In Gartners new report, “Top Strategic Tech Trends for 2023,” Gartner takes a deeper look at the biggest IT trends of the coming year, and what companies should expect. With money concerns again at the forefront for most businesses today, Gartners top 10 strategic technology trends for 2023 are focused on technologies that will help them improve resiliency, optimize operations, expand capabilities, and engineer new forms of customer engagement. According to analysts at ABI Research, there are a handful of trends capable of shaping the market, along with those attracting lots of attention, investments, but that are unlikely to impact the 2023 marketplace. Show Source Texts
Some key trends driving the accelerated market today include advances in big data analytics, data science, and artificial intelligence, which are changing how businesses are done around the world. C-level executives across various industries are using data analytics to make better business decisions and to better serve customers and be more efficient. Beyond Big Data is a one-stop shop for managers at all levels to learn more about the opportunities in these technologies, connecting with others across the industry. Show Source Texts
Augmented Analytics is contributing to the evolution of data science platforms and embedded analytics. With artificial intelligence, enterprises are strengthening their approach for migration into cloud, improving the efficiency of data-intensive applications. Todays devices, services in the Internet are becoming smarter and safer by adopting AI and ML. More data analytics trends are likely to arise and thrive in 2022, 2023, and beyond, as we continue with AI developments. Show Source Texts Augmented analytics is likely to see various developments over the next few years or years, becoming a major player in the rise of BI platforms. From chatbots and virtual assistants such as Siri and Alexa, to automated industrial machines and autonomous vehicles, the implications of artificial intelligence (AI) are difficult to ignore. Today, the most widely used technologies for AI are machine learning — high-level software algorithms designed to perform one particular task, like answering questions, translating languages, or driving on a road trip — and become more adept at that specific task as they are exposed to more data. While generative AI is most commonly associated with deepfakes and data journalism, the technology is playing a growing role in helping automate the repetitive processes used in digital image and audio correction.