Entefy recently covered AI advances in “traditional” industries like agriculture and banking, the follow-up to a look at disruptive technologies in manufacturing and heavy industries like aerospace and automobiles. For all of the differences between these industries, they share in common the need to understand the potential and limitations of artificial intelligence, and plan accordingly.
Can we spot the same common threads running through industries known for their advanced uses of technology? From telecommunications to travel to media, companies large and small are pursuing entirely new products, services, and capabilities created by smart uses of AI algorithms.
Here are 10 examples of disruptive AI technology in action:
1. Mobile telecomm
Wireless telecommunication companies have access to volumes of data from their millions of customers. One telecom implemented a machine learning-powered real-time customer analytics system that enabled it to track and respond to consumers immediately. The data gathered by the new program facilitated better customer service communication driven by the insights from the custom AI system.
People are not, generally speaking, purely rational investors and their irrationality is what makes markets unpredictable. An artificial intelligence algorithm that can anticipate human behavior while also monitoring economic signals in real-time could be highly disruptive to today’s markets (though some insiders have their doubts). Whether or not an AI “super investor” appears on the scene, the investments industry will require ever-smarter safeguards against exploitation and risk.
Online travel booking is nothing new, but AI-assisted vacation planning? That’s more of a novelty. Beyond aggregating flight times and hotel prices, computer programs now pull data about customers’ online behaviors and use learning systems powered by past preferences to personalize recommendations. When a human agent isn’t in the picture, chatbots can now answer questions and book reservations as well. ‘Nothing will ever replace the expertise and intuitive nature of travel agents,’ said one travel industry veteran. ‘Artificial intelligence brings just another component to their tool kit.’
4. Information Technology
IT professionals in particular find themselves at an exciting turning point in their careers. As more companies integrate AI into their processes, to one extent or another, IT teams are learning how to engage with these new technologies. A 2016 report from Narrative Science and the National Business Research Institute predicted that 62% of enterprises will adopt and use AI by 2018. Given that, IT could soon encompass competencies in machine learning platforms, natural language processing, decision management software, and AI-optimized hardware.
5. News media
The media has been under siege by critics and fake news purveyors during the past several years, but it may find an ally in AI. The Associated Press uses AI software to crank out earnings reports, and data companies are increasingly generating information useful to reporters. The lightning speed at which AI algorithms can gather and process multiple types of data could be a boon to journalists, enabling them to report breaking news as it happens. The Los Angeles Times encountered this firsthand in 2013, when it used a bot to report on an earthquake almost as it was happening.
Pharmaceutical researchers have begun integrating AI into developing new drugs. Using machine learning to transform drug creation, these platforms analyze medical histories, chemical databases, and past scientific findings to identify correlations between genetic markers and patient outcomes. This method of drug testing costs 50% less than traditional approaches and provides insight into how a treatment might impact certain types of patients. Pattern-recognition technology can provide a view into how different diseases work as well, allowing researchers to develop drugs that will target them more effectively. Most important, AI deep learning enables doctors to provide more targeted treatment plans based on an individual’s genetics and history.
7. Online dating
Can autonomous systems make better matches than people? After all, people have been matchmaking practically since there were people to match. Dating itself is ripe for disruption: it is time- and labor-intensive and carries a high failure rate. There’s plenty of room for improvement. So it’s not surprising that the online dating industry is exploring adding AI to the game of love, addressing common online dating complaints like dishonesty in profiles and increasing the relevance of the data underpinning matchmaking algorithms.
8. Motion pictures
Hollywood loves making movies about AI. Now it’s using AI to make and sell movies. There are AI systems that have been used to create movie preview trailers and even write screenplays. But the movie business might see an even bigger impact from AI systems that predict the likelihood that a given script will be a blockbuster. The system was trained using scripts and box office revenue data going back to the 1980’s. Given that just 20% of movies break even, there is a lot of room to improve the greenlighting process.
With more than 1 million books published each year—a figure up 400% from just 10 years ago—competition for readers’ attention is fierce. Data can help publishers make decisions about which books to publish, but the best-in-class reader analytics solutions can take up to 4 weeks to process data before providing actionable insights. A new generation of AI publishing systems is rewriting the rules, analyzing the text of books to predict reader engagement and sales performance.
You don’t have to do much more than read business headlines to grasp the impact AI is having on the semiconductor industry. Nvidia, until recently known for its graphics processors used in video games, is emerging as a leader in processors for AI number crunching. Google has launched its own AI-focused chip. The CPU king Intel is making acquisitions to catch up. Winners and losers TBD, but clearly the chip industry is being shaken up by the demand for AI processing power.
Taking a step back from the details, what we see in these ten examples are companies moving quickly to take advantage of the new capabilities artificial intelligence creates.