AI Articles and Analysis about model development

Essentials of Deploying Large Language Models in the Enterprise – v.2-1-min
Generative AI
Large Language Models
model development
Natural Language Processing
Text-to-image

Essentials of Deploying Large Language Models in the Enterprise – with Anton Kornienko and Ben Webster of NLP Logix

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. 
Multichannel Customer Journeys in Financial Services-1
Business intelligence and analytics
Finance
Case management
Financial services
Claim management
Insurance
Customer analytics
Customer experience
Customer service
Data analysis
Data auditing
Data collection
Data integration
Data management
Generative AI
Help desk
Intelligent assistant
Large Language Models
model development
Natural Language Processing
Predictive analytics and forecasting

Multichannel Customer Journeys in Financial Services – with Anuj Maniar of Deloitte

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.
Artificial Intelligence at Northwestern Mutual@1x-min
Business intelligence and analytics
Finance
Customer analytics
Financial services
Data analysis
Insurance
Generative AI
model development
Predictive analytics and forecasting
Report generation
Social network analysis

Artificial Intelligence at Northwestern Mutual

Northwestern Mutual is an insurance and financial planning firm operating in the USA. The company reported nearly $35 billion in revenue and a surplus of over $37 billion in 2022. It also surpassed five million clients across its product lines, including life insurance, disability insurance, long-term care insurance, annuities, and wealth management. 
Solving Insurance Inefficiencies with AI – v.1-1
Business intelligence and analytics
Finance
Case management
Insurance
Claim management
Customer analytics
Customer experience
Customer service
Data analysis
Data auditing
Data collection
Data integration
Data management
Generative AI
Help desk
Intelligent assistant
Large Language Models
model development
Predictive analytics and forecasting

Solving Insurance Inefficiencies with AI – with Sandee Suhrada and Karl Hersch of Deloitte

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.
Claims and Underwriting Trends in Personalized Insurance with AI – v.1-1
Business intelligence and analytics
Finance
Case management
Financial services
Claim management
Insurance
Claim management
Marketing
Compliance
Media
Customer analytics
Customer experience
Data analysis
Data auditing
Data collection
Data integration
Data management
E-commerce
Enterprise resource planning
Generative AI
Intelligent assistant
Investment
model development
Recommendations
Search engine
Search engine
Social network analysis
Text analysis
Utilization management

Claims and Underwriting Trends in Personalized Insurance with AI – with Kelly Cusick and Michael Cline of Deloitte

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.
01 – Building Trust in Data Science in Life Sciences@1x-min
Case management
Chemicals
Case management
Healthcare
Claim management
Heavy industry
Claim management
Manufacturing
Data analysis
Pharma
Data auditing
Data collection
Data integration
Data management
Enterprise resource planning
Generative AI
Help desk
Hiring
HR
model development
Predictive analytics and forecasting
Skills ID

Building Trust in Data Science in Life Sciences – Bikalpa Neupane of Takeda Pharmaceuticals

AI and data science have seen increased use in life sciences, particularly in the pharmaceutical industry. However, despite the multitude of AI use cases, pharmaceutical companies tend not to embrace every emerging AI trend eagerly. 
Automation and Beyond
for Sales and Marketing
in Life Sciences-1
"Clinical support
Healthcare
Case management
Pharma
Case management
Claim management
Claim management
Customer analytics
Customer service
Emotion recognition
Enterprise resource planning
Generative AI
Market segmentation
Marketing and advertising
Marketing automation
model development

Automation and Beyond for Sales and Marketing in Life Sciences – with Mark Miller of Deloitte

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.
Developing a Product Mindset in the AI-Driven Enterprise – v.1-min
Claim management
Claim management
Customer service
Data analysis
Data auditing
Data collection
Data integration
Data management
Enterprise resource planning
Generative AI
Large language models
model development

Developing a Product Mindset in the AI-Driven Enterprise – with Jennifer Bradshaw and Arash Kamiar at NLP Logix

This interview analysis 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.