74% of executives predict AI will be integrated into all enterprise applications within three years

After 5 years of relentless buzz about AI, is it finally hitting the mainstream? A new report by the Deloitte AI Institute about the State of BI in the Enterprise shows the giant leaps that enterprise businesses are taking to integrate AI into their data processes.

To obtain these insights, Deloitte surveyed 2,737 executives across nine countries from companies which have adopted AI technology. In this year’s survey, 73% of adopters say AI is very or critically important to their business success today, and 71% expect to increase their investment next fiscal year.

An interesting finding from the report is the overwhelming preference that enterprises have for buying over building AI technology in-house. Just 8% of the executives surveyed said they will “build all” their AI technology, and 13% responded they will “build more than buy.” The remaining 79% will be looking to purchase solutions within a thriving market of tools and alternatives that fit their needs.

With this appetite for outsourced AI tech it is not surprising that AI startups raised $31.8 billion over 2,899 deals in 2019. Of course, there are multiple types of technologies within the umbrella of AI, including machine learning, deep learning, natural language processing, and computer vision. So it is important not to treat AI as a homogeneous industry, whether in terms of technologies, the companies developing solutions, or the market needs.

In the words of Jason Yosinski, co-founder of Uber AI Labs: “This is a new period in the world’s history — we build models and machines in AI that are more complicated than we can understand”. No matter the industry, it is most likely being equipped with AI technology to evolve.

Whether it is used by marketing teams to model and predict user behavior, or by e-commerce platforms to mitigate cyber attacks, the applications of AI are broad and diverse. To an extent, any data-driven organization that relies upon insights or vast amounts of data will benefit from AI technologies.

For some companies, AI is about automating processes previously executed by humans. But for most businesses, AI will optimize processes, such as preventing fraud, finding errors in software code, or personalizing ad placement. AI technologies also enhance what individuals and teams can accomplish. AI enables much more sophisticated data analysis and insights that can predict trends, forecast revenues, and even diagnose patients with better data.

But while a machine can suggest the right reply to an email, it won’t kill human jobs any time soon. That’s because AI can’t replace human cognitive skills. In an article for MIT Tech Review titled What AI still can’t do, Judea Pearl explains that AI can’t be truly intelligent until it has a rich understanding of cause and effect. As a quote from the article explains the dilemma of machine intelligence: “It’s as if you knew that the presence of clouds made rain likelier, but you didn’t know clouds caused rain.”