How Artificial Intelligence Is Working in the Enterprise

1 - How Artificial Intelligence Is Working in the Enterprise
2 - Will AI Take Over the Human Race? Not to Worry
3 - Big Data and Financial Services Go Hand-in-Hand
4 - Sales and Marketing
5 - Health Care
6 - Social Networks
7 - Government
8 - Cyber-Security
9 - What's Next?
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How Artificial Intelligence Is Working in the Enterprise

by Chris Preimesberger

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Will AI Take Over the Human Race? Not to Worry

Despite well-publicized warnings from visionaries Elon Musk and Stephen Hawking about how AI poses a threat to the human race, the reality is there is no evidence that humans are in danger of being exterminated by AI or robots. AI is being designed by humans and for humans, helping improve lives and enabling a wave of benefits in everything from health care, finance and national security to simply allowing us to focus our work on our interests, rather than tedious tasks.

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Big Data and Financial Services Go Hand-in-Hand

With the advent of big data, banks now are able to analyze data in minutes instead of hours, reducing operational costs and empowering analysts. Now, companies such as MasterCard, U.S. Auto Association (USAA) and American Century Investments are using artificial intelligence such as Narrative Science's Natural Language Generation (NLG) to take things a step further, automating everything from investment performance reviews to suspicious activity reports to wealth advisory communications on an unprecedented scale and with very little human capital. USAA also uses IBM Watson's natural-language processing to provide financial advice to its members.

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Sales and Marketing

The days of going with "your gut" in sales and marketing are over. and Netflix have invested millions of dollars in artificial intelligence, including machine learning and predictive analytics to understand what their customers likely want in order to offer recommendations. B2B sales departments are leveraging the same technology, knowing exactly when to up-sell and predict customer churn. With AI, marketing departments are able to cater to customers one-to-one, on a massive scale. Rocket Fuel, for example, leverages machine learning to tailor programmatic media buying campaigns on the fly, self-optimizing them in real time.

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Health Care

Health care is one of the most data-intensive industries—not just in terms of volume, but the intricacies of its information. The enhancement of cognitive abilities through artificial intelligence has led to impressive breakthroughs in health care. A 2013 study at Indiana University showed that using big data analytics in patient care was 30 to 35 percent more successful when compared to doctor performance. IBM Watson has helped numerous medical institutions personalize health care by augmenting their understanding of diseases; the National Health Service of England is using NLG capabilities to turn massive volumes of data into information U.K. citizens can use to make important health decisions, Narrative Science CEO Stuart Frankel told eWEEK.

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Social Networks

Although social networks are primarily geared toward consumers, their work in artificial intelligence is groundbreaking and carries deep implications for the enterprise. Facebook, Google and Twitter have all invested millions of dollars in artificial intelligence, specifically automated machine learning, to better understand structured and unstructured data so that users can successfully connect with the people, information and advertisers they need. These companies have been investing in AI technologies for nearly a decade.

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In-Q-Tel, the venture capital investment arm of the U.S. Intelligence Community, has invested millions of dollars in artificial intelligence technology startups, including Narrative Science and Recorded Future. In emergency services, the U.S. Navy has developed robots that can fight fire and automate many of a firefighter's most dangerous tasks. The United Nations Institute for Disarmament Research (UNIDIR) is aiding world leaders and policymakers in understanding the implications of autonomous technologies and the automation of human decision-making.

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Many companies are beginning to use machine learning and artificial intelligence for cyber-security. Similar to financial services firms using deep-learning models to detect fraud and suspicious behavior, companies such as Allianz are applying machine-learning models to identify new vulnerabilities and suspicious activity to reduce external threats to customer data. A number of security vendors are beginning to include AI elements in their products, including Elastica, Dtex and Brighterion.

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What's Next?

With an increase in the technological possibilities of AI, businesses likely will increase their investments in intelligent machines as a way of augmenting human capital. According to CB Insights, $309 million was invested into pure AI startups in 2014, a 302 percent increase from 2013; mainly, the investments were focused on early-stage startups. It would not be a stretch to say that by 2020, AI will already be ubiquitous in most of our daily work and personal lives.

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