The results of a new In-Stat U.S. consumer survey demonstrate that while respondents' existing home networks are fairly evenly split between Ethernet and Wi-Fi, future home network deployments are largely planned as Wi-Fi networks. The 640 tech-savvy consumers who participated in the survey still chose data-networking applications over consumer electronics applications as the applications for which they were most interested in using Wi-Fi connectivity. "Consumer electronics vendors have a challenge to educate consumers about Wi-Fi and to overcome the perception that Wi-Fi is simply a data networking technology," says Norm Bogen, In-Stat analyst. "Nevertheless, Wi-Fi silicon vendors have fully committed to this market segment, and In-Stat believes the benefits to consumers of Wi-Fi connectivity in consumer electronics devices are significant enough to build a major market segment over the next five years." The challenges that Wi-Fi faces, in terms of range, bandwidth, security, and Quality-of-Service (QoS), are being addressed by new standards that have either recently been ratified or are set to be ratified over the next several years. The prevalence of wireless network availability, especially in home networks, makes it increasingly likely that any consumer electronics device would benefit from Wi-Fi connectivity. More PCs in a respondent's household was positively correlated with a greater likelihood of having heard of Wi-Fi being used in various devices.
Artificial intelligence (AI) has rapidly become the defining force in business technology development, but integrating AI into applications remains a formidable challenge. According to a recent Gartner survey, 77 percent of engineering leaders identify AI integration in apps as a major hurdle for their organizations. As demand for AI-powered solutions accelerates across every industry, understanding the tools, the barriers, and the opportunities is essential for business and technology leaders seeking to evolve. The Gartner survey highlights a key trend: while AI’s potential is widely recognized, the path to useful integration is anything but straightforward. IT leaders cite complexities in embedding AI models into existing software, managing data pipelines, ensuring security, and maintaining compliance as persistent obstacles. These challenges are compounded by a shortage of skilled AI engineers and the rapid evolution of AI technologies, which can outpace organizational readiness and...