AI Articles and Analysis about model development

Generative AI as a Catalyst for Enterprise Innovation_1x
Agentic Systems
Finance
Automation and robotics
Financial services
Business intelligence and analytics
Content Creation
Data auditing
Data collection
Data entry
Data integration
Data management
Document processing
Generative AI
Knowledge management
Large language models
Large Language Models
Machine learning infrastructure
model development
Predictive analytics and forecasting
Process automation
Report generation
Research and development
Training and development

Generative AI as a Catalyst for Enterprise Innovation – with Deborah Golden of Deloitte

Large enterprises' swift adoption of generative AI (GenAI) is driven by the quest for cost reduction and operational efficiency—but leaders risk falling behind competitors if these short-term gains stagnate without long-term innovation capabilities.
Driving Personal Relationships in F&B Procurement-min
Business intelligence and analytics
Consumer goods
Generative AI
Retail
model development
Predictive analytics and forecasting

Driving Analytics Efficiencies and Insights in F&B Procurement – with Hal Gerson of Fresh Del Monte and Edmund Zagorin of Arkestro

 This interview analysis is sponsored by Arkestro 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.
Artificial Intelligence at Geico-1x-min
Business intelligence and analytics
Aviation
Data auditing
Heavy industry
Data collection
Transportation
Data integration
Data management
Generative AI
model development

Artificial Intelligence at Boeing – Two Use Cases

Boeing, founded in 1916, is a global aerospace company and one of the largest aircraft manufacturers in the world. Headquartered in Arlington, Virginia, the company operates in commercial airplanes, defense, space, and security sectors. 
Solving Workforce and Workflow Challenges in Field Services with Tribal Knowledge-min
Claim management
Field Services
Customer service
Heavy industry
Data auditing
Data collection
Data integration
Data management
Generative AI
Knowledge management
model development
Tribal Knowledge

Solving Workforce and Workflow Challenges in Field Services with Tribal Knowledge – with Experts from Aquant, ABB, Atlas Copco, Illumina, and Tetra Pak

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.
Making the Move to Saas in Financial Services-1x-min
Claim management
Finance
Enterprise resource planning
Insurance
Generative AI
model development

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
Business intelligence and analytics
Software development
Data analysis
Technology
Data auditing
Data collection
Data management
Generative AI
Intelligence
model development
Security

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
Generative AI
Professional services
Large Language Models
model development

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.
Combining LLM Agents to Drive ROI in Business Workflows-2x
Content Creation
Software development
Copilot
Technology
Generative AI
Large Language Models
model development
Natural Language Processing

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.