Growing demand for healthcare services, rising shortage of clinical resources, unequal access and unwarranted variation in care have contributed to high interest in the role of artificial intelligence (AI) in the healthcare sector. AI applications are being developed and piloted across the entire spectrum of the industry ranging from clinical diagnostics, treatment procedures (surgical robotics), personal health applications, population stratification and pharmaceutical research to hospital administration and workflows. However, most of the AI applications under development are quite narrow in their focus, having been designed for very specific tasks/decisions, using standardised data from limited sample sets. These AI applications inevitably fail when exposed to the real world. The challenges of unstructured, non-standardised data, diverse patient populations, varying processes and treatment protocols need to be resolved to enhance the potential of AI in healthcare. When it comes to successes of AI in healthcare, diagnostic imaging has so far shown the most promise. All of the 120 plus AI algorithms that have been approved by US Food and Drug Administration (as of June 2021) for use are related to diagnostic imaging. AI applications are increasingly becoming mainstream across radiology departments. Drug discovery has been another promising area with numerous companies witnessing varying levels of success. Moderna famously used AI technologies to speed up vaccine discovery and development for Covid-19. AI technologies developed by Google have been slowly replacing conventional drug discovery methods. Population health management, hospital operations management, personal health diagnostics are some other areas where AI is making inroads in the healthcare sector. Increasing penetration of wearables combined with the growing adoption of mobile health apps has the potential of putting the power of managing health in the hands of the consumer. The Middle East as a market presents a unique set of challenges and opportunities that need to be highlighted and addressed in the coming years if it means to fully unlock this potential. It will require an integrated approach across four primary dimensions, driven by the key stakeholders in the healthcare sector.

As CEO of Hitachi Vantara, Gajen helps solve clients' problems by bringing to bear Hitachi's unrivaled industrial expertise across sectors. You might not think saving the world's tropical rainforests is a data challenge, but the urgent task of protecting the last remaining two million square miles of forest is precisely that. What is more, the challenge holds vital lessons for anyone tackling a data project with seemingly insurmountable odds. Logging, much of it illegal, strips the planet of more than 32 million acres of natural forest every year. If you ever imagined literally trying to find a needle in a haystack, then you might be able to contemplate what it is like to find a chainsaw in forested areas the size of Australia.

President Xi Jinping's "Made in China 2025" strategy, unveiled in 2015 and now thrust back into the limelight by President Trump's bellicose stance on trade, holds three important lesson for global industry. This should be a non-controversial statement, but it is not. Economists often mock "the manufacturing fetish" and argue there is no reason to consider manufacturing a better driver of economic growth than any other sector. As economies get richer, they tend to shift from agriculture to industry, and then to services. Manufacturing accounted for nearly 30% of the U.S. economy in the 1950s; it was still 20% in the 1980s; today it accounts for just 11%.