Organizations across sectors are looking closely at the technology to see what it can do for their business. As they should—one estimate suggests that 40% of all the potential value that can created by analytics today comes from the AI techniques that fall under the umbrella “deep learning,” (which utilize multiple layers of artificial neural networks, so-called because their structure and function are loosely inspired by that of the human brain).

In total, the estimate suggests deep learning could account for between $3.5 trillion and $5.8 trillion in annual value. While applications of AI cover a full range of functional areas, it is in fact in these two cross-cutting ones—supply-chain management/manufacturing and marketing and sales—where AI can have the biggest impact, at least for now, in several industries. Combined, these use cases make up more than two-thirds of the entire estimated AI opportunity.

While overall adoption of artificial intelligence remains low among businesses (about 20% upon our last study), senior executives know that AI isn’t just hype. Organizations across sectors are looking closely at the technology to see what it can do for their business.

As they should—we estimate that 40% of all the potential value that can created by analytics today comes from the AI techniques that fall under the umbrella “deep learning,” (which utilize multiple layers of artificial neural networks, so-called because their structure and function are loosely inspired by that of the human brain). In total, we estimate deep learning could account for between $3.5 trillion and $5.8 trillion in annual value.

However, many business leaders are still not exactly sure where they should apply AI to reap the biggest rewards. After all, embedding AI across the business requires significant investment in talent and upgrades to the tech stack as well as sweeping change initiatives to ensure AI drives meaningful value, whether it be through powering better decision-making or enhancing consumer-facing applications. Read more from hbr.org…

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