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Artificial intelligence (AI) plays a crucial role in the healthcare industry by helping doctors, patients and hospital administrators. Artificial Intelligence (AI) is defined as computing systems which are capable of performing tasks that humans are very good at, for example recognising objects, recognising and making sense of speech, and decision making in a constrained environment. For the purposes of this article, Machine Learning and Deep Learning (Deep Neural Networks) are defined as sub-branches of AI. See the Appendix for a more detailed explanation of these areas. Healthcare systems were already under a substantial strain before the arrival of the Covid-19 pandemic. This strain has only increased since the pandemic and may cause challenges that persist for many years. It takes many years and costly resources to train healthcare workers. Specialist medical practitioners tend to be in short supply and often work long hours.

It comes as no surprise that we, too, are shifting the way we approach healthcare. More and more, people are taking their health into their own hands through use of wearable technology and apps on their mobile device. Within the last year alone, according to the latest forecast from Gartner, worldwide end-user spending on wearable devices increased 18.1 percent from 2020. People are embracing technology for health and wellness more than ever. From leading successful healthcare ventures to being a sought-after speaker on innovative concepts and trends, Harry Glorikian understands the revolutionary potential artificial intelligence and data can have on healthcare and life sciences.

There is no greater challenge for healthcare and life science organizations than ensuring that their digital transformation along with better data management will improve patient outcomes, increase operational efficiency and productivity, and better financial results. The drivers of healthcare and life science's transition from data rich to data driven are not new and include the race to manage cost and improve quality. Some new drivers include the growth of at risk contracting for providers, the threat of care delivery disruption by the retail industry and the impact of drug discovery in the challenge to balance speed to market with costs. Health and life science industries are data rich. IDC estimates that on average, approximately 270 GB of healthcare and life science data will be created for every person in the world in 2020. Transformation of data into insights creates the value for health and life science organizations coupled with organizations establishing a data driven culture.

Leading Fortune 1000 companies have been organizing and analyzing their data to gain business insights for years. Traditional industries with a long history of capturing and managing their data, notably financial services, have decades of experience mining data to better service and grow their customer relationships and manage risk. During the past decade, as data volumes grew, and as new sources of data emerged, Big Data initiatives captured C-suite attention. Today, Fortune 1000 companies are managing exponentially greater volumes and sources of data, while leveraging emerging technology capabilities including machine learning and AI to gain ever more granular insights into market opportunities. Companies are leveraging computers to do the work that they once relied on humans to perform.

Artificial Intelligence (AI) can provide humans great relief from numerous repetitive tasks, with automation increasing productivity. Furthermore, AI powered machines and devices are fast and efficient: learning, predicting, and deciding with superhuman accuracy. Concurrently, the use cases for augmentative AI are expanding, with numerous industries and organizations looking to tap into the potential. This is clearly the situation in two key Healthcare and Life Sciences (HCLS) areas: neuroscience and radiology. In both areas, radiologists, MRI technicians and physicians must spend hours sifting through images, searching for markers and anomalies that may spur a disease diagnosis.

Specifically, 55 percent of business leaders in industrial manufacturing and 49 percent in retail and tech told KPMG that "AI is moving faster than it should in their industry." Moreover, these concerns are exceedingly pronounced within the section of leaders from small companies at 63 percent, leaders with high levels of AI knowledge at 51 percent and by Gen Z and Millennial business leaders at 51 percent. Notably, many business leaders with interest in AI implementation said COVID-19 has influenced their company's plans to adopt the technology and contributed to a quicker pace of adoption, including 53 percent from retail, 57 percent from tech, 72 percent from industrial manufacturing, and 37 percent from healthcare and life sciences. In fact, according to the survey 93 percent of leaders in industrial manufacturing, 84 percent in financial services, 83 percent in tech, 81 percent in retail, 77 percent in life sciences, 67 percent in health care and 61 percent in government, said AI is at least "moderately functional" in their organizations. Though 78 percent of retail business leaders said it is difficult to stay on top of the constantly evolving AI landscape -- expressing the sentiment more than leaders in other categories. Looking ahead, 53 percent of retail business leaders said they expect AI to have the greatest impact on customer intelligence, while 50 percent stated inventory management and 49 percent cited chatbots for customer service.

It's a living, changing entity that powers change throughout every industry across the globe. As it evolves, so do we all. Demands on your business are growing. Sometimes it's hard to see where your organisation should focus next. NVIDIA is here to support you.

Imagine what the world would be like if we could harness the multitude of data generated each day to catalyze positive change. What if we had the ability to predict and stop crimes before they happened, or could apply these same methodologies to save lives with better healthcare? With recent advances in artificial intelligence, these outcomes are not only possible, but an exciting reality! As we move swiftly into this new year, media, analysts and just about everyone is thinking about what will be'the next big thing' in technology. Looking back at 2017, this was a hallmark year for AI enthusiasm and awareness.

Data is the lifeblood of any business. And while advances in machine learning have been revolutionizing almost every industry, some have lagged behind due to technical constraints. Healthcare and life sciences rely on information, but when it comes to data, many professionals in this arena are stuck with legacy technologies when conducting their research. As John Brownstein, Director of the Computational Epidemiology Group at the Boston Children's Hospital put it, "We're missing the data, we're missing the realtime information, we're missing the forecasting methods. And we're missing the consumer tools that feed back to the patient to inform us about what's happening around us."