Applied Artificial Intelligence: An Introduction For Business Leaders by Marlene Jia & Adelyn Zhou & Mariya Yao

Author:Marlene Jia & Adelyn Zhou & Mariya Yao [Jia, Marlene]
Language: eng
Format: azw3
Publisher: TOPBOTS
Published: 2018-06-01T16:00:00+00:00

If you answered in the affirmative to all three questions, your project may be suitable for AI.

Build vs. Buy

If you ask your engineers whether you should build your own machine learning software, they will almost always say yes. What technologist doesn’t want to master the latest and greatest innovations and play with shiny new tools? Unfortunately, this is rarely the correct solution for most companies, especially those that are still completing digital transformations and have not repeatedly demonstrated the ability to design, develop, and ship successful technology to both internal and external customers.

Many of the tech giants offer to “democratize AI” by releasing open-source development tools such as Keras, TensorFlow, CTNK, and PyTorch, or offer enterprise cloud solutions and proprietary Machine Learning as a Service (MLaaS) platforms. For companies that don’t have the infrastructure or the technical knowledge, these represent excellent solutions for quickly integrating AI capabilities into your company’s workflow . If you already store data and build applications on Amazon Web Services (AWS), Microsoft Azure, Google Cloud, or Apple’s iOS platform, using tightly integrated machine learning solutions like AWS Rekognition or Apple’s Core ML can simplify work for your own developers and may be the most economical business decision.

However, the mere existence of a solution does not mean that it’s definitely right for your company. In the digital era, data is the hottest commodity. Many executives tell us that they are concerned with the potential business impact of sharing data and outsourcing technical expertise. Google, Amazon, Facebook, and other internet giants already own an enormous amount of data about your customers and employees. These tech companies often know more than you do about what your customers search for, what they buy, what they say, who they interact with, where they are, and how they might behave in the future. Their expertise has helped them to grow rapidly with high profit margins, overwhelming less tech-savvy competitors in the process.

Technology companies may not compete directly with you today, but heed prominent venture capitalist Marc Andreessen's warning that “software is eating the world." (61) As consumers opt for the convenience of Amazon Prime and investors question other companies’ abilities to compete against the “Amazon Effect," retailers across a wide range of industries have seen their profits and stock values decline. (62) Amazon has even launched private labels for popular product categories that directly compete for market share with third-party sellers on their own platform. (63) Web traffic and advertising revenues have plummeted at many online media publishers. (64) Even though digital advertising spending is growing, Google and Facebook present a duopoly that captured 85 percent of the new growth in the first quarter of 2016. (65)

Technological superiority alone cannot account for success. Even well-funded tech behemoths have failed when entering new markets or when copying the products of their competitors because they failed to master business fundamentals first. However, as data, analytics, automation, and AI have infiltrated all aspects of modern life, companies primed to take advantage of them will have no problem trouncing those that are unprepared.

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