Alan Gibson, VP EMEA at Alteryx explains that these technologies have real business-altering potential and that's why Gartner's Enter the Age of Analytics report predicts that by 2023, AI and deep-learning techniques will be the two most common approaches for new applications of data science. But despite the promise, few companies have been able to successfully implement and deploy this technology as part of their overall data and analytics strategy--according to Gartner, 46 percent of CIOs have developed plans to deploy AI but just 4 percent have made the concept a reality. The truth is that it will take years before many organisations realise the true potential of AI and ML, but it is never too early to lay the groundwork now for an AI-driven future. In fact, if an organisation is not already thinking about what an AI strategy looks like, its competition is likely one step ahead. There's no time to waste, so here are five important points to consider when getting started with AI and ML.

Five years ago, perhaps not many people would have thought of Abu Dhabi and the UAE as global leaders in artificial intelligence (AI). That changed in 2017 when the UAE became the first country in the world to create a dedicated AI ministry. Today Abu Dhabi is taking another important step at placing AI at the core of our future by announcing the world's first graduate level AI university. AI has emerged into the mainstream and is quickly becoming embedded in our daily lives. Machines that learn can now be found across the globe and are transforming organisations and the way things are done, covering everything from antivirus software to IT infrastructure management.

Companies plan to spend big money on AI -- as much as $77.6 billion by the year 2022 according to some estimates, with a compound annual growth rate (CAGR) of a whopping 37.3%. That spending is an investment that can be expected to pay rich dividends in the future. AI is a competitive advantage and leaders would be wise to ensure their companies are AI-ready. But how will the rapid rise of AI change what's expected of leaders -- today and in the future? According to It's the Manager, of all the traits of successful leadership Gallup has studied, most can be "distilled down to two elements" -- bringing multiple teams together and great decision-making.

Companies around the world are investing tens of billions of dollars on artificial intelligence (AI) and machine learning (ML), and for good reason. These technologies have real business-altering potential, and that's why Gartner's "Enter the Age of Analytics" report predicts that by 2023, AI and deep-learning techniques will be the two most common approaches for new applications of data science. Effective use of both AI and ML in business production use cases can help enterprises that use them jump far ahead of competitors in their sectors, because the technologies remove friction that gums up processes. But despite this promise, few companies have been able to successfully implement and deploy this technology as part of their overall data and analytics strategy. According to Gartner, 46 percent of CIOs have developed plans to deploy AI, but just 4 percent have made the concept a reality.

Recognizing the pervasivetalent gapthat exists between data scientists and data workers in the line of business, Assisted Modeling helps teach data science with a guided walk-through and aims to help all data workers, regardless of technical acumen, advance their skill sets in the process of building machine learning models. Our approach in building Assisted Modeling is to advance the skills of the data worker, creating next-level citizen data scientists capable of building the machine learning models required to tackle the advanced analytic challenges of the future. Assisted Modeling provides users the transparency and control needed to build trustworthy machine learning models that drive business outcomes without writing a line of code. As an output of the application, users can access code-free machine learning tools directly within the Alteryx Designer interface. Assisted Modeling allows any data worker to construct machine learning models, understand how and why their models work, and capture modeling decisions, turning raw data into informed business decisions with unprecedented speed and confidence.

For two straight quarters, deal activity in artificial intelligence has hit record highs. Dennis Mortensen is one of the biggest winners in all the craze. His startup x.ai is the creator of Amy Ingram, an AI-driven personal assistant that can schedule meetings for you. After testing Amy in beta for two years, Mortensen announced last week 23 million in Series B funding to bring Amy to market. Dennis Mortensen: AI used to be for academia only and decades-long research.