How Leading Companies Use Neural Networks [AI]
Leaders are using AI more broadly across their organizations, especially in areas that appear incidental to generating short-term revenue…
AI leaders and followers alike are using the AI technology to automate the IT function. This is critical because IT costs are rising and network protection has increasingly become a battleground between machine learning and hackers (as Microsoft has found). The exact same percentage of AI leaders and followers are using AI in the IT function: 66%. Surprisingly, a higher percentage of followers were using AI in customer service: 36% vs. 32% of the leaders. However, AI leaders were more frequently using AI in other areas than followers. The functions with the biggest differentials in usage were: Corporate level (31% of leaders vs. 12% of followers) Distribution and logistics (20% of leaders vs. only 6% of followers) Human resources (25% of leaders vs. 12% of followers) Finance and accounting (35% of leaders vs. 22% of followers) None of those four functions touches customers every day. Yet the companies we surveyed that generated the greatest value from their AI initiatives in 2015 — our leaders — — were much more likely to be using the technology in those functions . AI systems used in finance can spot customers with credit problems before credit is granted. Microsoft has used machine learning to decrease credit card fraud for its consumer products like Xbox. HR departments have huge amounts of digital data today that they could use to identify unhappy, highly productive, 49 highly influential, and other employee types. But without AI to do the trend-spotting, companies can’t easily do it manually. Most companies have learned that highly motivated employees are key to corporate productivity, and that certain employees’ opinions are cherished by far many more people in an organization than others’.
Examples of business activities which use AI to solve the problems…
Potential customer payment problems: We found that 83% of leaders using AI in their corporate center are using it to identify potential revenue and profitability problems from data in their financial systems. An example of such a problem might be a customer who is late in paying dozens of invoices to multiple business units of a large company. Also, 60% of leaders that use AI in finance are using the technology to identify high-risk customers. For example, Microsoft told us that machine learning has been highly effective in identifying fraudulent credit card transactions. Hacking and other attacks on corporate computer networks: Many big companies’ information systems are attacked daily . A company’s ability to detect and secure its networks is increasingly vital to protecting customer records, preventing proprietary and valuable intellectual capital from leaking out, and keeping the business running. Leaders and followers alike appear highly attuned to the value of AI in protecting their information systems from external or internal attacks. Some 45% of the leaders are using AI for this purpose today (calculated by multiplying the 66% of leaders who are using AI in IT by the 69% of those using AI in IT for this purpose). Protecting the company against computer attacks is one of the most popular ways that the companies we surveyed are using AI now. Crucial products and services powered by digital technologies, and whose performance for customers can never slip: The self-driving car is a perfect example. If the goal is to reduce accidents (and for taxi companies, to minimize personnel costs), then the product must have excellent accident-avoidance performance. Even Microsoft’s use of machine learning for its Bing search engine is a great example of a product that has millions of digital interactions every day (customers’ online search entries) that require better and better real-time responses (i.e., better search results). Google has embraced machine learning and is trying to implement it in all of its products. As its CEO Sundar Pichai said in 2015 to investment analysts, “Machine learning is a core, transformative way by which we’re rethinking how we’re doing everything … across all our products, be it search, ads, YouTube or Play.” Added Jeff Dean, senior fellow at Google’s Research Group, “Previously, we might use machine learning in a few sub-components of a system. Now, we actually use machine learning to replace entire sets of systems, rather than trying to make a better machine learning model for each of the pieces.”
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