What Is Automation? Complete Guide to Technology Transforming Work in 2026
- Muiz As-Siddeeqi
- 2 hours ago
- 29 min read
Every second, somewhere in the world, a robot arm picks up a package. A chatbot answers a customer question. A software script processes a loan application. These aren't science fiction scenes—they're ordinary moments in our automated present. Right now, over 1 million robots work in Amazon warehouses alone, while the global automation market races toward $379 billion by 2030. Whether you realize it or not, automation touches nearly every product you buy, every service you use, and potentially, every job you'll hold in your lifetime. Understanding automation isn't optional anymore—it's essential.
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TL;DR
Automation replaces human tasks with machines, software, or algorithms that operate with minimal human intervention
The global industrial automation market reached $206.33 billion in 2024 and will hit $378.57 billion by 2030 (Grand View Research, 2024)
Over 60% of companies had implemented automation by 2024, with adoption rates accelerating rapidly (Thunderbit, 2025)
Real-world impact: Amazon deployed 1 million robots across its facilities, reducing order processing time by 25% (AboutAmazon, 2024)
While 85 million jobs may be displaced by 2025, 97 million new roles will emerge, creating a net gain of 12 million positions (World Economic Forum, 2023)
Automation spans industrial robotics, workflow software, AI-powered systems, and smart devices across all industries
What Is Automation?
Automation is the use of technology—including machines, software, robots, and algorithms—to perform tasks with minimal human intervention. It replaces repetitive manual work with automated systems that execute processes faster, more accurately, and more consistently than humans. Automation ranges from simple mechanical devices to sophisticated AI-powered systems that learn and adapt over time.
Table of Contents
Understanding Automation: Core Definition and Concepts
Automation means using technology to do work that humans used to do manually. At its heart, automation is about replacing human action with programmed commands, mechanical systems, or intelligent algorithms.
Think of it this way: when you set your coffee maker to brew at 6 AM, that's automation. When a car factory robot welds chassis frames without stopping for breaks, that's automation. When software automatically sorts your emails into folders, that's automation too.
The key element that makes something "automation" is self-operation. Once set up, automated systems run with little or no human intervention. They follow pre-programmed instructions or learn patterns through artificial intelligence.
Three Core Components
Every automated system has three basic parts:
Sensors and inputs collect information from the environment. These might be temperature gauges, cameras, motion detectors, or data feeds from other systems.
Control systems make decisions based on that information. This could be simple if-then logic, complex algorithms, or AI models that learn over time.
Actuators and outputs execute the decisions. Motors move robot arms, valves control flow, software updates databases, or messages get sent to customers.
According to Grand View Research (2024), the industrial automation and control systems market stood at $206.33 billion in 2024, demonstrating how deeply automation has embedded itself into modern business operations.
The Evolution: From Water Wheels to AI
Automation didn't start with computers. Humans have been automating tasks for thousands of years.
Ancient Foundations (Before 1700)
Water wheels automated grain milling as early as 2,000 years ago in ancient Greece. These devices used flowing water to turn stones that ground wheat into flour—no human muscle required.
In 1624, Cornelius Drebbel invented the temperature regulator, an early feedback control system. By the 1680s, pressure regulators and float regulators emerged, showing that even centuries ago, people understood the value of self-adjusting systems.
Industrial Revolution Era (1700-1900)
The real automation revolution began in the 1700s. In 1745, Jacques de Vaucanson invented the first automated loom. Then in 1801, Joseph Marie Jacquard created the Jacquard loom, which used punched cards to control weaving patterns—an early form of programming (Britannica, 1999).
Oliver Evans developed an automatic flour mill in 1785, creating history's first completely automated industrial process with continuous production and zero human intervention (Progressive Automations, 2025).
The steam engine, perfected by James Watt, became the power source that drove early industrial automation. Factories could now run machines without relying on water wheels or animal power.
Electrical Age (1900-1950)
The early 1900s brought electricity, which transformed automation possibilities. Electric motors were easier to control than steam engines. In 1913, Henry Ford introduced the moving assembly line for automobile production—a breakthrough that slashed production times and costs while improving efficiency (Automate.org, n.d.).
The assembly line represented a fundamental shift: instead of skilled workers building complete products, specialized machines and unskilled workers each performed one small task repeatedly. This process automation became the template for modern manufacturing.
Computer Era (1950-2000)
The 1958 introduction of solid-state digital logic modules for programmable logic controllers (PLCs) marked a turning point. These predecessors to modern PLCs gradually replaced electro-mechanical relay logic (Progressive Automations, 2025).
In 1971, microprocessors arrived, causing dramatic price drops for computer hardware. This enabled rapid growth of digital controls in manufacturing. By the 1980s and 1990s, computer-integrated manufacturing became standard, with software managing production from design through delivery.
Modern AI Era (2000-Present)
The 21st century introduced intelligent automation powered by artificial intelligence, machine learning, and the Internet of Things (IoT). In 2012, Amazon acquired Kiva Systems for $775 million, launching the era of warehouse robotics that would eventually deploy over 1 million robots (AboutAmazon, 2024).
By 2024, generative AI began transforming automation again. Amazon's DeepFleet AI model improved robot efficiency by 10 percent, a massive gain at their scale (Fortune, 2025).
Types of Automation Systems
Automation comes in many forms. Understanding these categories helps you recognize automation opportunities in your own work.
Basic Automation (Fixed Automation)
Basic automation performs one task repeatedly without variation. Assembly line robots that weld the same car part all day exemplify this type. Once programmed, they execute the same motion thousands of times.
These systems are inflexible but extremely fast and reliable for high-volume production.
Programmable Automation
Programmable automation can be reprogrammed to perform different tasks. CNC (Computer Numerical Control) machines fall into this category. You can program them to cut different shapes and patterns by changing the code.
This flexibility makes programmable automation ideal for batch production where you make several thousand of one product, then switch to another.
Flexible Automation
Flexible automation adapts to produce different products with minimal changeover time. Modern car factories use flexible automation to build multiple vehicle models on the same assembly line.
According to Mordor Intelligence (2025), flexible automation systems are growing rapidly as manufacturers demand the ability to switch products quickly without rebuilding entire production lines.
Intelligent Automation (Cognitive Automation)
Intelligent automation combines AI, machine learning, and robotic process automation (RPA) to handle complex tasks that require decision-making. These systems can analyze data, learn patterns, and adapt their behavior.
The intelligent process automation market reached $14.55 billion in 2024 and will grow to $44.74 billion by 2030, expanding at a 22.6% compound annual growth rate (Grand View Research, 2024).
Robotic Process Automation (RPA)
RPA uses software robots to automate digital tasks like data entry, form filling, and moving information between systems. Unlike physical robots, these "bots" work entirely in software.
Companies worldwide deployed over 650 bots for IT and HR processes, realizing 50%+ efficiency gains and 40% improvements in compliance and accuracy (ExpertBeacon, n.d.).
Industrial Automation
Industrial automation applies to manufacturing and includes robotics, control systems, and smart sensors. It ranges from simple conveyor belts to sophisticated AI-powered quality inspection systems.
Workflow Automation
Workflow automation manages business processes by routing tasks, documents, and approvals through predefined steps. The workflow automation market reached $23.77 billion in 2025 and will grow to $37.45 billion by 2030 (Mordor Intelligence, 2025).
How Automation Works: Key Technologies
Modern automation relies on several converging technologies working together.
Sensors and Data Collection
Automation starts with sensing. Sensors measure temperature, pressure, position, speed, light, sound, and countless other variables. Modern sensors generate massive amounts of data that feed into control systems.
Amazon's warehouse robots use cameras, LiDAR, and sensors to navigate facilities and avoid collisions with humans and other robots (AboutAmazon, 2024).
Control Systems
Control systems process sensor data and make decisions. These include:
Programmable Logic Controllers (PLCs) execute logic sequences for industrial equipment. They're rugged, reliable computers designed for factory environments.
Distributed Control Systems (DCS) manage complex processes across large facilities like oil refineries or chemical plants. The DCS segment held 35.5% of the automation market in 2025 (Data Bridge Market Research, 2025).
SCADA (Supervisory Control and Data Acquisition) systems monitor and control infrastructure like power grids, water treatment, and transportation networks.
Artificial Intelligence and Machine Learning
AI enables automation to handle tasks that previously required human judgment. Machine learning algorithms analyze patterns in data and make predictions.
In 2024, AI adoption in sales jumped from 24% to 43%, with generative AI tools assisting with emails, lead analysis, and customer interactions (Thunderbit, 2025). Machine learning now automates diagnostics in healthcare and fraud detection in financial services.
Robotics
Physical robots execute actions in the real world. Industrial robots include:
Robotic arms for welding, assembly, and material handling
Autonomous mobile robots (AMRs) that navigate warehouses without fixed guide paths
Collaborative robots (cobots) designed to work safely alongside humans
The global industrial automation market's robots segment is growing at 12% annually through 2034, faster than most other automation technologies (Precedence Research, 2025).
Internet of Things (IoT)
IoT connects devices, sensors, and systems to share data and coordinate actions. Smart factories use IoT to enable machines, robots, and control systems to communicate in real-time.
According to Straits Research (2025), IoT integration is a key driver of industrial automation growth, enabling predictive maintenance and real-time process optimization.
The Automation Market: Numbers and Growth
The automation industry is experiencing explosive growth across all sectors.
Overall Market Size
The global industrial automation market reached $192.02 billion in 2024 and will climb to $420.49 billion by 2033, growing at 9.1% annually (Straits Research, 2024).
Multiple market segments show similar trajectories:
Industrial Control & Factory Automation: $255.89 billion in 2024, reaching $399.12 billion by 2029 (MarketsandMarkets, 2025)
Warehouse Automation: $29.91 billion in 2025, expanding to $63.36 billion by 2030 at 16.2% growth rate (Mordor Intelligence, 2025)
Intelligent Process Automation: $14.55 billion in 2024, projected to hit $44.74 billion by 2030 (Grand View Research, 2024)
Regional Distribution
Asia-Pacific dominates with 39% of global industrial automation revenue in 2024. China, India, South Korea, and Southeast Asia drive this leadership through massive manufacturing investments and government initiatives like "Made in China 2025" (Grand View Research, 2024).
North America commands 34.68% of workflow automation revenue and leads in financial process automation (Mordor Intelligence, 2025). The United States continues to commission mega-warehouses exceeding 1 million square feet, supported by a $44.2 billion industrial build-out pipeline.
Europe held $4.74 billion in manufacturing automation value in 2024, with growth accelerating to $12.17 billion by 2034. Well-established manufacturers adopting automation for quality standards drive European growth (Precedence Research, 2025).
Adoption Rates
By 2024, 60% of companies had implemented automation, with adoption rates expected to increase rapidly (Thunderbit, 2025). The Gartner survey found that 85% of infrastructure and operations leaders without full automation expect to increase automation within three years (AIMultiple, n.d.).
Seventy-five percent of companies use sales automation, and among successful sales organizations, the rate is even higher (Thunderbit, 2025).
Real-World Case Studies
Let's examine documented automation implementations with specific outcomes.
Case Study 1: Amazon's Warehouse Revolution
Company: Amazon
Timeline: 2012-2024
Implementation: Multi-stage robotics deployment
Amazon acquired Kiva Systems in 2012 for $775 million. Since then, they've deployed more than 1 million robots across over 300 fulfillment centers worldwide (AboutAmazon, October 2024).
Key Technologies:
Sequoia robotic system using AI, robotics, and computer vision
Proteus autonomous mobile robots that navigate around human workers
DeepFleet generative AI model improving robot efficiency by 10%
Digit bipedal robots from Agility Robotics for tote consolidation
Results:
Operational efficiency increased by 25% (IEEE Spectrum, April 2025)
Over 75% of Amazon's orders worldwide now processed with robotic assistance (Robotics and Automation News, July 2025)
Robot population (1 million+) approaches human workforce levels (1.5 million globally)
Five-year OPEX reduction of 42% in facilities using AMRs, with eight-month payback periods (Mordor Intelligence, 2025)
Source: AboutAmazon.com (2024), IEEE Spectrum (2025), Robotics and Automation News (2025)
Case Study 2: Arizona State University Student Enrollment
Organization: Arizona State University (ASU)
Timeline: 2023-2024
Implementation: AI-powered student enrollment automation
ASU struggled with time-consuming manual processes in student enrollment and document verification. Traditional methods created bottlenecks and delayed onboarding for new students.
Solution Implemented:
Custom no-code student enrollment system integrating with university databases
AI-powered chatbots handling student inquiries 24/7
Automated student onboarding portal with self-service options
Results:
Application processing accelerated by 50%
Fewer errors in document verification
Enhanced student experience through faster response times
Staff redeployed to higher-value student support activities
Source: ColorWhistle (September 2025)
Case Study 3: Barclays Bank Loan Processing
Company: Barclays Bank
Timeline: 2023-2024
Implementation: AI-powered automation in loan processing
Barclays deployed AI-powered automation throughout its loan processing operations to reduce processing times, minimize errors, and improve customer satisfaction.
Key Technologies:
Machine learning algorithms for credit assessment
Natural language processing for document analysis
Automated workflow systems for application routing
Results:
Processing times reduced by 20-30%
Lower error rates in loan assessments
Improved customer satisfaction scores
Cost savings of 20-30% according to McKinsey research
By 2025, 80% of financial institutions had adopted similar AI-powered automation in loan processing (Gartner projection cited by SuperAGI, June 2025)
Source: SuperAGI (June 2025), McKinsey research
Case Study 4: HCL Technologies IT and HR Automation
Company: HCL Technologies
Timeline: 2022-2024
Implementation: Large-scale RPA deployment for IT and HR services
HCL Technologies deployed over 650 bots for IT and HR service processes across its global operations.
Results:
Efficiency gains exceeding 50%
Compliance and accuracy improvements of approximately 40%
System integration after a recent acquisition completed 4x faster due to RPA
Demonstrated scalability of automation in professional services
Source: ExpertBeacon (n.d.), AIMultiple (n.d.)
Case Study 5: Shreveport Fulfillment Center
Company: Amazon
Location: Shreveport, Louisiana
Timeline: 2024
Implementation: Next-generation state-of-the-art fulfillment center
Amazon launched its most advanced fulfillment center in 2024, equipped with cutting-edge robotics and AI systems to support employees who package and deliver customer orders.
Key Technologies:
Full integration of Sequoia inventory management system
Proteus autonomous robots working alongside humans
Project Eluna agentic AI for workflow optimization
DeepFleet AI foundation model for fleet management
Results:
Served as testing ground for technologies being scaled across Amazon's network
Demonstrated viability of human-robot collaboration at scale
Reduced repetitive physical tasks for employees
Improved safety by minimizing lifting and repetitive motion
Source: AboutAmazon (October 2024), IEEE Spectrum (April 2025), Fortune (February 2025)
Industries Transformed by Automation
Automation affects virtually every industry, but some have experienced more dramatic transformations.
Manufacturing
Manufacturing leads automation adoption. The manufacturing automation market reached $13.53 billion in 2024 and will grow to $34.28 billion by 2034 (Precedence Research, August 2025).
Automotive manufacturing uses flexible automation to build multiple vehicle models on the same assembly line. Electronics manufacturing relies on precision robots for component assembly. Food and beverage production uses automation for packaging, sorting, and quality control.
China's "Made in China 2025" initiative aims to upgrade manufacturing capabilities with smart technologies. Companies like Huawei implement AI and IoT to automate production lines, enhancing productivity (Straits Research, 2024).
Logistics and Warehousing
Warehouse automation exploded in recent years. The warehouse automation market reached $29.91 billion in 2025 and will hit $63.36 billion by 2030, growing at 16.2% annually (Mordor Intelligence, 2025).
Hardware captured 58% of the warehouse automation market in 2024, while software is set to post the highest 17% growth rate through 2030. Mobile robots are forecast to expand at a 20.5% growth rate to 2030 (Mordor Intelligence, 2025).
More than half of warehouse operators cite unfilled headcount as the top automation catalyst. Wage bills climbed 7-9% year-over-year in 2024 for U.S. general warehouse labor, reinforcing ROI math that favors collaborative robotics (Mordor Intelligence, 2025).
Banking and Financial Services
The Banking and Financial Services sector held 23.96% of the workflow automation market share in 2024 (Mordor Intelligence, 2025). Financial institutions automate fraud detection, loan processing, customer service, and trading operations.
According to research cited by SuperAGI (June 2025), AI in loan processing results in 20-30% cost reductions and 10-20% increases in customer satisfaction. By 2025, 80% of financial institutions had adopted some form of AI-powered automation in loan processing operations.
Seventy percent of basic banking operations are projected to be automated by 2025, with loan processing automation expected to reach 80% by 2030. As much as 54% of banking jobs have high potential for AI automation (DemandSage, September 2025).
Healthcare
Healthcare projects the fastest growth in the intelligent process automation market from 2025 to 2030. Healthcare businesses increasingly focus on reducing operational expenses and enhancing operational efficiency (Grand View Research, 2024).
Machine learning automates diagnostics and paperwork, giving clinicians more time for patient care. AI-powered systems analyze medical images, predict patient outcomes, and manage hospital resources.
Healthcare and Pharmaceuticals is projected to compound at an 11.38% annual growth rate through 2030 in workflow automation (Mordor Intelligence, 2025).
Retail and E-Commerce
Retail and e-commerce held 28% revenue share of the warehouse automation market in 2024, while e-grocery is projected to grow at 18.3% annually through 2030 (Mordor Intelligence, 2025).
Retailers automate inventory management, pricing optimization, customer service through chatbots, and personalized marketing recommendations. Amazon's massive automation investments set the standard that other retailers now chase.
Agriculture
The World Economic Forum predicts a 30% increase in professional agricultural roles by 2028, equal to 30 million jobs. This growth comes from shorter supply chains and the need for in-person manual labor, indicating AI won't fill increased agricultural demand (AIPRM, July 2024).
However, precision agriculture uses automation for planting, harvesting, irrigation control, and crop monitoring through drones and sensors.
Pros and Cons of Automation
Automation delivers significant benefits but also creates challenges that organizations and societies must address.
Advantages of Automation
Increased Productivity Machines work 24/7 without breaks. Amazon's robots process packages around the clock, enabling faster delivery than human-only operations could achieve. Manufacturing facilities using automation report productivity gains of 50% or more (ExpertBeacon, n.d.).
Improved Quality and Consistency Automated systems don't get tired or distracted. They execute tasks the same way every time. This consistency reduces defects and improves product quality. HCL Technologies achieved 40% improvement in compliance and accuracy through RPA (ExpertBeacon, n.d.).
Enhanced Safety Robots handle dangerous tasks like working with toxic chemicals, extreme temperatures, or heavy lifting. Amazon's robots reduce employee injuries by minimizing repetitive physical tasks (AboutAmazon, 2024).
Cost Reduction While automation requires upfront investment, it cuts long-term costs. Case studies show a 42% five-year OPEX reduction relative to manual processes, with eight-month payback periods (Mordor Intelligence, 2025). Research indicates 20-30% cost savings in loan processing automation (SuperAGI, June 2025).
Faster Processing Automated systems process information and execute tasks much faster than humans. Barclays Bank reduced loan processing times by 20-30% through AI-powered automation (SuperAGI, June 2025). Arizona State University accelerated application processing by 50% (ColorWhistle, September 2025).
Data-Driven Insights Automation generates vast amounts of data that organizations can analyze to optimize operations, predict maintenance needs, and improve decision-making.
Scalability Automated systems scale more easily than human operations. Adding capacity often means deploying additional software licenses or machines rather than recruiting, training, and managing more employees.
Disadvantages and Challenges
Job Displacement Automation replaces human workers in some roles. Research suggests 85 million jobs will be displaced by 2025, though 97 million new roles will emerge (World Economic Forum, 2023). Workers in routine, repetitive jobs face the highest displacement risk.
High Initial Investment Implementing automation requires significant upfront capital for equipment, software, integration, and training. Small and medium enterprises often struggle with these costs, though robotics-as-a-service (RaaS) models are emerging to address this barrier.
Maintenance and Technical Complexity Automated systems need skilled technicians for maintenance, troubleshooting, and optimization. Breakdowns can halt entire operations if backup systems aren't in place.
Skills Gap Seventy-seven percent of new AI jobs require master's degrees, creating substantial skills gaps (SSRN, June 2025). Organizations struggle to find workers with the technical expertise to implement and manage automated systems.
Cybersecurity Vulnerabilities Connected automated systems face cyber threats. Hackers who breach control systems could disrupt operations, steal data, or cause physical damage.
Reduced Flexibility for Unique Situations Automated systems excel at repetitive, predictable tasks but struggle with exceptions and unique situations that require human judgment, creativity, or empathy.
Dependency and Resilience Concerns Organizations become dependent on their automated systems. When systems fail, operations may grind to a halt. Building resilient systems with appropriate redundancy adds cost and complexity.
Myths vs Facts About Automation
Misconceptions about automation create unnecessary fear or unrealistic expectations. Let's separate myth from reality.
Myth 1: Automation Will Eliminate All Jobs
Fact: While automation displaces some jobs, it creates others and transforms many more. Research shows that while 85 million jobs may be displaced by 2025, 97 million new roles will simultaneously emerge, representing a net positive job creation of 12 million positions globally (SSRN, June 2025).
In 2024, AI created about 119,900 direct jobs in the U.S., while approximately 12,700 jobs were lost to AI—far fewer than created (ITIF, December 2025). The World Bank's 2019 World Development Report shows evidence that new industries and jobs in the technology sector outweigh the economic effects of workers being displaced by automation (Wikipedia, December 2025).
Myth 2: Only Manufacturing Jobs Are Affected
Fact: Automation affects every industry. While manufacturing saw early automation adoption, service industries now experience rapid automation growth. Banking, healthcare, retail, logistics, and professional services all deploy significant automation technologies.
The workflow automation market reached $23.77 billion in 2025, with Banking and Financial Services holding 23.96% market share (Mordor Intelligence, 2025). This demonstrates automation's spread beyond manufacturing.
Myth 3: Automation Is Too Expensive for Small Businesses
Fact: Automation costs are dropping. Cloud-based solutions, subscription models, and robotics-as-a-service (RaaS) make automation accessible to smaller organizations. Seventy-two percent of logistics firms plan to adopt RaaS contracts that swap multi-million-dollar capital expenditures for usage-based operational expenses (Mordor Intelligence, 2025).
The small and medium-sized enterprises segment is projected to grow at 10.31% annually in workflow automation, faster than large enterprises (Mordor Intelligence, 2025).
Myth 4: Robots Will Quickly Replace Most Workers
Fact: Companies surveyed for the World Economic Forum's 2020 report anticipated 47% of manual labor tasks could be automated by 2025, but by 2023, this prediction had been revised to 42% automation by 2027 (AIPRM, July 2024). These revisions indicate that complete automation takes longer than initial predictions suggest.
Yale's Budget Lab analysis found that labor markets show no sign of discernible disruption 33 months after ChatGPT's release, despite widespread public anxiety about AI job losses (Budget Lab at Yale, 2025).
Myth 5: Automated Systems Don't Need Human Oversight
Fact: All automated systems require human supervision, maintenance, and intervention for exceptions. Amazon emphasizes that its robots "augment" rather than replace human workers, with employees handling problem-solving, quality control, and management roles (Fortune, February 2025).
Tye Brady, Amazon Robotics' chief technologist, stated the future will never be fully automated because people need to design, program, and maintain the robots (PEX Network, February 2025).
Myth 6: Automation Only Benefits Large Corporations
Fact: Organizations of all sizes gain from automation. Small businesses automate marketing emails, invoicing, appointment scheduling, and customer communications. These modest automations save time and reduce errors without requiring massive investments.
Arizona State University, an educational institution, achieved 50% faster application processing through automation (ColorWhistle, September 2025), demonstrating benefits beyond corporate environments.
Automation and Employment Impact
The relationship between automation and employment is complex, nuanced, and emotionally charged.
Job Displacement Statistics
Current Impact: In the first six months of 2025, 77,999 tech job losses were directly attributed to AI (DemandSage, September 2025). The U.S. saw a 22% increase in AI-induced layoffs from Q4 2023 to Q1 2025 (SQ Magazine, October 2025).
Manufacturing: Since 2000, automation led to the loss of 1.7 million manufacturing jobs (TeamStage, February 2024). Manufacturing is forecasted to lose 2 million jobs by 2025 due to robotics and AI integration. Oxford Economics predicts as many as 20 million manufacturing jobs could be replaced globally by 2030 (DemandSage, September 2025).
Financial Services: Approximately 200,000 jobs are expected to be cut from Wall Street banks over the next 3-5 years. Seventy percent of basic banking operations are projected to be automated by 2025 (DemandSage, September 2025).
Customer Service: Customer service representatives face the highest immediate automation risk with 80% automation rate by 2025. AI-driven chatbots have replaced 36% of live support roles in e-commerce companies with over 200 employees (Zebracat, May 2025).
Entry-Level Positions: Entry-level job postings dropped 15% year over year. Over the past 18 months, entry-level job listings containing AI-related tasks increased by 64% by 2025 (Zebracat, May 2025).
Job Creation Statistics
New Roles: Research reveals that while 85 million jobs will be displaced by 2025, 97 million new roles will simultaneously emerge, representing a net positive job creation of 12 million positions globally (SSRN, June 2025).
AI-Related Jobs: In 2024, AI growth generated more than 8,900 employees added to the U.S. economy to develop, train, and operate AI models. Data center construction fueled over 110,000 construction jobs. Altogether, AI created about 119,900 direct jobs in 2024 (ITIF, December 2025).
Professional Growth: In Q1 2025, 35,445 AI-related positions existed, representing a 25.2% increase from Q1 2024. LinkedIn reported a 12% increase in adverts for AI-based and related jobs across seven major economies between December 2022 and September 2023 (DemandSage, September 2025).
Healthcare: Nurse practitioners are projected to grow by 52% from 2023 to 2033, much faster than the average for all occupations, as AI augments rather than replaces these jobs (National University, September 2025).
Most Vulnerable Occupations
Critical Risk (70-95% automation risk, 2024-2025):
Customer service representatives (80% automation rate)
Data entry clerks (7.5 million jobs eliminated by 2027)
Retail cashiers (65% automation risk by 2025)
High Risk: Administrative assistants declined by 33% in firms that implemented AI scheduling tools between 2021 and 2024 (Zebracat, May 2025).
Demographic Factors: Workers aged 18–24 are 129% more likely than those over 65 to worry AI will make their job obsolete. Women in clerical and administrative roles are disproportionately impacted—61% of AI-displaced roles in 2024 were held by women (National University, September 2025; SQ Magazine, October 2025).
Least Vulnerable Occupations
Jobs involving physical tasks, human emotions, teaching, caring, coaching, or complex problem-solving face lower automation risk (National University, September 2025).
Low Risk Sectors:
Healthcare professionals (nurses, therapists, physicians)
Skilled trades (construction, plumbing, electrical work)
Creative professionals requiring human judgment
Teaching and education roles
Personal services requiring human interaction
Skilled trades remain in high demand, with 94% of construction companies reporting difficulty in sourcing workers, underscoring that AI cannot replace them (DemandSage, September 2025).
Adaptation Strategies
Upskilling: Lifelong learning and upskilling are now a top priority for 75% of U.S. employers. Corporate training programs including an AI upskilling module rose by 45% globally between 2023 and 2025 (Zebracat, May 2025).
Human-Machine Collaboration: The most successful automation strategies emphasize collaboration. Forty-six percent of employers now subsidize robotics certificates to enhance human-machine teaming (Mordor Intelligence, 2025).
Education Shifts: According to a 2025 report from the National Student Clearinghouse Research Center, students earning traditional college degrees have declined, while certificate completions are trending upward as workers pursue practical skills (National University, September 2025).
Implementation Checklist: Getting Started with Automation
Organizations considering automation should follow a structured approach to maximize success.
Phase 1: Assessment and Planning
1. Identify Automation Opportunities
Map current workflows and processes
Identify repetitive, high-volume tasks
Prioritize processes with high error rates or bottlenecks
Calculate time spent on manual tasks
2. Define Clear Objectives
Set specific, measurable goals (reduce processing time by X%, cut errors by Y%)
Determine acceptable ROI timeline
Identify critical success factors
Establish baseline metrics
3. Evaluate Readiness
Assess technical infrastructure and integration requirements
Review data quality and availability
Evaluate staff technical capabilities
Determine budget constraints
4. Choose Technology Approach
Research automation technologies suitable for your use case
Consider cloud vs. on-premise deployment
Evaluate vendor options and support
Review case studies from similar organizations
Phase 2: Implementation
5. Start Small
Begin with a pilot project in one department
Choose a process with clear ROI potential
Set short-term milestones
Plan for iteration and refinement
6. Prepare Your Team
Communicate automation benefits and plans clearly
Address employee concerns about job security
Provide training on new systems
Identify internal champions
7. Ensure Data Quality
Clean and standardize data before automation
Establish data governance procedures
Set up monitoring and validation
Plan regular data audits
8. Build in Flexibility
Design systems that can be modified
Avoid over-automation that removes necessary human judgment
Create clear exception handling processes
Plan for system updates and changes
Phase 3: Optimization and Scaling
9. Monitor and Measure
Track KPIs against baseline metrics
Gather user feedback regularly
Identify bottlenecks or issues
Document lessons learned
10. Optimize Continuously
Refine automated processes based on data
Address pain points quickly
Update systems as needs change
Stay current with technology advances
11. Scale Gradually
Expand successful pilots to other departments
Integrate automated systems with existing workflows
Maintain focus on ROI
Balance automation with human oversight
12. Plan for Maintenance
Schedule regular system updates
Train staff on troubleshooting
Establish vendor support relationships
Budget for ongoing costs
Future of Automation: What's Next?
Automation technology continues evolving rapidly. Several trends will shape the next decade.
Generative AI Integration
Generative AI is already transforming automation. Amazon's DeepFleet AI model improved robot efficiency by 10 percent (Fortune, February 2025). Expect continued AI integration across all automation types.
Microsoft introduced Copilot AI features across Power Platform in January 2025 to enable natural-language workflow design, reducing build time for non-technical users (Mordor Intelligence, 2025).
Autonomous Systems Evolution
Self-driving vehicles, autonomous drones, and intelligent robots will become more capable and widespread. However, complete autonomy remains distant. The World Economic Forum cites low expectations on autonomous drivers as evidence these jobs are unlikely to be replaced by AI in the near future (AIPRM, July 2024).
Hyperautomation
Hyperautomation combines multiple automation technologies—RPA, AI, machine learning, process mining—into integrated systems that automate entire end-to-end processes rather than individual tasks.
Edge Computing and IoT
Real-time processing at the data source is removing latency barriers that previously hampered machine-critical automation. Manufacturers leverage local compute to analyze sensor streams in milliseconds (Mordor Intelligence, 2025).
Human-Robot Collaboration
Collaborative robots (cobots) designed to work safely alongside humans will proliferate. Amazon's integration of Proteus robots that navigate around human workers represents this trend (AboutAmazon, 2024).
Democratization Through Low-Code/No-Code
Low-code and no-code platforms enable non-technical users to create automated workflows. The workflow automation market's cloud segment captured 62.87% of market size in 2024, with hybrid configurations expected to expand at 10.21% annually through 2030 (Mordor Intelligence, 2025).
Robotics-as-a-Service (RaaS)
Seventy-two percent of logistics firms plan to adopt RaaS contracts that replace capital expenditures with usage-based operational expenses, unlocking automation for mid-tier companies previously priced out (Mordor Intelligence, 2025).
Industry 4.0 and Smart Factories
The Fourth Industrial Revolution emphasizes integration of cyber-physical systems, IoT, and cloud computing into manufacturing. Smart factories with enhanced automation, data exchange, and real-time analytics will become standard.
Sustainable Automation
Energy-efficient automated solutions are being introduced to cut waste, emissions, and operational costs due to growing sustainability concerns (MarketsandMarkets, 2025).
FAQ: Your Automation Questions Answered
What is automation in simple words?
Automation means using technology—machines, software, or robots—to do work that humans used to do manually. Automated systems perform tasks with minimal human intervention, following programmed instructions or learning from data. Examples include factory robots assembling products, software automatically sorting emails, or smart thermostats adjusting temperature based on your schedule.
What are the 4 types of automation?
The four main types are:
Basic (Fixed) Automation: Performs one task repeatedly without variation, like assembly line robots
Programmable Automation: Can be reprogrammed for different tasks, like CNC machines
Flexible Automation: Quickly adapts to produce different products with minimal changeover
Intelligent (Cognitive) Automation: Uses AI and machine learning to handle complex tasks requiring decision-making
How much does automation cost?
Costs vary dramatically based on complexity. Simple software automation (like email marketing tools) costs $50-500 monthly. Robotic Process Automation implementation ranges from $5,000-100,000 depending on scope. Industrial robots cost $25,000-500,000+ per unit. However, Robotics-as-a-Service models now offer usage-based pricing, making automation more accessible. Case studies show eight-month payback periods and 42% five-year operational cost reductions (Mordor Intelligence, 2025).
Will automation take all jobs?
No. While 85 million jobs may be displaced by 2025, 97 million new roles will emerge, creating a net gain of 12 million positions (SSRN, June 2025). History shows automation reallocates work rather than eliminating it. In 2024, AI created 119,900 jobs in the U.S. while displacing 12,700 (ITIF, December 2025). Jobs involving creativity, complex problem-solving, physical tasks, and human interaction face lower automation risk.
Which jobs are most at risk from automation?
Customer service representatives face 80% automation risk by 2025. Data entry clerks, retail cashiers, administrative assistants, manufacturing assembly line workers, and basic accounting roles face high automation risk. Generally, routine, repetitive jobs with predictable patterns are most vulnerable. Entry-level positions are particularly affected, with postings dropping 15% year-over-year (Zebracat, May 2025).
Which jobs are safest from automation?
Healthcare professionals (nurses, therapists, physicians), skilled trades (construction, plumbing, electrical), teaching roles, creative professionals, and jobs requiring complex human judgment face low automation risk. Ninety-four percent of construction companies report difficulty sourcing workers, indicating AI cannot replace skilled trades (DemandSage, September 2025). Jobs involving physical tasks and human emotions account for 23% of workers and are least likely to be automated (National University, September 2025).
How is AI different from traditional automation?
Traditional automation follows fixed rules and requires explicit programming for every scenario. AI-powered automation learns from data, adapts to new situations, and handles tasks requiring judgment. Traditional automation might sort emails by sender address (a simple rule), while AI automation understands email content and context to categorize messages intelligently. AI enables automation of complex cognitive tasks that previously only humans could perform.
Can small businesses afford automation?
Yes. Cloud-based tools, subscription models, and low-code platforms make automation accessible to small businesses. Workflow automation tools start at $15-100 monthly. Many businesses automate marketing emails, appointment scheduling, invoicing, and customer communications affordably. The small and medium enterprise automation segment is growing at 10.31% annually (Mordor Intelligence, 2025), demonstrating increasing accessibility.
How long does automation implementation take?
Timelines vary by complexity. Simple software automation can be deployed in days or weeks. Robotic Process Automation projects typically take 2-6 months. Industrial robot integration requires 6-18 months for planning, installation, testing, and training. Cloud-based solutions deploy faster than on-premise systems. Start with pilot projects to demonstrate value before scaling.
What skills do I need to work with automation?
For implementing automation: programming skills (Python, JavaScript), understanding of business processes, project management, and data analysis capabilities help. For working alongside automation: adaptability, digital literacy, problem-solving, and willingness to learn new tools are essential. Seventy-five percent of employers prioritize lifelong learning and upskilling (Zebracat, May 2025).
How do I know which processes to automate?
Prioritize processes that are: (1) Highly repetitive, (2) High-volume, (3) Rule-based with predictable patterns, (4) Time-consuming, (5) Error-prone when done manually, (6) Well-documented with clear steps. Calculate ROI by comparing time/cost savings against implementation costs. Start with simple processes to build momentum.
Is automation environmentally friendly?
It depends on implementation. Automation can reduce waste, optimize energy use, and minimize material consumption through precision. However, manufacturing robots and data centers consume significant energy. Energy-efficient automated solutions are now being prioritized to cut emissions and operational costs (MarketsandMarkets, 2025). Smart building automation reduces energy consumption through optimized climate control and lighting.
What happens when automated systems fail?
System failures can disrupt operations significantly. Organizations must build resilience through backup systems, redundancy, and contingency plans. Maintenance and monitoring are crucial. Amazon employs over 9,000 safety experts for robotics and automated technologies (Fortune, February 2025). Well-designed systems include failsafes, alerts, and manual override capabilities.
How do I convince leadership to invest in automation?
Present clear ROI calculations showing time and cost savings. Share relevant case studies demonstrating results in your industry. Start with a small pilot project to prove value before requesting larger investments. Address concerns about job displacement by emphasizing how automation allows employees to focus on higher-value work. Provide data on competitors' automation adoption.
What are the biggest automation implementation mistakes?
Common mistakes include: (1) Automating bad processes without fixing underlying issues first, (2) Choosing overly complex solutions for simple problems, (3) Neglecting change management and employee training, (4) Underestimating integration challenges, (5) Failing to maintain and optimize systems after deployment, (6) Not starting with clear, measurable objectives, (7) Automating too much too fast without building organizational capability.
Will automation lead to lower wages?
Evidence suggests automation impacts wages differently across sectors. Research indicates automation and AI have contributed to wage decreases of 50-70% for some blue-collar workers since 1980 (SEO.ai, n.d.). However, automation also creates higher-skilled, better-paying jobs in fields like robotics, data science, and AI development. Workers who transition to roles requiring specialized skills often see wage increases. Amazon's robotics apprenticeship program graduates see a 40% pay bump (Fortune, February 2025).
How do governments regulate automation?
Regulation varies by country and sector. Safety standards govern industrial robotics. Financial regulators oversee automated trading systems. Privacy laws affect automation involving personal data. Some regions implement robot taxes or require human oversight in critical decisions. Japan's 2024 regulation caps truck driver hours at 960 annually, intensifying automation adoption (Mordor Intelligence, 2025). Expect continued regulatory evolution as automation proliferates.
Can automation work alongside human employees?
Yes. The most effective automation strategies emphasize human-machine collaboration. Amazon states its robots "augment" rather than replace workers, with humans handling problem-solving and quality control (Fortune, February 2025). Collaborative robots (cobots) are specifically designed to work safely beside humans. Forty-six percent of employers subsidize robotics certificates to enhance human-machine teaming (Mordor Intelligence, 2025).
What is Robotic Process Automation (RPA)?
RPA uses software "robots" or "bots" to automate digital tasks like data entry, form filling, and information transfer between systems. Unlike physical robots, RPA bots work entirely in software, mimicking human interactions with computer applications. RPA is ideal for repetitive, rule-based tasks across business processes. HCL Technologies deployed 650+ bots achieving 50%+ efficiency gains (ExpertBeacon, n.d.).
How do I measure automation success?
Key metrics include: (1) Time savings per process, (2) Error rate reduction, (3) Cost per transaction decrease, (4) Processing speed improvement, (5) Employee productivity gains, (6) Customer satisfaction changes, (7) ROI and payback period, (8) System uptime and reliability. Compare metrics against baseline measurements taken before automation. Survey employees about satisfaction and workload changes. Track both quantitative and qualitative outcomes.
Key Takeaways
Automation uses technology to perform tasks with minimal human intervention, ranging from simple mechanical systems to sophisticated AI-powered platforms
The global industrial automation market reached $206.33 billion in 2024 and will grow to $378.57 billion by 2030 at 10.8% annually (Grand View Research, 2024)
Amazon deployed over 1 million robots across 300+ facilities, achieving 25% efficiency improvements and processing 75%+ of orders with robotic assistance (AboutAmazon, 2024)
While 85 million jobs may be displaced by 2025, 97 million new roles will emerge, creating a net gain of 12 million positions globally (SSRN, June 2025)
Automation delivers measurable benefits: 50%+ efficiency gains, 40% accuracy improvements, 42% five-year cost reductions, and eight-month payback periods in documented cases
Customer service representatives, data entry clerks, and retail cashiers face highest automation risk, while healthcare professionals, skilled trades, and creative roles remain safer
Small businesses can now access automation through cloud-based tools, subscription models, and Robotics-as-a-Service (RaaS), with 72% of logistics firms planning RaaS adoption
Successful automation emphasizes human-machine collaboration rather than complete replacement, with workers redeployed to higher-value activities
Automation spans all industries—manufacturing, logistics, banking, healthcare, retail, and agriculture—with adoption accelerating across all sectors
Organizations should start small with pilot projects, focus on clear ROI, invest in employee training, and continuously optimize automated systems
Actionable Next Steps
Assess Your Current State: Map your organization's workflows and identify 3-5 repetitive, high-volume processes consuming significant time or generating frequent errors.
Calculate Baseline Metrics: Measure current processing times, error rates, and costs for target processes. These baselines are essential for demonstrating ROI later.
Research Solutions: Investigate automation technologies suitable for your identified processes. Review case studies from similar organizations. Request demos from 2-3 vendors.
Start With a Pilot: Choose one simple process for a pilot automation project. Set a 3-6 month timeline with clear success criteria.
Engage Your Team: Communicate automation plans transparently. Address employee concerns. Identify internal champions who will advocate for automation.
Invest in Training: Allocate budget for employee upskilling. Consider certifications in relevant automation technologies. Seventy-five percent of employers now prioritize lifelong learning (Zebracat, May 2025).
Monitor and Measure: Track KPIs weekly during pilot phase. Gather user feedback. Document lessons learned for future automation projects.
Scale Gradually: If pilot succeeds, expand to similar processes in other departments. Avoid automating everything at once. Build organizational capability progressively.
Stay Informed: Follow industry publications, attend automation webinars, and join professional communities to stay current with technology advances.
Plan for Continuous Improvement: Automation isn't "set and forget." Schedule quarterly reviews to optimize processes, update systems, and identify new automation opportunities.
Glossary
Actuator: A device that converts energy into motion, executing commands from control systems (e.g., motors, valves, robotic arms).
Artificial Intelligence (AI): Computer systems that perform tasks typically requiring human intelligence, including learning, reasoning, and decision-making.
Autonomous Mobile Robot (AMR): Self-navigating robots that move materials in facilities without fixed guide paths, using sensors and AI.
Collaborative Robot (Cobot): Robots designed to work safely alongside human workers, featuring sensors and safety mechanisms.
Computer Numerical Control (CNC): Automated control of machine tools through computer programming, enabling precise manufacturing.
Distributed Control System (DCS): Control systems that manage complex industrial processes across large facilities, with control elements distributed throughout the plant.
Hyperautomation: Business strategy combining multiple automation technologies (RPA, AI, machine learning) to automate complex end-to-end processes.
Internet of Things (IoT): Network of physical devices embedded with sensors, software, and connectivity to exchange data.
Machine Learning: AI subset enabling systems to learn and improve from experience without explicit programming.
Programmable Logic Controller (PLC): Industrial digital computer designed for automation of manufacturing processes, machinery, and control systems.
Robotic Process Automation (RPA): Software technology using "bots" to automate repetitive digital tasks like data entry and form filling.
Robotics-as-a-Service (RaaS): Business model offering robots through subscription or usage-based pricing rather than upfront purchase.
SCADA: Supervisory Control and Data Acquisition systems that monitor and control infrastructure like power grids and water treatment.
Sensor: Device that detects and measures physical properties (temperature, pressure, motion) and converts them into signals for control systems.
Workflow Automation: Technology that automates business processes by routing tasks, documents, and approvals through predefined sequences.
Sources and References
Grand View Research (2024). "Industrial Automation And Control Systems Market Report, 2030." Retrieved from https://www.grandviewresearch.com/industry-analysis/industrial-automation-market
Thunderbit (November 2025). "Automation Statistics 2025: Comprehensive Industry Data and Market Insights." Retrieved from https://thunderbit.com/blog/automation-statistics-industry-data-insights
Mordor Intelligence (September 2025). "Workflow Automation Market - Size, Report & Forecast." Retrieved from https://www.mordorintelligence.com/industry-reports/workflow-automation-market
Mordor Intelligence (June 2025). "Warehouse Automation Market - Industry Size & Growth 2025 - 2030." Retrieved from https://www.mordorintelligence.com/industry-reports/warehouse-automation-market
Grand View Research (2024). "Intelligent Process Automation Market Size Report, 2030." Retrieved from https://www.grandviewresearch.com/industry-analysis/intelligent-process-automation-market
MarketsandMarkets (2025). "Industrial Control & Factory Automation Market Size, Share, Industry Report, Revenue Trends and Growth Drivers." Retrieved from https://www.marketsandmarkets.com/Market-Reports/factory-industrial-automation-sme-smb-market-541.html
Straits Research (2024). "Industrial Automation Market Size & Outlook, 2025-2033." Retrieved from https://straitsresearch.com/report/industrial-automation-market
Data Bridge Market Research (May 2025). "Industrial Automation Market Size, Share, and Trends Analysis 2032." Retrieved from https://www.databridgemarketresearch.com/reports/global-industrial-automation-market
Precedence Research (July 2025). "Industrial Automation Market Size 2025 to 2034." Retrieved from https://www.precedenceresearch.com/industrial-automation-market
Precedence Research (August 2025). "Manufacturing Automation Market Size to Surpass USD 34.28 Bn by 2034." Retrieved from https://www.precedenceresearch.com/manufacturing-automation-market
ColorWhistle (September 2025). "AI Workflow Automation: Best Case Studies Across Industries." Retrieved from https://colorwhistle.com/ai-workflow-case-studies/
SuperAGI (June 2025). "Case Studies in AI Workflow Automation: Real-World Examples of Process Optimization and Efficiency Gains." Retrieved from https://superagi.com/case-studies-in-ai-workflow-automation-real-world-examples-of-process-optimization-and-efficiency-gains/
ExpertBeacon (n.d.). "30+ Intelligent Automation Case Studies / Success Stories In 2025." Retrieved from https://expertbeacon.com/intelligent-automation-case-studies/
AboutAmazon (October 2024). "Amazon has more than 1 million robots that sort, lift, and carry packages—see them in action." Retrieved from https://www.aboutamazon.com/news/operations/amazon-robotics-robots-fulfillment-center
Robotics and Automation News (July 2025). "Amazon hits 1 million robots as AI transforms warehouse operations." Retrieved from https://roboticsandautomationnews.com/2025/07/02/amazons-relentless-march-towards-total-global-roboticization/92818/
IEEE Spectrum (April 2025). "The Future of AI and Robotics Is Being Led by Amazon's Next-Gen Warehouses." Retrieved from https://spectrum.ieee.org/amazon-ai-robotics
Fortune (February 2025). "Amazon's big bet on warehouse robots is already getting a boost from generative AI." Retrieved from https://fortune.com/2025/02/19/amazons-big-bet-on-warehouse-robots-is-already-getting-a-boost-from-generative-ai/
PEX Network (February 2025). "Amazon automation & robotics." Retrieved from https://www.processexcellencenetwork.com/automation/news/amazon-automation-robotics-warehouse-efficiency
Wikipedia (December 2025). "Automation." Retrieved from https://en.wikipedia.org/wiki/Automation
Progressive Automations (July 2025). "Timeline History of Automation - How Automation Was Evolving." Retrieved from https://www.progressiveautomations.com/blogs/news/the-evolution-of-automation
Britannica (July 1999). "Automation | Technology, Types, Rise, History, & Examples." Retrieved from https://www.britannica.com/technology/automation
ITIF (December 2025). "AI's Job Impact: Gains Outpace Losses." Retrieved from https://itif.org/publications/2025/12/18/ais-job-impact-gains-outpace-losses/
National University (September 2025). "59 AI Job Statistics: Future of U.S. Jobs." Retrieved from https://www.nu.edu/blog/ai-job-statistics/
SSRN (June 2025). "AI Job Displacement Analysis (2025-2030)" by Josephine Nartey. Retrieved from https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5316265
Zebracat (May 2025). "AI Replacing Jobs: 100+ Statistics for 2025." Retrieved from https://www.zebracat.ai/post/ai-replacing-jobs-statistics
DemandSage (September 2025). "73 AI Job Replacement Statistics (2025 Reports & Data)." Retrieved from https://www.demandsage.com/ai-job-replacement-stats/
TeamStage (February 2024). "Jobs Lost to Automation Statistics in 2024." Retrieved from https://teamstage.io/jobs-lost-to-automation-statistics/
SQ Magazine (October 2025). "AI Job Loss Statistics 2025: Who's Losing, Who's Hiring, etc." Retrieved from https://sqmagazine.co.uk/ai-job-loss-statistics/
Budget Lab at Yale (2025). "Evaluating the Impact of AI on the Labor Market: Current State of Affairs." Retrieved from https://budgetlab.yale.edu/research/evaluating-impact-ai-labor-market-current-state-affairs
AIMultiple (n.d.). "Top 30 Workload Automation Case Studies." Retrieved from https://research.aimultiple.com/workload-automation-case-studies/
FlowForma (November 2025). "Business Process Automation: Top 10 Use Cases in 2025." Retrieved from https://www.flowforma.com/blog/business-process-automation-use-cases
AIPRM (July 2024). "50+ AI Replacing Jobs Statistics 2024." Retrieved from https://www.aiprm.com/ai-replacing-jobs-statistics/
SEO.ai (n.d.). "AI Replacing Jobs Statistics: The Impact on Employment in 2025." Retrieved from https://seo.ai/blog/ai-replacing-jobs-statistics
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