Nov 28, 2018 
In order to get the most out of new technologies that use AI and machine learning, we must start envisioning the possible new use cases across industries that can be supported with future smart engineering.
Artificial intelligence is poised to lead the next business revolution in many industries from finance and healthcare to energy, agriculture and cybersecurity. A recent McKinsey study found that in 2017, tech giants spent close to USD 30 billion on AI research and development and another USD 10 billion on acquisitions of AI companies. The US has the lead in AI research, but China is catching up. For example, internet giants Baidu, Alibaba and Tencent are investing heavily in AI research and hiring top data scientists.
Expanding Use Cases to Diverse Industries
A new technology is only as ground-breaking as the use cases we discover for it. Right now, we are still in that discovery phase for AI, as industries across the board are looking for new cutting edge use cases for AI, automation and machine learning. Here’s a few we’re starting to see:
Detecting traffic violations. In many countries, cameras are installed in urban areas that monitor traffic flow and read vehicle license plate numbers. Using AI to analyze the data, cities can detect traffic violations and issue tickets.
Autonomous driving. It has been estimated that nearly 1.25 million people worldwide die in road accidents every year.[B1] Of these fatal accidents, 90% are due to human error.[B2] Self-driving cars can prevent human errors by letting the cars communicate with one another and with roadside infrastructure to form a collective experience of millions of cars, which can lead to safer roads.[A4] For example, Intel is collaborating with Waymo—a Google-owned vehicle manufacturer-to develop autonomous cars.[A1] Similarly, NVIDIA is developing graphics processing units (GPUs) with AI capabilities for autonomously cars.[A2, A3] These cars will use sensors to observe road conditions, make decisions about driving and network with other cars or base stations to enhance the driving experience.
Understanding web-user behavior. The number of web users globally has grown tremendously in the last decade. However, most websites are unable to derive insights about user behavior from these visits. Recently, some startups have begun to use AI to understand user-intent based on the users’ web-crawling behaviors.[B4] For example, Fashion to Figure, a leading fashion design company, uses AI to provide individualized product recommendations to users on its homepage, category pages and product pages.
AI in the banking sector. AI tools can analyze credit default patterns of customers and recommend steps to lower the default rate by increasing or decreasing interest rates. Such recommendations can be highly useful in reducing gross non-performing assets.
Retail sector. AI-based analytics and natural language processing (NLP) programs can provide senior decision makers with valuable business insights. For example, AI can give senior managers detailed performance analytics for any market-segment, brand or demographic. The tool can even analyze the company’s social network and build a perception model. From there, management can make adjustments to increase the acceptability of the company’s products in the market, which can boost sales.
Military and defense sector. The defense industry is integrating AI into robots for military applications. For example, the deployment of autonomous vehicles for detecting anti-ship mines, monitoring coastal waters and making precision air strikes on evasive targets. [B7] The Indian armed forces, for example, is deploying robots that function as a team, similar to soldiers. These robots can do many tasks and work in a variety of environments both indoor and outdoor including in mountains, deserts and both rural and urban settings. [B7]
For any of these use cases to truly reach mass adoption, organizations and enterprises need to start with the right infrastructure for machine learning and automation powered by AI. Altran is the partner of choice when it comes to helping organizations build the groundwork for innovative new AI use cases.
Our future smart engineering AI experts are ready to help your company build for intelligence.
References:
[A1] https://newsroom.intel.com/editorials/waymo-intel-announce-collaboration-driverless-car-technology/
[A2] https://seekingalpha.com/article/4127814-nvidia-future-gaming-ai-self-driving-cars
[A3] https://www.investopedia.com/news/how-selfdriving-cars-will-boost-nvidias-stock/
[A4] https://connect.altran.com/2018/05/connected-vehicles-in-lte-and-beyond/
[B1] http://www.who.int/mediacentre/factsheets/fs358/en/
[B2] https://crashstats.nhtsa.dot.gov/Api/Public/ViewPublication/811059 and http://cyberlaw.stanford.edu/blog/2013/12/human-error-cause-vehicle-crashes
[B3] https://www.investors.com/news/technology/ai-technology-u-s-chip-stocks-vs-china/
[B4] https://yourstory.com/2017/10/reflektion-uses-ai-tech-allow-businesses-leverage-customer-intent/
