Enterprises across the globe are starting to realize the value of artificial intelligence and this is mirrored in the ASEAN region with AI adoption rates steadily on the rise. The current adoption rate has almost doubled from last year, highlighting a significant drive from organizations to implement AI in their operations. However, amidst the optimism, many businesses still have concerns.

“Singapore’s organizations are holding back significantly with the national adoption rate at only 9.9%,” said Jason Loh, Head of Analytics Asia Pacific at SAS, in an interview with Networks Asia. “This is largely because there are still concerns over AI technology putting human jobs at risk. Organizations need to understand that AI is different from hardware-driven, robotic automation and it doesn’t just remove manual processes.”

In the interview with NWA, Loh talks about the differences between IoT, AI and ML; as well as the critical things organizations should understand in today’s AI age.

Loh also discussed some of the key benefits businesses can reap from using SAS’ cloud platform.

We’ve seen the videos of robots working in warehouses. How far are we from the machine revolution? Do enterprises understand what is needed to successfully implement AI? What are some critical things that organizations should understand in today’s AI age?

AI is the science of training systems to emulate human tasks through learning and automation. Using AI, computers can be trained to accomplish specific tasks by processing large amounts of data and recognizing patterns in the data. Today, we are seeing more and more machines that can probe complex data to learn and perfect specific tasks. It is important to remember that a majority of the best AI systems today are built for highly specialized problem solving. For example, an AI system that detects health care fraud cannot be used in tax fraud or warranty claim fraud contexts.

Enterprises across the globe are starting to realize the value of AI and this is mirrored in the ASEAN region with AI adoption rates steadily on the rise. The current adoption rate has almost doubled from last year, highlighting a significant drive from organizations to implement AI in their operations. However, amidst the optimism, many businesses still have concerns.

A recent study by IDC found that Singapore’s organizations are holding back significantly with the national adoption rate at only 9.9%. This is largely because there are still concerns over AI technology putting human jobs at risk. Organizations need to understand that AI is different from hardware-driven, robotic automation and it doesn’t just remove manual processes. AI machines have the capability to intelligently automate tasks that augment human capabilities, allowing humans to solve more complex problems at speeds that would not be humanly possible. In today’s contexts, AI systems are designed to analyze high-volumes of data and deliver informed recommendations to humans. Examples of these include the detection of different forms of cancer on medical images.

With the growth of AI applications across industries, new jobs that require AI-related skills will also emerge. AI, Machine Learning (ML) and IoT all have a common denominator – data analytics. Organizations need to take on the responsibility of ensuring that employees, regardless of age and experience, continues to upskill and acquire knowledge on data analytics. Business leaders need to provide an additional layer of support by enforcing collaboration in analytics and breaking down silos across departments. In today’s economy, access to this technology cannot be the sole privilege of those trained in data science. Access to analytics of any complexity is a basic right.