In this series, we are looking at the interrelationship between artificial intelligence and digital marketing. Last week, we looked at what artificial intelligence is all about, the technologies driving it, and its applications in some industries.
This week, we look at the specific ways AI is changing the world.
One of the significant impacts of AI is the increasing capacity for personalization. For example, in the field of customer service, the use of AI technology can help an organization keep track of all the previous engagements and interactions with a particular customer. Consequently, the organization can have a more personalized interaction with every customer.
AI is helping marketers to achieve more personalization in the content and product offerings they offer to customers. Many ad platforms also help marketers deliver personalized ads to their target audience. Marketers can deliver personalized emails. The extent of personalization includes the day and time of day that will lead to the best open rates. Search engines can offer recommendations to each user based on all their previous searches and internet usage. This is what Google does with Discover. Social media platforms like Facebook also use AI to offer more personalized news feeds for users. Amazon also uses AI for their kindle platform.
In finance, organizations are using AI (robo-advisers) to help clients develop a personalized investment portfolio.
Medicine is another area where AI is helping to achieve more personalization. AI is empowering the development of virtual nurturing assistance that gives medical advice to patients based on their medical records and history. Rather than endless visitation and readmission, every patient can receive personalized medical advice, response to inquiries, explanations of medications usage, etc.
The use of AI in manufacturing is leading to increased productivity. Research by Accenture shows that AI increases productivity by 40% or more and profitability by 38%. Machines are not subject to some of the limitations we have as humans. Therefore, the input-output process is more streamlined, leading to higher productivity. According to Taarini Kaur Dang, “Unlike human labor that can be very limited, artificial intelligence provides more input with a corresponding positive output – on average. The technology can achieve this through the use of innovative diffusion, apt and proactive decision implementations, and other roadmaps that ultimately jerks up positive output.”
Similar to the point is that AI helps achieve greater accuracy. Stress can lead to poor judgment from humans. These poor judgments can lead to inefficiencies and inaccuracies. AI helps to remove this limitation.
In medicine, for example, hospitals can achieve a more accurate medical diagnosis. AI-empowered devices give a more accurate diagnosis and help prevent cases where medical experts make incorrect judgments. In finance, they help make objective and precise investment portfolios for users by taking the emotion out of investing. Similarly, banks use AI-empowered technology to evaluate loan applicants. This technology analyzes more than the credit score of applicants. It considers many data to offer a more accurate decision.
One of the apparent advantages of AI in the business environment is the replacement of mundane human tasks with machines. There are many repetitive and mundane tasks in the average workplace. Typically, humans bury themselves in these tasks. Apart from the lack of creativity, they waste considerable time that they could use in other endeavors. AI-empowered machines take over these tasks and free up humans to do more creative and analytical activities.
Reduction in Operational Costs
AI can help organizations significantly reduce operational costs. For example, the use of medical imaging devices can help to reduce the cost of medical diagnosis. Writing on the use of medical imaging to detect lymph nodes, Darrell West and John Allen commented, “Humans can do this, but radiologists charge $100 per hour and may be able to carefully read only four images an hour. If there were 10,000 images, the cost of this process would be $250,000, which is prohibitively expensive if done by humans. What deep learning can do in this situation is train computers on data sets to learn what a normal looking versus an irregular-appearing lymph node is. After doing that through imaging exercises and honing the accuracy of the labeling, radiological imaging specialists can apply this knowledge to actual patients and determine the extent to which someone is at risk of cancerous lymph nodes”
Using AI, Netflix saved about $1billion in 2017. Organizations will have lower human labor costs as they use machines to replace the mundane and repetitive tasks otherwise performed by humans.
One area where AI is seriously making inroad is transportation. Companies are focusing on the development of self-driving cars and trucks. These cars are not only self-driving; they are self-healing, self-learning, and self-socializing. Tesla is one of the companies investing in these projects.
However, there have been some setbacks in this particular industry, and these cars and trucks are still in the works. Nevertheless, when these cars hit the road, they will improve efficiency on the roads. As Darrel West and John Allen pointed out, “Autonomous vehicles—cars, trucks, buses, and drone delivery systems—use advanced technological capabilities. Those features include automated vehicle guidance and braking, lane-changing systems, the use of cameras and sensors for collision avoidance, the use of AI to analyze information in real-time, and the use of high-performance computing and deep learning systems to adapt to new circumstances through detailed maps.” Self-driving cars can reduce accidents on the road (90% of accidents result from human error), minimize traffic, and reduce the pollution on the roads.
AI is improving health care accessibility. With wearables, many more people can have access to essential data about their health. Virtual nursing assistants are also helping many more people access essential healthcare without going to a hospital. There are current attempts to fine-tune the image capturing power of smartphones so they can function as diagnostic tools.
The use of AI, in combination with IoT and big data, is helping in predictive analysis and forecasting. With Electronic Health Records, medical experts can forecast or predict potential health risks of patients. Organizations are also increasing their capacity to make data-based recommendations. The use of IoT sensors also enables companies to carry out predictive analytics. Kayla Mathews explains how this works, “When a business has access to large amounts of accurate data, it can use predictive analytics to make better decisions. IoT sensors can provide quality information at volumes that have never been possible before — allowing businesses to improve their ability to forecast the future significantly”
The importance of AI for forecasting is vast. As Geoff Birnes puts it, “A company with intelligent forecasting sees all of that same data but goes further. Their ML will analyze their past opportunities, successes, misses, win rates and other criteria to create a recommended forecast and provide insights to help their sales team take action. Intelligent forecasting is more than making predictions on revenue or deals closed. It is transparent and explanatory, which informs workflows, helps improve sales strategies and opens the door to increasing win rates.”
The use of computer vision can help achieve better accountability. Mike Thomas observing how this works in IFM, made this comment – “Employing machine learning and computer vision for detection and classification of various “safety events,” the shoebox-sized device doesn’t see all, but it sees plenty. Like which way the driver is looking as he operates the vehicle, how fast he is driving, where he is driving, locations of the people around him and how other forklift operators are maneuvering their vehicles. IFM’s software automatically detects safety violations (for example, cell phone use) and notifies warehouse managers so they can take immediate action. The main goals are to prevent accidents and increase efficiency. The mere knowledge that one of IFM’s devices is watching, Gyongyosi claims, has had “a huge effect.””
Government agencies also use AI to improve the results they get from surveillance. By analyzing surveillance data, the defense agency can identify abnormal or suspicious activities in a particular location of interest. This allows them to prepare ahead for situations that may arise.
In finance, companies also use AI to detect when some key metrics are going overboard due to possible fraudulent activities. This risk management system helps them to identify potential fraudulent practices. Cybersecurity agencies also use the same risk management system to identify cyber threats.
AI is making inroads into every industry. If current trends continue, what we have may not even compare to what is coming. In the next article, we will look specifically at the effects of Ai in digital marketing.