Artificial Intelligence (AI) is not some sort of sci-fi or apocalyptic eyesight of the future. Actually, it’s already being used by some of the most successful businesses throughout the world, both in and from the Fortune 500, to reduce costs, generate revenue and increase efficiency. Here are some of the very best ways to use AI in your business now.
The majority of us are not data analysts. We need systems that actually explain in simple English (or Spanish or French or whatever) what data means and what we should do about it. In short, we need systems that speak our vocabulary, not systems that speak database, to coin a term.
We discuss this in and how one of the very best ways to use AI solutions is to automate the last mile in data evaluation and analytics. You can read more in the eBook “Natural Language Generation: The Last Mile in Analytics and BI”. Robo-journalism is a buzzword for a long time but writing tales from data can be a lot more than typical systems that write simple descriptive stories like we’ve seen about sports. These standard systems were very good at explaining factual occasions but they cannot explain the explanation behind a summary, offer a summary of large amounts of data, or any contextual information.
Today, companies focused on data monetization use Natural Language Generation software to automatically write content about data, that they would not have the person capacity to write without the tools. This white paper looks at this exact use case in financial services and how technology can help. We all have been familiar with tools like Siri or Cortana. These kinds of technology are called Natural Language Understanding (NLU) software, never to be confused with Natural Language Generation software.
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- Create a virtual data layer across all business data resources
- Approximately 130 people receive suggestions from their friends on different products
We put together an inforgraphic to clear up the differences. NLU software turns unstructured data into organized data. Technically, when you speak to Siri, the software is taking your talk (unstructured data) and structuring it therefore the machine may use it. Today, dashboards have become so complex that businesses need to hire the services of a data analyst to clarify what the info means and what styles to attract from it.
However, regarding to McKinsey, the U.S. 190,000 people with analytical data skills and a shortage of just one 1.5 million analysts who can make decisions from data. To address this problem, businesses are turning to Artificial Intelligence. Technologies like Yseop Compose can easily analyze and clarify what data suggest as they draw insights and action items from the data set.
It’s hard for businesses to market complex products (such as financial services, automobiles, or other big-ticket items) because sales people can only keep track of so many products in their head. By the end of your day many sales representatives simply sell the merchandise they know, not the best products for the customer. Sales enablement is one of the very best ways to use AI. Natural Language Generation tools, for example, can write talking factors for conferences and memos to help inside sales people and sales representatives more generally, sell the right product to the right customer at the right time.
But I don’t caution. It had been the plain thing to do at that time, and at no future point in history will a “free book” be automatically appealing to anyone, unless it is a rare wonder by a big name. Genie out of the bottle and it is never heading back in. But I also foresee major changes–that free books (supported by advertisements) and the subscription services will be the “new normal.” Maybe, in when three years. Just look at the dramatic arcs and changes of the past three years–is there any reason to suspect the digital future won’t change just as rapidly? THEREFORE I can barely call it a “marathon” –more just like a 440-meter run.