You may be familiar with the “productivity paradox,” the idea that increased investments in technology don’t always lead to a proportional increase in productivity. This concept was first identified by economist Robert Solow in 1987, who famously remarked, “You can see the computer age everywhere but in the productivity statistics.”
Sadly, the paradox remains true for many organizations today. The complexity of managing technology can often negate the expected time and resource savings. For instance:
- Lack of integration can create data silos and fragmented workflows
- Additional resources may be required for the upkeep and updates of technology
- Overlapping features can cause confusion rather than enhance efficiency
- Change management challenges can lead to resistance and hinder adoption
The rise of AI has only sparked renewed conversation about the productivity paradox, with experts citing mismeasurement, false expectations, unequal distribution, and lagging implementations as reasons AI often fails to live up to its hype and promises.
For businesses struggling to see productivity improvements from AI and other technology, enterprise orchestration is a powerful solution. By reducing the burden of managing complex technology systems, it helps companies unlock greater operational efficiency.
What is enterprise orchestration?
Enterprise orchestration is a strategy that connects and automates processes, data, and workflows across an organization’s systems, applications, and services.
Positioned as a layer above individual systems, it manages the interactions between microservices, APIs, and data pipelines. It ensures workflows are executed in the correct sequence, dependencies are managed effectively, and data is synchronized across platforms.
Key characteristics of enterprise orchestration include:
- System integration: Often achieved through API management
- Workflow automation: Triggers predefined actions across systems
- Dependency management: Ensures tasks and processes occur in the correct order by managing prerequisites and interdependencies
- Governance: Enforces security, compliance, and control
How to adopt agentic enterprise orchestration
AI agents can enhance enterprise orchestration, enabling something called agentic orchestration and allowing companies to automate tasks, trigger workflows, and make decisions in real-time, all without human intervention. These agents interact with systems via APIs, monitor conditions, and initiate actions autonomously.
For example, in a customer support scenario, an AI agent might automatically generate responses to common inquiries, route more complex support questions to the appropriate person, and escalate tickets when response times are delayed. This reduces the manual workload of managing interdependent support technologies and improves efficiency.
Moreover, AI-powered orchestration enables predictive automation. By analyzing historical data, machine learning models can anticipate potential issues, like supply chain disruptions, and trigger preemptive workflows to mitigate risks.
Workato for agentic orchestration
Workato is a powerful low-code/no-code platform that simplifies agentic automation by seamlessly integrating and automating business processes.
Pre-built connectors: With thousands of pre-built integrations for enterprise applications, Workato allows organizations to quickly integrate systems without custom coding.
Recipe-based automation: Workato uses “recipes”—modular automation scripts that connect apps and trigger workflows. These recipes support complex logic while remaining easy to create and manage, ensuring rapid deployment and flexibility.
Agentic orchestration: Workato integrates AI agents to autonomously manage workflows, make decisions, and trigger automated actions.
Data management and compliance: Workato provides robust tools for data governance, security, and compliance, essential for enterprise environments.
A key advantage of Workato is its versatility. For example, Workato’s Senior Solutions Consultant Sashikumar Kannappan, finds that many companies struggle with data orchestration despite having some kind of orchestration layer in place already.
“In the last decade, one of the most exciting changes in the data orchestration space has been the emergence of new tools like Fivetran, Stitch, and dbt,” he says. “Having worked closely with data and BI teams over the years, I’ve found that even with the adoption of these technologies, they’re still struggling with siloed data and fragmented systems.”
“This inability to perform configurations like filters or set conditions is a common downside of ‘one-click’ turnkey connectors. Businesses need a more flexible solution that allows them to easily extract data from niche software, and eliminate the need for human intervention.”
Learn more about how to use Workato for enterprise orchestration.
