Infographic 10 Game-Changing Use Cases for Data and AI
By Insight Editor / 5 Aug 2022 / Topics: Data analytics Artificial Intelligence (AI)
So you’ve heard of Artificial Intelligence (AI) — but do you know what it can do for your business? In this infographic, we break down how organizations across industries are leveraging AI to solve their toughest challenges, including:
- Inefficient supply chain operations
- High labor and capital costs
- Lack of resources
- Time-intensive processes
Accessibility note: The infographic is transcribed below the graphic.
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10 Game-changing Use Cases for Data & AI
Five major industries are adopting 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
Demand forecasting
Next-gen retailers are using AI to analyze historical data, predicting what products will be needed and when — month-by-month, region-by-region and even based on weather patterns.
Challenges solved:
- Demand volatility
- Inefficient/reactive supply chain operations
- Lost retail revenue opportunities
Inventory management
AI solutions are offering real-time, highly accurate views of inventory levels — helping stores keep business running smoothly while allocating resources more strategically.
Challenges solved:
- Out-of-stock or overstock status
- Inaccurate inventory data
- Error-prone processes for counting inventory
Manufacturing
Line quality control
Computer vision is automating routine inspections and pinpointing 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
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
Hospital labor optimization
Unified data platforms powered by AI algorithms are helping hospitals make more timely decisions for patients, leading to more efficient, better-quality care.
Challenges solved:
- Inefficient care coordination
- Downtime between lab results and provider consultations
- Lengthy patient stays
- Low patient satisfaction
Automated document processing
Reducing or eliminating human intervention for document processing is increasing accuracy and efficiencies.
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 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
AI-enhanced customer agents
Cognitive customer agents are integrating with social channels to engage potential clients — improving the customer experience by solving issues and answering questions quickly.
Challenges solved:
- Slow customer service response times
- Lack of resources to capture new or untapped markets
Data science upskilling/enablement
Seeking outside expertise in Machine Learning Ops (MLOps) is helping teams identify, build and deploy AI models — taking AI adoption to the next level at velocity.
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
Computer vision drone cameras are inspecting 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
Detection algorithms are being pushed to edge locations — helping energy companies proactively shut down faulty machines, create more efficient repair patterns and save millions in repair costs.
Challenges solved:
- Reactive repair crews in “firefighting mode”
- High repair costs
- Time-consuming maintenance
What will AI do for your business?
No matter your industry or level of AI adoption, you can turn data into impact. Insight leverages deep expertise to help you pinpoint and execute on your most strategic use cases for maximum ROI.
