AI Articles and Analysis about Generative AI

Making the Move to Saas in Financial Services-1x-min

Quantifying AI Risk – with Head of AI Insurance at Munich Re Michael Berger

As AI continues to reshape industries, calculating the ROI for AI initiatives remains a complex challenge. According to a study by MIT Sloan Management Review, only 10% of organizations report significant financial benefits from their AI investments despite the widespread adoption of AI tools and platforms.

Bringing Trust and Guardrails into Developing Enterprise AI Systems@2x

Bringing Trust and Guardrails into Developing Enterprise AI Systems – with Steve Jones of Capgemini

This interview analysis is sponsored by Capgemini 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.

Developing AI Solutions
for Work Marketplaces@2x-min

Developing AI Solutions for Work Marketplaces – with Andrew Rabinovich of Upwork and Tsavo Knott of Pieces

This interview analysis 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.

Driving Development Efficiencies for Saas, V.2-1x-min

Driving Development Efficiencies for Saas – with Akash Gupta of GreyOrange and Tsavo Knott of Pieces

This interview analysis 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.

Combining LLM Agents to Drive ROI in Business Workflows-2x

Combining LLM Agents to Drive ROI in Business Workflows – with Babak Hodjat at Cognizant

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.

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Artificial Intelligence at Lilly

Lilly and Company is a global pharmaceutical corporation founded in 1876 and headquartered in Indianapolis, Indiana. The company has offices in 18 countries and sells its products in approximately 125 countries worldwide. As of 2024, Lilly employs over 38,000 people globally and has an annual revenue of $34.12 billion. 

Driven Approaches 
to Infrastructure

Driving Patient Experiences Through Data Science-Driven Approaches to Infrastructure – with Xiong Liu of Novartis

Explainable AI models are essential in pharmaceutical R&D because they provide transparency and understanding of how AI-driven predictions are made. In drug discovery and development, stakeholders, including researchers, regulatory bodies, and healthcare professionals, need to trust and understand AI models' outputs to make informed decisions. Without explainability, AI models can be seen as "black boxes," leading to skepticism and reluctance to adopt these technologies in critical decision-making processes. 

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Artificial Intelligence at KeyBank

KeyBank is a financial services institution with a rich history dating back to 1825 and headquartered in Cleveland, Ohio. With 17,000 employees, operations across 15 states, and assets totaling $187 billion, KeyBank's commitment to innovation is evident in its strategic application of AI technologies to enhance both workforce management and customer service.