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The use of artificial intelligence in business is showing signs of acceleration. Nearly three-quarters of companies are now using AI (31%) or are exploring the use of AI (43%), according to IBM's "2021 Global AI Adoption Index."

IT professionals responding to the IBM survey cited changing business needs in the wake of the pandemic as a driving factor in the adoption of AI at their companies. Indeed, 43% said their companies have accelerated AI rollouts as a result of the pandemic.

Advances in AI tools have made artificial intelligence more accessible for companies, according to survey respondents. They listed data security, process automation and customer care as top areas where their companies were applying AI. Natural language processing (NLP) is at the forefront of AI adoption, the report found: Over half of businesses are using applications with NLP.

Business leaders, IT managers, executive advisors, analysts and AI experts interviewed for this article said they're not surprised by the expansion of AI in the enterprise. AI can significantly lower costs, increase efficiency and boost productivity as well as create avenues into new products, services and markets, they said.

Here are nine top applications of artificial intelligence in business and the benefits that AI brings. This is followed by a section on industry-specific AI use cases.

One of the most common enterprise use cases for AI centers around customer experience, service and support.

"The uses for AI that are really first and foremost in organizations are customer-facing types of things," said Seth Earley, author of The AI-Powered Enterprise and founder and CEO of Earley Information Science.

Chatbots, for example, use both machine learning algorithms and NLP to understand customer requests and respond appropriately. And they do that faster than human workers can and at lower costs.

AI also powers recommendation functions, which use customer data and predictive analytics to suggest products that customers are most likely to need or want and therefore buy.

Intelligent systems can help employees better serve customers, too, drawing on analytics similar to the ones used in chatbots and recommendation engines to give workers suggestions as they tend to customers.

"The system can propose next-best actions, how to take discussions with the customer further and how to present a certain targeted option," explained Alex Linden, an analyst and research vice president with Gartner who specializes in data science, machine learning and advanced algorithms.

Online search providers, online retailers and other internet entities use intelligent systems to understand users and their buying patterns, so they can select advertisements for the specific products that they're most likely to want or need.

"Every advertisement [on the internet] is placed by machines, and it's designed to optimize click-through rates," Linden said.

AI also helps businesses deliver targeted marketing in the real world, too. Some organizations have started combining intelligent technologies, including facial recognition and geospatial software along with analytics, using the technologies to first identify customers and then promote products, services or sales designed to match their personal preferences.

Organizations across industries are using AI to improve management of their supply chains. They're using machine learning algorithms to forecast what will be needed when as well as the optimal time to move supplies.

In this use case, AI helps business leaders create more efficient, cost-effective supply chains by minimizing and even possibly eliminating overstocking and the risk of running short on in-demand products.

Gartner, the tech research and advisory firm, predicted that 50% of supply chain organizations will invest in applications that support AI and advanced analytics capabilities between 2020 and 2024.

As developers of business process applications build AI-enabled capabilities into their software products, AI is becoming embedded across the enterprise.

"There is AI in all the functions that support the business, like human resources, finance and legal," said Beena Ammanath, executive director of Deloitte AI Institute. "The [software] itself is using AI, and the team members may be using the tool and might not even know that AI is being used in a way that's enabling their function."

AI, for example, can handle many customer requests; it can route customer calls not just to available workers but to those best suited to handle the specific needs.

Meanwhile, retailers are using AI for intelligent store design, optimized product selection and in-store activities monitoring. Some are using AI to monitor inventory on shelves in various ways, including for the freshness of perishable goods.

AI is also impacting IT operations. For example, some intelligence software applications identify anomalies that indicate hacking activities and ransomware attacks, while other AI-infused solutions offer self-healing capabilities for infrastructure problems.

AI is being used by a multitude of industries to improve safety.

Construction companies, utilities, farms, mining interests and other entities working on-site in outside locales or in spacious geographical areas are gathering data from endpoint devices such as cameras, thermometers, motion detectors and weather sensors. Organizations can then feed that data into intelligent systems that identify problematic behaviors, dangerous conditions or business opportunities and can then make recommendations or even take preventative or corrective actions.

Other industries are making similar use of AI-enabled software applications to monitor safety conditions. For example, manufacturers are using AI software and computer vision to monitor workers' behaviors to ensure they're following safety protocols.

Similarly, organizations of all kinds can use AI to process data gathered from on-site IoT ecosystems to monitor facilities or workers. In such cases, the intelligent systems watch for and alert companies to hazardous conditions -- such as distracted driving in delivery trucks.

Manufacturers have been using machine vision, a form of AI, for decades. However, they're now advancing such uses by adding quality control software with deep learning capabilities to improve the speed and accuracy of their quality control functions while keeping costs in check.

These systems are delivering a more precise, and ever-improving, quality assurance function, as deep learning models create their own rules to determine what defines quality.

Businesses are also using AI for contextual understanding. Linden pointed to the insurance industry's use of monitoring technologies to offer safe driving discounts as a case in point. AI is used in processing data about driving behavior to predict whether it is low or high risk. For example, driving 65 miles per hour is safe on a highway but not through an urban neighborhood; intelligence is needed to understand and report when and where fast driving is acceptable or not.

"Classifying the risk is to some extent AI," Linden explained.

AI is used in a similar manner in the emerging area of usage-based prices, he said. Turning again to the insurance industry as an example, he said providers could use AI to customize rates beyond the typical parameters of annual mileage and place of registration by understanding when, how and where -- perhaps even down to street level -- a vehicle is being driven

Optimization is another use case for AI that stretches across industries and business functions. AI-based business applications can use algorithms and modeling to turn data into actionable insights on how organizations can optimize a range of functions and business processes -- from worker schedules to production product pricing.

AI's potential impact on education is significant, with many organizations already using or exploring intelligence software to improve how people learn.

"There are so many ways that AI can be used to make learning better," Ammanath said, noting that use of AI in this space is still in its early stages. "This is the one area we will definitely see evolve over the next couple of years."

Ammanath said intelligent tools can be used to customize educational plans to each student's unique learning needs and understanding levels. Businesses, too, can benefit from AI-infused training software to upskill workers.

Although many AI applications span industry sectors, other use cases are specific to individual industry needs. Here are some examples:

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9 top applications of artificial intelligence in business - TechTarget

Newswise June 30, 2021 For most patients, the reasons for having a facelift are simple: to "turn back the clock" for a younger and more attractive appearance. Even during the pandemic year 2020, more than 234,000 patients underwent facelift surgery, according to American Society of Plastic Surgeons (ASPS) statistics.

When considering facelift surgery, patients may ask, "How much younger will I look?" For plastic surgeons, that has been a difficult question to answer. Typically, the cosmetic outcomes of facelifting have been judged on a case-by-case basis, or with the use of subjective ratings.

Now research suggests a new, objective approach to assessing the reduction in apparent age after facelift surgery: artificial intelligence (AI) networks trained to estimate age based on facial photos. "Our study shows that currently available AI algorithms can recognize the success of facelifting, and even put a number on the reduction in years of perceived age," comments senior author James P. Bradley, MD, Vice Chairman of Surgery, Zucker School of Medicine at Hofstra/Northwell. The study is published in the July issue of Plastic and Reconstructive Surgery, the official medical journal of the ASPS.

The study used a type of AI algorithm called convolutional neural networks. "By training on datasets containing millions of public images, these neural networks can learn to discern facial features with much higher 'experience' than a typical person," Dr. Bradley explains.

Four different, publicly available neural networks were used to make objective age estimates of facial age for 50 patients who underwent facelifting. The AI estimates were made using standardized photos taken before and at least one year after facelift surgery. The results were compared with patients' subjective ratings of their appearance, along with responses to a standard patient-rated evaluation (FACE-Q questionnaire).

The patients were all women, average age 58.7 years. The AI algorithms used in the study were 100 percent accurate in identifying the patients' age, based on "before" photos.

In the "after" photos, the neural networks recognized a 4.3-year reduction in age after facelift surgery. That was substantially less than the 6.7-year reduction, as rated by patients themselves. "Patients may tend to overestimate how much younger they look after facelift surgery perhaps reflecting their emotional and financial investment in the procedure," Dr. Bradley comments.

On the FACE-Q questionnaire, patients were highly satisfied with the results of their facelift surgery: average scores (on a 0-to-100 scale) were 75 for facial appearance and over 80 for quality of life. Neural network estimates of age reduction were directly correlated with patient satisfaction. "The younger the AI program perceives a patient's age, the greater their satisfaction with the results of their facelift," says Dr. Bradley.

Artificial intelligence algorithms can provide an objective and reliable estimate of the apparent reduction in age after facelift surgery, the new findings suggest. These age estimates also seem to provide an indicator of patient satisfaction scores even if the reduction in years doesn't quite match the patient's own subjective rating.

"Together with powerful image analysis tools used in modern plastic surgery, neural networks may play a useful role in counseling patients and demonstrating successful results of facial rejuvenation procedures," Dr. Bradley adds. "We think that AI algorithms could also play a useful role for plastic surgeons in assessing their own results and comparing the outcomes of different techniques."

Click here to read Turning Back the Clock: Artificial Intelligence Recognition of Age Reduction after Face-Lift Surgery Correlates with Patient Satisfaction.

DOI: 10.1097/PRS.0000000000008020

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Plastic and Reconstructive Surgery is published in the Lippincott portfolio by Wolters Kluwer.

About Plastic and Reconstructive Surgery

For over 75 years, Plastic and Reconstructive Surgery (http://www.prsjournal.com/) has been the one consistently excellent reference for every specialist who uses plastic surgery techniques or works in conjunction with a plastic surgeon. The official journal of the American Society of Plastic Surgeons, Plastic and Reconstructive Surgery brings subscribers up-to-the-minute reports on the latest techniques and follow-up for all areas of plastic and reconstructive surgery, including breast reconstruction, experimental studies, maxillofacial reconstruction, hand and microsurgery, burn repair and cosmetic surgery, as well as news on medico-legal issues.

About ASPS

The American Society of Plastic Surgeons is the largest organization of board-certified plastic surgeons in the world. Representing more than 7,000 physician members, the society is recognized as a leading authority and information source on cosmetic and reconstructive plastic surgery. ASPS comprises more than 94 percent of all board-certified plastic surgeons in the United States. Founded in 1931, the society represents physicians certified by The American Board of Plastic Surgery or The Royal College of Physicians and Surgeons of Canada.

About Wolters Kluwer

Wolters Kluwer (WKL) is a global leader in professional information, software solutions, and services for the clinicians, nurses, accountants, lawyers, and tax, finance, audit, risk, compliance, and regulatory sectors. We help our customers make critical decisions every day by providing expert solutions that combine deep domain knowledge with advanced technology and services.

Wolters Kluwer reported 2020 annual revenues of 4.6 billion. The group serves customers in over 180 countries, maintains operations in over 40 countries, and employs approximately 19,200 people worldwide. The company is headquartered in Alphen aan den Rijn, the Netherlands.

Wolters Kluwer provides trusted clinical technology and evidence-based solutions that engage clinicians, patients, researchers and students in effective decision-making and outcomes across healthcare. We support clinical effectiveness, learning and research, clinical surveillance and compliance, as well as data solutions. For more information about our solutions, visit https://www.wolterskluwer.com/en/health and follow us on LinkedIn and Twitter @WKHealth.

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Original post:
Did your Plastic Surgeon Really Turn Back the Clock? Artificial Intelligence May Be Able to Quantify How Young You Actually Look After Facelift...