Reality And Errors About The Future Of Artificial Intelligence (AI)

Source: Deep Learning on Medium

Reality And Errors About The Future Of Artificial Intelligence (AI)

A deep dive in four recurring statements about AI

Artificial intelligence (AI) is changing the way machines and people work together. It improves customer interaction across industries and drives operational and process improvements. More than 40% of companies expect AI to be a game changer. The German government also wants to accelerate the introduction and development of AI technologies. It plans to invest 3 billion euros in AI research by 2025. But 77% of companies also say that acceptance in the economy is a challenge. To date, only a few boardrooms are ready to weigh the risks and opportunities associated with AI.

AI is different from other technology innovations. In order to have a more complete picture of the available skills and possibilities, in this article I address four statements that customers most often address to me:

“AI promote innovation and business success.”

The heart of AI and other leading technologies is data. The quantity of data is usually not lacking, as there is usually more than enough in the age of increasing amounts of data. According to Statista, the world’s large data market will grow to $ 103 billion by 2027, more than doubling its market size in 2018.

In addition to the quantity, AI models also depend on the quality of the data that must be ensured. In addition, the challenge for most companies is to collect and create meaningful correlations of data stored in silos throughout the company, data from external sources, and data that is transferred to the company in real time.

Managing large amounts of data requires long-term commitment and planning to cope with future growth. If you think too small, it may take a long time before an AI investment pays off economically and the business case pays off.

Choosing the wrong platform, tools, or poor integration can also waste valuable time and add significant costs and complexity to implementation and ongoing management. Corporate governance and security strategies are critical to avoiding regulatory and regulatory compliance issues when developing new technologies. As in other areas, AI technology is developing faster than regulation. But the evolution of (sometimes country-based) data and AI regulations will increase. Since no responsible board member can afford to remain unprepared but still use potential, it is a consideration, for example,

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