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April 13, 2017
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Four Trends in Artificial Intelligence That Affect Enterprises

Andrew Ng, the renowned data scientist, has said that artificial intelligence (AI) needs to be a company-wide strategic decision. Companies that don’t strategically invest in AI will slowly lose market share to companies whose core businesses are built around AI.

AI enables the prediction, planning and automation of a variety of tasks, and for enterprises, there are four trends in artificial intelligence that stand out: large-scale machine learning, deep learning, human-enhanced AI and autonomous systems. Contributing to these trends are less expensive and more powerful hardware, and end-to-end data platforms that maximize the value of data-in-motion and securely store, manage and perform complex processing of data-at-rest. Furthermore, pure and hybrid cloud deployments enable companies to quickly scale and access additional resources on demand.

Here’s a bit more on the four trends in artificial intelligence that affect enterprises.

1. Large-Scale Machine Learning

A classic example of machine learning is detecting fraudulent login attempts. Instead of explicitly specifying every rule and every possible fraud case, machines learn by being presented with thousands of examples. The advantage here is that once the initial model has been created, it can continuously evolve. [Read more]

2. Deep Learning

Due to recent improvements in computer graphic cards and releases of popular frameworks, deep learning has some excellent results in specific narrow use cases with actionable intelligence. This now makes it possible for businesses to hone in on new business opportunities. Additionally, raw processing costs are falling rapidly, lowering the barrier to entry for everyone, and there are many pre-trained (downloadable) components that allow companies to significantly shorten model training time and focus on optimizing their networks for their specific use cases. [Read more]

3. Human-Enhanced AI

Another common trend is having humans evaluate results from AI. AI is still a long way from having humanlike abilities of comprehension, reasoning and intuition. Human-AI teaming will result in better outcomes than either alone would provide. For instance, in health care, using the combination of AI and the human experience can reduce false positives and increase patient satisfaction, which often leads to monetary gains. [Read More]

4. Autonomous Systems

More and more systems operate and adapt to new circumstances with little to no human control, changing the landscape of the workforce and the way we think about the workforce moving forward. This category is much broader than just autonomous cars or drone delivery. There’s automated financial trading or automated content curation systems, such as creating automated news digests around sports or finance. But more importantly, driving the business includes the ability to diagnose and update internal systems such as security vulnerabilities, which is key in the world of rapidly evolving cybersecurity threats. [Read more]

In light of the evolving AI trends in the coming year, it’s important to keep in mind that “AI is eating the world and will eventually eat every vertical,” as Sanjit Dang, of Intel Capital, recently said at the Global AI Conference. And data science plays a vital role in unlocking the potential of enterprise data to extract maximum value, improve revenue and increase profitability.

Check out our white paper on Four Tenets of Modern Data Science and Machine Learning to learn more. And, to understand more about The Future of the Digital Enterprise, watch The Data Works Summit, Munich keynote.

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