of rule-based and knowledge-based systems (KBSs). One of the main goals of neural-symbolic AI is the development of hybrid AI systems that are more explainable and transparent in their reasoning.
Yesha Sivan and Yonatan Rabinovitch discuss how to manage “black swans” crises with what they propose as the Three New Normals (3NN) framework. The authors explicitly state that the 3NN framework “was designed as a flexible descriptive framework, allowing for optimism, pessimism, or realism.” It focuses on how digital leaders can navigate sea changes.
Cui Zou, Wangchuchu Zhao, and Keng Siau respond directly to COVID-19 by framing the skills and training necessary to survive crises. The authors focus on the importance of helping organizations prepare beyond the current pandemic by teaching everyone how to use the technology tools — and exploit the processes — around remote working.