AI Articles and Analysis about model development

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.
02 – Streamlining Data-Driven Decision-Making in Customer Experiences
for Financial Services@1x-min
Business intelligence and analytics
Finance
Case management
Financial services
Claim management
Insurance
Claim management
Marketing
Compliance
Media
Customer analytics
Customer experience
Customer service
Data analysis
E-commerce
Enterprise resource planning
Generative AI
Intelligent assistant
Investment
Large Language Models
model development
Recommendations
Report generation
Risk management

Streamlining Data-Driven Decision-Making in Customer Experiences for Financial Services – with Ciprian Porutiu of Marsh McLennan and Mike Borrelli of Uniphore

This interview analysis is sponsored by Uniphore 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 Procter & Gamble@2x-min
Business intelligence and analytics
Chemicals
Claim management
Consumer goods
Customer analytics
Heavy industry
Customer experience
Manufacturing
Customer service
Retail
Data analysis
Data auditing
Data collection
Data integration
Data management
Generative AI
Help desk
Large Language Models
Logistics
model development
Supply chain management

Artificial Intelligence at Procter & Gamble

Procter and Gamble (P&G) is an American multinational goods corporation. The company is well known for its fabric & home care, family care, beauty, healthcare, and grooming products. P&G owns several of the most well-known brand names in the world, including Pampers, Tide, Gillette, Always, Head & Shoulders, and many more. 
UNICRI on responsible AI criteria and other tool kits@2x-min
Cybersecurity
Government
Emergency management
Law enforcement
Generative AI
Intelligence
Large Language Models
Logistics
Machine learning infrastructure
model development
Natural Language Processing
Research and development
Security
Software development

UNICRI-Approved Responsible AI Toolkits for Law Enforcement

The United Nations Interregional Crime and Justice Research Institute (UNICRI) was established in 1968 as an autonomous institution in response to a United Nations resolution urging expanded crime prevention and criminal justice activities. UNICRI's mission is to advance justice, crime prevention, security, and the rule of law to support peace, human rights, and sustainable development. 
The Future of Customer Interactions in Financial Services
Business intelligence and analytics
Case management
Claim management
Claim management
Compliance
Conversion optimization
Customer analytics
Customer analytics
Customer experience
Customer service
Data auditing
Data collection
Data integration
Data management
Enterprise resource planning
Generative AI
Help desk
Intelligent assistant
Large Language Models
Market segmentation
Marketing and advertising
model development
Risk management

The Future of Customer Interactions in Financial Services – with Ivan Edwards of Cadence Bank and John Thomas of Uniphore

This interview analysis is sponsored by Uniphore 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.
Var.1_Streamlining Field Services with AI – with Leaders from Aquant, Xylem and Johnson Control
Generative AI
Automotive
Large Language Models
Chemicals
Logistics
Electronics
model development
Heavy industry
Supply chain management
Manufacturing
Mining
Natural resources
Oil & gas
Transportation

Streamlining Field Services with AI – with Leaders from Aquant, Xylem and Johnson Controls

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.
final-updated-Approaching Life Sciences and Retail Challenges from a Data Perspective – with Alberto Rizolli of V7
Automation and robotics
Consumer goods
Conversion optimization
Healthcare
Customer analytics
Pharma
Data auditing
Professional services
Data collection
Retail
Data management
Retail
Demand generation
Document processing
Drug discovery
Generative AI
Industrial automation
Large language models
Large Language Models
Logistics
Marketing and advertising
model development
Natural Language Processing
Research and development
Supply chain management

Approaching Life Sciences and Retail Challenges from a Data Perspective – with Alberto Rizzoli of V7

Problems in different industries can look quite similar when looked at from the perspective of data. Though diverse business problems originate from distinct domains and needs, they often share a common thread and solution. 
Financial Services Challenges from a Data Perspective – with Bill Waid of FICO@2x-min
Case management
Claim management
Compliance
Customer experience
Customer service
Data auditing
Data collection
Data entry
Data integration
Data management
Enterprise resource planning
Generative AI
Help desk
Intelligent assistant
Investment
Knowledge management
Large Language Models
model development
Natural Language Processing
Process automation
Report generation
Risk management
Training and development

Financial Services Challenges from a Data Perspective – with Bill Waid of FICO

Originally founded as Fair, Isaac and Company, FICO is a data analytics company founded in 1956. Based in Bozeman, Montana, the company is focused on credit scoring services, most notably its FICO score, which measures a person's creditworthiness.