AI Articles and Analysis about Natural Language Processing

One of the key strategies for future-proofing an organization is recognizing the limits of AI models and filtering out the misconceptions that AI is a one-solution-fixes-all narrative for businesses. Enterprises build an AI strategy supported by use cases and how LLMs can change the workforce going forward.

AstraZeneca is a global biopharmaceutical company that researches, develops, manufactures, and markets prescription drugs and vaccines. Its key therapeutic areas include oncology, cardiovascular, renal, metabolism, respiratory, and immunology. In 2022, the company reported revenue of $42.67 billion and a profit of $4.08 billion. The company has a significant global presence, employing around 89,900 people across more than 60 countries as of 2023.

The asset management industry is going through several challenges, like the prolonged low-interest rate environment, dwindling margins, increased cost pressures, and squeezed profitability. Meanwhile, exponential growth in data volumes has overwhelmed legacy data management systems and analytical tools, making it tiring to process and extract valuable insights from the deluge of information. 

This article is sponsored by NLP Logix 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.

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. 

As new generative AI use cases continue to reshape the enterprise landscape across the global economy, many sectors are still weathering significant risks to keep pace with the adoption hype. Deloitte's "State of Generative AI in the Enterprise 2024" report found that 79% of respondents expect generative AI to transform their organizations within three years. However, companies must approach these investments cautiously with a focus on responsible implementation. 

Deploying large language models (LLMs) in an enterprise setting requires management teams to adopt a strategic approach tailor-made for their organizations, which research consistently shows must consider various essential factors. 

This interview analysis is sponsored by Deloitte 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.