According to the Forbes Advisor, two of the biggest operating costs for smaller organizations come in the form of labor and inventory management, which take about 70% and 25% respectively.
If we look at the numbers from a larger perspective, it is understandable that businesses are looking for an effective way to reduce labor costs.
And that is where the ServiceNow shines best.
So, how is ServiceNow going to improve the probability of reducing the organizational operating costs? Well, the answer lies in the latest technology, AI, particularly “Intelligence Automation.”
In this article, let’s take a closer look at how ServiceNow Intelligence Automation works and how it can help you reduce operational costs.
Jump to any section to learn more about ServiceNow Intelligence Automation:
What is Intelligence Automation?
On a high level, Intelligence automation (IA) is an enhanced version of the automation process with built-in intelligence.
Usually, most automation is limited to simpler tasks. That changes significantly when you integrate with AI and machine learning.
With the help of AI integrated with automation, businesses can create end-to-end processes that can learn and adapt on their own.
This drastically improves the turnover rate for a task and ultimately helps streamline the decision-making process.
Intelligence Automation in ServiceNow
As a workflow automation platform, ServiceNow uses intelligent automation in its modules to create a comprehensive service operation that will surely improve productivity, reliability, and adaptability.
In ServiceNow IT Service Management (ITSM), intelligent automation significantly assists businesses in identifying service-related issues across the enterprise. It can then suggest the appropriate remediation workflow to resolve the issue.
This reduces complexity into simplicity, meaning workers can now focus on more important tasks rather than the issues that can be easily resolved by the technology.
What ServiceNow Intelligence Automation Made Of?
The term hyper automation is synonymous with intelligence automation denoting the next iteration in the automation process.
IA is not a single entity but a cumulation of several technologies ranging from AI to otros (other technologies). There are two main core components and they are as follows:
Artificial intelligence (AI)
- Machine Learning (ML) – Algorithms that make systems learn from data, identify patterns, and make decisions with minimal human intervention.
- Natural Language Processing (NLP) – Allows systems to understand and process human language, and carry out tasks like text analysis, sentiment analysis, and conversational interactions with chatbots or virtual agents.
- Computer Vision – Enables systems to interpret and make decisions based on visual input from the world, such as images or videos.
- Low-code Platform – Empower citizen developers to create applications and automate processes with minimal coding effort, often through a drag-and-drop interface.
Automation Tools
- Robotic Process Automation (RPA) – Software bots that mimic human actions to automate repetitive tasks across various applications, such as data entry or transaction processing.
- Business Process Management (BPM) – Tools and methodologies for modeling, automating, and optimizing business processes, often serving as the backbone for automated workflows.
- Workflow Automation – The use of software to design, execute, and manage workflows, ensuring tasks are automatically routed to the right individuals or systems for action.
Otros Technologies
- Cognitive Computing – Systems that simulate human thought processes to interpret complex data and provide actionable insights, often used in decision support systems.
- Intelligent Document Processing (IDP) – Tools that use AI to extract and process data from documents, enabling automation of tasks like invoice processing, contract analysis, and form handling.
How ServiceNow Intelligence Automation Works
1. Data Collection and Integration
- Event Logs and Data Sources – ServiceNow IA starts to collect data from various sources, including your IT systems, applications, and user interactions. This data is stored in the platform’s event logs and other databases, known as Configuration Management Database aka CMDB.
- Integration with Third-Party Tools – ServiceNow IA integrates with other enterprise systems and tools through APIs, connectors, and integration hubs, ensuring a seamless flow of data across the organization.
2. AI and Machine Learning Capabilities
- Predictive Intelligence – ServiceNow AI models analyze historical data to predict future outcomes. For instance, it can predict incidents or service requests that are likely to escalate and suggest proactive measures.
- Natural Language Processing (NLP) – NLP enables ServiceNow to understand and process human language. This is used in chatbots, virtual agents, and text analytics, helping to automate responses and improve user interaction.
- Machine Learning Models – These models learn from past interactions and data, continuously improving the accuracy of predictions and recommendations.
3. Workflow Automation
- Automated Workflows – ServiceNow allows users to design automated workflows that handle routine tasks without manual intervention. For example, it can automatically route service requests to the appropriate team based on predefined criteria.
- Robotic Process Automation (RPA) – ServiceNow can deploy software robots to mimic human actions, such as data entry or updating records, across various systems and applications.
4. Decision Automation
- Business Rules and Logic – ServiceNow uses business rules to automate decision-making within workflows. These rules are predefined conditions that trigger specific actions, such as approving a request or escalating an issue.
- AI-Driven Decisions – AI algorithms analyze data in real-time and make decisions that optimize processes. For example, AI can prioritize incidents based on their potential impact on business operations.
Self-Healing Systems
- Automated Remediation – When an issue is detected, ServiceNow’s automation engine can trigger corrective actions automatically. For instance, it might restart a service or apply a configuration change to resolve an IT incident without human intervention.
- Proactive Maintenance – ServiceNow’s predictive analytics can identify potential failures before they occur and trigger maintenance tasks automatically, reducing downtime and improving system reliability.
Value Add-Ons You Get By Implementing ServiceNow Intelligence Automation (Industry Wise)
| Industry | Value Add-Ons You Get |
|---|---|
| IT Services and Technology |
|
| Banking |
|
| Healthcare |
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| Manufacturing |
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| Telecommunications |
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| Retail |
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| Government and Public Sector |
|
Key Takeaways
What if, organizations can reduce the operational cost considerably and at the same time not reduce the workload?
The answer is, that it is possible with the ServiceNow Intelligence Automation. But at the same, it may not be enough to justify the layoffs happening around the world.
Fortune did a piece on the AI impact on jobs and it says that by 2027, around 5.9 million new jobs could be created in the West and possibly more around the world, thanks to the new technologies powered by AI.
AI cannot fully take over human tasks but to enhance our current technology, it is in our best interest to embrace AI and bring about “AIvolution.”
LMTEQ, being the frontrunner in from ServiceNow Implementation to managed and support services, our ServiceNow-certified experts are ready to transform your business with AI.
Connect with our ServiceNow experts now.