Software enables completely new inspiration in the creative process By keeping AI software development entirely in-house, Audi demonstrates competence in a crucial emerging field Leveraging artificial intelligence (AI) in all departments: this is the goal Audi has set itself on its way to becoming a data-driven company. With FelGAN, the company now employs software that uses artificial intelligence to open up new sources of inspiration for designers. Creative people are always on the lookout for inspiration. The same is true of the designers who create new wheels at the Audi Design Studio in Ingolstadt. But where to find untapped sources of inspiration?

CFO CFO of Sandline Global & author of Deep Finance, Glenn has spent the past two decades helping startups prepare for funding or acquisition. Artificial intelligence (AI) is to business what telescopes are to star gazing--an incredible technological boost that magnifies, clarifies and illuminates business decisions. AI-enabled technology drives everything from algorithms that filter spam emails to complex systems that can drive cars without human intervention. Advances in AI over the past decade have been nothing short of astounding. Thanks to advances in computing power and the ever-increasing data available to train models, growth in AI and machine learning (ML) has been exponential. Machines can now teach themselves to play and beat the best players in the world in skilled games like chess, Go and countless other digital strategy games.

Data is a company's most powerful asset. Yet, many businesses cannibalize this valuable asset by selling it to third parties when they should be using it to make their businesses stronger and more sustainable. Nearly all digital businesses collect some type of data from their users, so there has been growing concern from privacy rights groups about how that data is used. Yet, data collection is not wrong in and of itself. It's the why, how and what is done with it that matters most when it comes to building a profitable and sustainable business that simultaneously respects the privacy of its users.

It is undeniable that acceleration in technology requires firms to revisit the core of their business. Success stories enabled by data analytics and machine learning are becoming public at accelerating pace as firms try to position themselves as digital leaders. This creates urgency to evaluate automation as a new source of growth across all industries. However, companies that rush into sophisticated artificial intelligence before getting control of their data and setup structured analytics might end up paralyzed. Let s outline a typical bad scenario.

The key to making better business decisions is surprisingly simple: take a proactive approach to using data. Every company gathers data in one form or another, but the way a company uses its data has a lasting impact on the ability to compete, innovate, and attract talent. For many companies and their employees, data is gathered and handled reactively. They collect and use data intermittently on an as-needed basis, but it's seldom collected for historical analysis to support the creation of AI solutions. Data-driven companies believe that being proactive with their data is the ultimate differentiator.

You're in good company – a recent article by Laurence Bradford in Forbes calls data science'the century's hottest career'. But how can you get your foot in the door? Many resources out there may lead you to believe that becoming a data scientist requires comprehensive mastery of a number of fields, such as software development, data munging, databases, statistics, machine learning and data visualization. You don't need to learn a lifetime's worth of data-related information and skills as quickly as possible. Instead, learn to read data science job descriptions closely.

Engulfed in a strange new world, the pharmaceutical industry understands there are industry changes; however, they are not certain what to do about them. Interestingly enough, the automotive industry is facing similar challenges. Both industries are multi-faceted behemoths with a traditional approach. And like many other industries – journalism, for instance, or music – it's important that they recognize the changes that are occurring and plan for strategies that will keep them competitive. Both industries have focused on breakthroughs as key components of their business model.