Market Size of Service Delivery Automation Industry
Study Period | 2018 - 2028 |
Base Year For Estimation | 2022 |
CAGR | 28.20 % |
Fastest Growing Market | Asia Pacific |
Largest Market | North America |
Market Concentration | Low |
Major Players*Disclaimer: Major Players sorted in no particular order |
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Service Delivery Automation Market Analysis
The service delivery automation market is expected to register a CAGR of 28.2% over the forecast period.
- Automation enables digitally equipped enterprises or businesses to transform their service delivery and operations, bringing cost savings, accuracy, and increased productivity. It generates valuable data, facilitating smarter and faster decision-making by optimizing current processes and operations and predicting when, where, and how to provide new products and services.
- The market for service delivery automation is expanding due to the growing adoption of a digital workforce and the functional advantages of automation solutions for business process automation across various end-user sectors. Market vendors enhance their offerings by adding new features such as automation lifecycle management, workload management, credential management, SLA-based automation, Citrix automation, and new data APIs, attracting new industries looking for higher operational and security capabilities.
- Smart process automation, big data, IoT, integration with other tools, and an increase in the adoption of service automation tools are the primary factors driving automation's growth. Furthermore, automation can create many jobs, driving demand for skilled workforces in different industries.
- However, the need for more skilled professionals to develop and manage automation processes might hinder this market's growth as new technologies get introduced exponentially. There is a need to re-skill the aging workforce to keep pace with automation's evolution.
- The COVID-19 pandemic positively impacted the market as online retail sales increased. Furthermore, using artificial intelligence (AI) and machine learning (ML), innovation leaders and business pioneers can develop the best frameworks for everything from staffing to finance and development to production.