Artificial intelligence (AI) is about to transform every segment of our economy by bringing human intelligence into computing and allowing machines to learn from experience and make human-like decisions. AI helps businesses automate routine tasks, better understand their customers by analyzing their behavior, reduce operational costs, and personalize experiences. After discussing the overall benefits and challenges of AI, today we look into how the new intelligent technologies shape and disrupt different industries.
Finance & Banking
As online transactions grow more popular every year, the finance and banking industry faces increasingly complex identity theft and fraud loss cases. AI can bring financial cybersecurity to the next level, as systems using deep learning technologies are able to analyze patterns and spot suspicious behavior and potential fraud.
- For instance, PayPal managed to reduce its fraud rate to just 0.32% of revenue using a sophisticated deep learning system that analyzes transactions in real time.
- Trading and investment management also makes use of AI, or more precisely machine learning—a subset of artificial intelligence.
- A machine learning (ML) application is basically a learning system that automates statistical model building. As a result of the new ML technologies, artificially intelligent hedge funds and robo-advisory platforms are on the rise. AI also helps everyday tasks of financial management, such as assessing credit quality or automating client interactions.
In healthcare, AI can provide tremendous help in analyzing complex medical data such as X-rays, CT scans, and different screenings and tests. Using the patient’s data and external knowledge sources such as clinical research, medical professionals can build a personalized treatment path for everyone.
Besides on-site clinical decision support, AI can also be used to provide real-time medical advice to patients.
- The Babylon AI doctor app uses speech recognition to consult with patients, checks their symptoms against a database, and offers them adequate treatments.
- Virtual nurses, such as Molly by Sense.ly, connects patients with clinical advice and services by using a proprietary classification engine that listens to the patient and delivers an adequate response.
- Finally, Microsoft’s Hanover project uses machine learning and natural language processing to make predictions about the most effective cancer drug treatment option for every patient, individually.
Artificial intelligence is probably the most widely-known for its application in the etail/retail industry. Conversation intelligence software helps companies interact with customers and follow up leads by analyzing and segmenting sales calls using speech recognition and natural language processing. Chatbots and virtual customer assistants allow retail companies to run a 24/7 customer service and answer basic questions without the involvement of human staff.
- Recommendation engines make use of machine learning and predictive analysis to provide personalized recommendations to each customer. Big e-commerce platforms such as Amazon make heavy use of recommender systems which boost their revenue at an impressive rate (about one third).
- Geo-targeted sales campaigns and price optimization such as the Darwin Pricing dynamic pricing software are also implementations of artificial intelligence worth watching. Darwin Pricing uses artificial neural networks to model price expectations at different locations, enabling retailers to offer geo-targeted discounts.
Technology companies don’t solely build AI solutions; they also utilize it. Moreover, tech giants such as Google, Apple, and IBM are known to acquire smaller AI companies to gain a competitive advantage.
As they frequently have products that can be hard to understand for the average layperson, chatbots and virtual customer assistants using speech recognition and natural language processing are indispensable for tech companies.
- Apart from chatbot platforms used by SMEs, market leaders have also built their own intelligent voice assistants such as Google Home, Apple’s Siri, and Microsoft’s Cortana. They use neural networks to analyze human language and return appropriate answers.
- AI-powered translation engines are a huge thing as well, as they revolutionize the field of communication. Skype offers real-time AI translations, and Google Translate uses a unique machine translation system to provide the most accurate translation between any two languages.
- Face and image recognition systems are also heavily researched and used, especially by big social media players such as Facebook.
There are countless implementations of AI in the tech industry, and its prevalence continues to rise.
Artificial intelligence is also about to disrupt the field of higher education. Most importantly, it makes possible personalized learning that tailors educational content to the needs of each individual student. Data analytics help implement adaptive learning programs by allowing educators to collect and analyze data about the performance and learning style of each student and constantly adjust the learning material according to their progress.
- Oregon State University already uses adaptive learning technologies to personalize their hardest courses that come with the highest attrition rates.
- Northern Arizona University has also begun to implement the method university-wide, and DFW rates (D-grades, F-grades or withdrawals) have already decreased from 23 to 19 percent.
- Machine learning can also be used to give immediate feedback on students’ writing assignments. The University of Michigan makes use of an automated text analysis (ATA) program that reviews writing submissions, identifies the strengths and weaknesses of every student, and recommend revisions to them.
Energy & Utilities
Although artificial intelligence is still in the early stage of implementation in the energy & utility industry, companies in the sector have already begun to invest in the new technology. Big data and artificial intelligence deals in the energy industry went up tenfold just in 2017. Generally, industry leaders expect AI to make energy systems cleaner, more affordable and reliable.
- The most popular implementations to watch out for are intelligent energy forecasts, data analytics for managing intermittent renewable generation, and self-healing digital grids.
- Deep learning algorithms are also expected to be used to analyze patterns in order to identify the vulnerabilities of power grids. For instance, a promising new project led by the Department of Energy’s SLAC National Accelerator Laboratory intends to use AI to prevent or minimize electric grid failures by installing an autonomous grid that quickly responds to disruptive events.
Currently, we are at the dawn of the Fourth Industrial Revolution (4IR). Artificial intelligence, machine learning, data analytics, automation, and deep learning systems revolutionize each and every industry and mean incredible opportunities for businesses. Governments, tech giants, universities have already entered the game. Companies making use of the new technologies can gain huge competitive advantages, boost their bottom line, and can become even market leaders in their respective sectors.
Is your company leveraging AI to gain a competitive advantage? What examples of AI have you noticed in your daily interactions with leading enterprises?
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