AI Articles and Analysis about Knowledge management

In 2020, we wrote about the early but fertile stage of AI development at Johnson and Johnson. Since then, the COVID-19 pandemic and improvements to machine learning have forced important changes in how J&J is using artificial intelligence. 

This interview analysis is sponsored by Aquant and was written, edited, and published in alignment with our Emerj sponsored content guidelines. Learn more about our thought leadership and content creation services on our Emerj Media Services page.

Business processes are defined in large part by the data within an organization. Value-driven data, by definition, represents higher-quality data. The importance of high-quality data cannot be overlooked. Research from MIT, even from before the pandemic AI boom, showed that insufficient data can cost as much as 25% of the revenue for most companies.

This article is sponsored by Pieces and was written, edited, and published in alignment with our Emerj sponsored content guidelines. Learn more about our thought leadership and content creation services on our Emerj Media Services page.

The applications of AI in the healthcare and life sciences industries are vast, with data-powered algorithms and analytics promising to upend the status quo. Applications, including the use of AI to interpret medical imaging, optimize drug discovery and development, analyze large-scale data sets to identify patterns among patient populations, and streamline provider workflows, are already transforming the industry. 

Over the last decade, public introductions of advanced technologies from big tech firms, such as Google Glasses and Meta's (then-Facebook) Metaverse platform, were met with infamous disappointment. In stark contrast, initial iterations of generative AI (GenAI) in large language models and other tools deployed across the global economy by smaller players like OpenAI in the last few years are having a far more lasting impact. A recent report from McKinsey noted that the staying power of GenAI could add $2.6 trillion to 4.4 trillion USD annually to the global economy.

Whether or not AI will replace humans depends on who you ask. Opinions vary, but part of the difficulty of answering the question has to do with the difficulty of quantifying what even counts as AI from a technology standpoint.

Far beyond surface-level 'chatbot' software, and other customer-facing support systems, the same generative AI (GenAI) capabilities having direct impacts across language workflows in front-office tasks in financial and legal services is also having a direct impact on how research teams in the life sciences space are targeting solutions for rare diseases and novel treatments.