By the year 2020, all enterprises, whether small or large, in the US, will depend on some form of deep learning and artificial intelligence to ensure competitive advantage.
According to a recent study, by 2021, Gartner projects that 40% of new enterprise applications implemented by service providers will include AI technologies.
In the recent future, we are witnessing an acceleration and urgency in AI adoption by enterprises. Some of them called `Intelligent Enterprises’ are adapting AI to create new business tracks, and offer superior customer experience, while several are adopting AI to modernize business processes, and manage costs.
What Makes an Enterprise `Intelligent’?
Intelligent enterprises use existing data to unfold business secrets, smarter and faster through deep learning, automation, and integration. Enabling them in unraveling data is AI, which through automation, deciphers loose data to provide valuable and actionable insights. A recent study on the `Power of AI’ by a well-known research organization confirms that 82 percent of participants confirmed that they would use AI actively in 2018.
Mindshift to an Analytics-Driven Mindset
Global enterprises are actively using AI to exploit data and information for the opportunities that it provides. It has become the secret mantra for predictable outcomes.
The 4-Step AI Application Process for Business Success
Descriptive Analytics or Business Intelligence as it is more popularly known is like a rear-view window to business performance. It looks at historical events, for example – what were the sales in the last year, what was the overall organizational revenue, the number of cars that were recalled, and so forth. As we begin finding answers to these kinds of questions, the looming thought in most minds is, “What happens next?”
This is where Predictive Analytics enters the scene. Businesses can use Predictive Analytics to strategize for the future. Advanced data science tools help to integrate multiple data streams. Thus, through predictions, businesses can find valuable answers to avert future problems. Answers to questions such as “which model of vehicle will meet with assured success” “which is the weak part of the mechanism which needs to be strengthened,” or “which component could be the weak link.”
Thus, while Descriptive Analytics looks at past data for patterns, Predictive Data provides future predictions. Intuitive knowledge becomes the key to find workable solutions for the future.
To find solutions to avert future challenges is Prescriptive Analytics. Prescriptive Analytics helps enterprises to discover the best course of action. It can also recommend options and help to automate processes to future-proof businesses.
To illustrate the use of Prescriptive Analytics, integrated farming, for example, looks at real-time data streams such as weather fluctuations, soil quality to automate the entire farming process. This is an example of how something as modern and next-gen as Prescriptive Analytics is rewriting the rules of the game for a very traditional business segment. Techniques in deep learning, neural networks, optimization, and decision-analysis methods drive this level of analytics.
Cognitive Analytics which can be termed the future of AI unlocks the hidden insights from existing data. By applying artificial intelligence to specific tasks, a cognitive application continues to evolve. Its value grows as it learns from its interactions with processes, humans, and tasks to define the best course for the future.
The four forms of analytics are equally valuable as they continue to create new business opportunities, position companies for competitive advantage and provide superior customer experiences. The following infographic depicts an analytics journey and the evolution of the “Intelligent Enterprise.”
How WinWire is helping enterprises drive innovation using AI
With deep expertise in Analytics, Automation, Artificial Intelligence, and Machine Learning, WinWire has been successful in delivering innovative enterprise applications to its customers to enhance customer experience, drive innovation and optimize operational effectiveness and efficiency.
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