- 21st May 2019
- Posted by: Manolis
- Category: algorithms, Artificial intelligence, machine learning, robotics
Technology is a transformative force, and there is currently no technology more transformative than AI. Because AI encompasses so many different fields — from robotics to deep learning to self-driving cars — it can be hard to quantify the exact impact it has had on the economy and on individual industries.
Whether you’re heavily involved within the industry or an outside observer, by examining the different use cases and successes (or failures) that AI has been a part of, you can gain a better understanding of how to implement AI within your own organization, and how to generate the most value from it.
Here is a closer look at five industries that have been affected the most by artificial intelligence:
1. Health Care
Given the lucrative opportunities available, it is unsurprising that both established players in the health care industry (i.e., hospitals, pharmaceutical companies, insurers, etc.) and startups are looking to utilize AI to maximize their impact. A 2018 report revealed that health care-focused AI startups alone have raised $4.3 billion since 2013, more than startups in any other industry.
Moreover, AI is already impacting the health care industry in ways big and small. Health care professionals can use AI to automate basic administrative tasks, such as analyzing paperwork, transcribing patient notes and sending out prescriptions. But a handful of companies are also focused on the doctor-patient relationship, allowing patients to communicate their symptoms to a chatbot, book doctors appointments and conduct regular (virtual) check-ins with their medical providers.
The processing power of neural networks and other AI algorithms allows insurance companies to analyze huge amounts of data and better understand the lives of their clients. This, in turn, gives those companies the ability to craft plans and pricing models that are better attuned to their customers’ needs.
A report by McKinsey notes that the “avalanche of new data created” by smart devices (i.e., phones, Fitbits, smart lamps, etc.) could give carriers a way to provide personalized services, potentially with updates in real time. The example that McKinsey gives is of a wearable linked to a database that updates a consumer’s personal risk score based on their activities over the course of the day and personal risk factors. This is not particularly far-fetched — some auto insurance companies are actually using data from smartphones to help calculate insurance quotes and rates.
Thanks to the rapid growth of the digital landscape, marketing is an industry in the midst of significant transformation. Not only do marketers use more technology now than ever before for automation and better results, but there’s also a new emphasis on data and accountability, as brands want to ensure their money is being spent in the right places.
For example, there are now tools that utilize AI and deep learning to match brands with the right influencers. In addition to reducing the amount of time brands have to spend researching partnerships, this also helps them better amplify their messaging. Another innovation includes tools that use machine learning to personalize advertising content, ensuring that it remains relevant and engaging to those who see it.
Sure, everybody knows about self-driving cars and their potential to transform the way we live, shop and travel. But AI has more applications in the automotive industry than that. For example, without going all the way into autonomous territory, auto manufacturers can include AI as a safety feature, capable of monitoring information from multiple sensors and alerting the driver in dangerous situations. Many cars now have emergency braking, blind-spot monitoring and other features that allow the car to take over briefly and prevent accidents from occurring.
As mentioned earlier, there are companies out there that use AI to customize quotes for car insurance by collecting data as individuals drive. Some automotive manufacturers use AI and deep-learning algorithms to better predict customer demand and determine how many vehicles they should be manufacturing, as well as how many parts they should have on hand at any given moment. Still, others have used advances in robotics to make their factories more advanced and efficient.
According to some estimates, adopting AI will save financial institutions more than $1 trillion by 2030. While a lot of these savings will come from automation, banks will also save billions of dollars by using AI to combat fraud, ensure compliance, manage risk and process data.
In fact, millions of employees working for U.S. financial institutions are already using AI in some way, shape or form. Hedge funds are using AI to crunch huge amounts of data and finetune their predictive models, while banks are turning to chatbots to manage customer queries and image recognition to allow people to deposit checks from their mobile phones.
There are countless other industries currently being impacted by AI — from manufacturing to agriculture to retail. To explore the complete effects of the technology would take up much more space than this one here, but suffice it to say that they will be felt for a long time.