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10 Game-changing Use Cases for Data & AI
Five major industries have adopted Artificial Intelligence (AI) to solve real-world challenges — from capturing new markets to improving the patient experience.
Here’s a look at what’s possible.
Retail
This is how you gain
Demand forecasting
Forward-looking retailers use AI to forecast demand month by month and region by region. They combine real-time signals with historical data from point of sales systems, weather, and social media to predict what products will be needed and when. Challenges solved:
Challenges solved:
- Inventory volatility
- Inefficient/reactive supply chain operations
- Lost retail revenue opportunities
Security upgrades
AI-powered video analytics turn existing surveillance infrastructure into a real-time operations engine – helping retailers detect safety risks, monitor traffic patterns, and optimize layouts without adding new hardware.
Challenges solved:
- Blind spots in store safety and incident response delays
- Limited visibility into shopper behavior
- Manual, time-intensive audits of in-store operations
Inventory management
AI solutions offer real-time, highly accurate views of inventory levels — to help stores respond faster to demand shifts, reduce waste, and allocate resources more strategically.
Challenges solved:
- Out-of-stock or overstock status
- Inaccurate inventory data
- Error-prone processes for counting inventory
Manufacturing
This is how you gain
Line quality control
Computer vision or AI visual intelligence is used to automate routine inspections and pinpoint defects immediately, leading to new levels of visibility and productivity.
Challenges solved:
- High product defect rates on the line
- Time-intensive processes for quality control
- High return rates
Parts delivery
Digital twins — virtual representations that act as digital counterparts of a physical object or process — are drastically improving errors with real-time data.
Challenges solved:
- Line downtime due to inefficient parts delivery
- High labor costs
Client story
$10M saved the company in lost labor. For an automobile manufacturer, carts were loading parts inefficiently and getting into traffic jams in high-use areas. We built a digital twin of the factory floor, created an optimization algorithm for parts delivery — and saved the company $10 million in lost labor.
Health & life sciences
This is how you gain
Hospital labor optimization
Hospitals are using AI-platforms with real-time data integration across records and staffing systems, and IoT medical devices to help make faster decisions for patients, leading to more informed care.
Challenges solved:
- Inefficient care coordination
- Downtime between lab results and provider consultations
- Lengthy patient stays
- Low patient satisfaction
Automated document processing
AI-powered systems — using large language models — can intelligently extract, summarize, and validate data from complex documents like invoices, claims, and clinical notes, reducing the need for human review. Challenges solved:
Challenges solved:
- Error-prone back-office processing
- High capital costs across invoicing, claims management, ERP and more
- High labor costs
Client story
We worked with a pioneering health care system to develop a machine learning driven support platform aimed at improving hypertension management. The solution provides personalized treatment recommendations, leading to an estimated 100 additional days of life per patient and annual healthcare savings of $2,000 for 20% of the hypertensive population.
We worked with Steward Health Care to create a length-of-stay monitoring system powered by real-time business data and analytics — reducing patient length of stay by 1.5 days and saving millions of dollars per hospital per year.
Financial services
This is how you gain
AI-enhanced customer agents
Financial institutions now deploy multimodal support AI agents that can engage across chat, voice, and social platforms to offer accurate, real-tim responses and personalized support 24/7.
Challenges solved:
- Slow customer service response times
- Lack of resources to capture new or untapped markets
Data science upskilling/enablement
Organizations like yours are turning to partners like Insight with MLOps and LLM expertise to help internal teams build, deploy and integrate AI models effectively—accelerating time to impact while maintaining governance.
Challenges solved:
- Older patterns and legacy tools for data science
- Constraints with small amounts of data
- Error-prone deployments for code
- Processes not repeatable
Client story
A financial services leader worked with Insight to integrate AI into its investment and trading platform — leading to a 72% increase in new millennial account openings at launch.
Energy
Infrastructure inspection
AI-enhanced and computer vision drone systems inspect hundred-acre areas for dust, encroachment, and more, using models with high accuracy for a complete view.
Challenges solved:
- Error-prone processes (ground-level visual inspection)
- Time-intensive processes
Predictive maintenance
Edge-deployed AI models monitor equipment health continuously — enabling early detection of failures and smarter maintenance scheduling to reduce unplanned downtime. Challenges solved:
Challenges solved:
- Reactive repair crews in “firefighting mode”
- High repair costs
- Time-consuming maintenance
What will AI do for your business?
No matter where you are in your data and AI journey, Insight helps you move with clarity and purpose to identify high-impact use cases and turn strategy into measurable outcomes. This is how you gain clarity, momentum and efficiency. This is how you gain the lead.
