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Organizations embracing promises of artificial intelligence

The ability to predict business outcomes affords obvious competitive advantages, but understanding why or how the outcome occurs is where artificial intelligence will shine in 2017, according to Michael Schmidt, CTO and founder of machine intelligence company Nutonian. Schmidt offers eight ways in which organizations will incorporate time series forecasting, defined as predicting future outcomes using historical datasets, into their data analysis efforts to understand what shapes the future and to change the outcome.
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Predicting and preventing the next big cybersecurity attack

“Earlier this year, Dyn was hit by the largest DDoS attack on record, taking down major company websites including Netflix, Amazon, Reddit, Twitter, etc.,” Schmidt says. “Imagine if we had the anatomy of the cyberattack and the target in advance? In 2017, security teams will use AI and time series forecasting to identify items that they should quarantine and proactively investigate (i.e. honeypots). As a result, many companies will be able to mitigate the consequences and potentially prevent an attack.”
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Building a market-beating investment portfolio

“The financial industry is full of ever-present uncertainty with huge financial gains and losses potentially at stake,” Schmidt says. “In 2017, Wall Street will turn to AI to dive into corporate data to identify key predictive relationships that are signals or early indicators that an investment is primed to tumble or soar. These will include key drivers of excess returns, and how those variables will move in the context of the current economy.”
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Upgrading the retail experience and profit margins

“To stay competitive in 2017, retailers will turn to AI to better optimize new store locations, staffing, supply chain, new hires and sales forecasting,” Schmidt predicts. “This optimization can make or break a retailer’s profits – the estimated difference between building a new store in a ‘good’location versus an ‘average’ location adds up to $30 million in extra revenue per store per year.”
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Improving patient care with AI-driven medical research

“For a child with acute appendicitis, treatment depends largely on whether the appendix has burst,” Schmidt notes. “But the most accurate way to find out - CT scans - can damage DNA and increase cancer risk. With AI, researchers at Albert Einstein College of Medicine created a formula that allows doctors to utilize technology that has the same level of diagnostic accuracy but doesn’t have the same side effects. In 2017, medical research driven by AI will become the norm – raising the level of patient care across the board.”
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Spending marketing budget more efficiently using AI insights

“Marketing campaigns help grow, engage and convert audience, but it’s often hard to tell which campaigns are effective and under what circumstances,” Schmidt explains. “In 2017, AI will augment marketing by looking at historical sales, marketing campaigns, website discounts, events and competitor events to determine which campaign converted the highest number of customers via what technique, at which time, and with which specific keywords.”
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Using AI to develop better advanced manufacturing materials

“In 2017, manufacturers will use AI to develop and design new advanced materials with the highest level of performance,” Schmidt says. “In manufacturing, there are thousands of things that could go wrong. But with time series forecasting, manufacturers can quickly isolate key factors that are affecting the production process so they can fine-tune their process to ensure quality and a consistent supply for customers.”
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Better matching energy supply and demand

“It can be difficult for electric utility companies to determine how much power to produce each day while trying to provide affordable, reliable and environmentally friendly power,” Schmidt says. “A surplus means wasted resources and preventable emissions, and a shortage means having to purchase power from other producers for a sizable fee. In 2017, time series forecasting will provide the path to calculating energy demand with highly accurate models.”
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Using AI to take the lead in the fight against poachers

On a more humane topic, “illegal shooters have devastated the tiger population while scarce human capital and resources have slowed down governments’ and non-profits’ efforts to combat poachers,” Schmidt says. “The good news is that the National Science Foundation has adopted AI to determine the highest-probability patrol routes while minimizing elevation changes, saving time and energy to fight back. In 2017, non-profits and governments will adopt this AI-driven approach to stop poachers in their tracks to protect endangered species across the globe.”
This article first appeared in Information Management.