Execs Remain Competitive with Emerging Tech

Emerging technologies like artificial intelligence (AI), machine learning and deep learning, are essential for organizations, including healthcare, to stay competitive, according to a new report.

According to the 2019 RELX Emerging Tech Executive Report, the perception of AI technologies also shifted among business leaders in various industries-use of AI has jumped from 48% in 2018 to 72% in 2019.

The study was conducted to analyze and identify how executives in across multiple industries in the U.S. use and view AI technologies including machine learning and deep learning. To do this, RELX surveyed over 1,000 U.S. senior executives across seven industries: government, healthcare, insurance, legal, science/medical, banking, and agriculture.

“Additionally, over half (54%) of the executives surveyed reported that AI technology is helping their team optimize systems and reduce costs-although the survey cites budget constraints as the most commonly cited reason for not using AI. Less reported reasons include lack of technical expertise, unproven ROI and lack of C-suite or Board buy-in,” says Vijay Raghavan, executive director of the Chief Technology Officer Forum at RELX, a global provider of information-based analytics and decision tools for professional and business customers.

Related: Novartis, Microsoft Aim to Transform Medicine with AI

Additional highlights from the survey include:

• Ninety-three percent of U.S. business leaders believe emerging technologies have a positive impact within their industry, compared to 69% last year.

• Over half (54%) of executives surveyed responded that AI technology is optimizing systems and reducing cost.

• The survey shows that 64% of businesses expanded the areas of their business touched by AI in the last year.

• Ninety-three percent of respondents say that emerging technologies, including deep learning, machine learning and artificial intelligence, help their businesses be more competitive.

• A vast majority (93%) believe that U.S. companies should invest in the future artificial intelligence workforce through educational initiatives such as university partnerships.

The survey shows that 60% of healthcare executives reported expansion of their business was due to AI technologies. And, 92%of healthcare executives surveyed believe emerging technologies have a positive impact on care delivery, population health, and treatment pathways.

Across all seven of the industries evaluated, the science/medical industry reported emerging technologies to have the greatest impact on efficiencies or worker productivity. Similarly, the science and medical industry reported the highest increase of AI utilization than any other industry surveyed, with 69% of science/medical executives reporting an expansion in their areas of the business touched by AI technologies.

“As we continue to learn more on the impact of AI and how it is helping reshape healthcare as we know it, one thing is clear: AI is a key differentiator in helping to improve and develop products, treatments and technologies that support better outcomes for patients,” Raghavan says.

According to Raghavan, AI technologies, including deep learning and machine learning, are developing rapidly and being applied to new use cases, affecting everything from business strategy to product design and operations. “The survey results highlight the need for U.S. businesses to be agile and flexible in the way they use AI technologies. Emerging technologies have the capabilities to be incredibly powerful tools, enabling businesses to remain competitive and achieve business goals. Companies with AI integration can offer better products and services and those who don’t risk becoming obsolete," he says

“Without a doubt, AI can help in many areas of healthcare. From our perspective, it is critically important to focus first on the problems we are solving in healthcare and then think about if and how AI might be part of the solution," says Richard Loomis, MD, chief informatics officer, Clinical Solutions, Elsevier. We have seen some notable failures of AI in healthcare when attempting to start first with the solution. For example, instead of attempting to “replace the radiologist” with AI-based image recognition, use AI to prioritize a radiologist’s queue to move studies with critical findings to the top.”