AI in IT: The Future of IT Operations

Suzanna Daniel
June 7, 2023
min read
November 27, 2023
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Discover how AI in IT is revolutionizing operations. Simplify complex tasks, automate workflows, enhance cybersecurity, and optimize operations.
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A new technological revolution is happening in 2023. Artificial Intelligence (AI) is completely changing how businesses (and individuals) operate, innovate and give value. 

Although the technology was first invented in the 1940s to 1960, AI recently gained mainstream popularity — and keeps evolving.

This article will discuss how AI impacts the IT industry, some of its real-time applications today and how your business can benefit from it to drive growth and profitability.

This article is one chapter in our expert Generative AI User Guide. Check out the rest of the chapters below:

Chapter 1: What is Generative AI?
Chapter 2: AI Applications
• Chapter 3: Best Generative AI Tools
• Chapter 4: What are the Benefits of AI?
• Chapter 5: Best AI Writing Software
• Chapter 6: Winning Examples of AI Used Today
• Chapter 7: Best AI Tools for Productivity
• Chapter 8: How AI is Used in Business
• Chapter 9: AI Tools for Businesses
• Chapter 10: No Code? No Problem. Here are the Top No-Code AI Tools
• Chapter 11: How IT Teams Use AI
• Chapter 12: Best AI Tools for Developers
• Chapter 13: AI and the Future of Work


  • AI is revolutionizing the information technology industry by simplifying complex tasks and working with robust datasets.
  • AI applications in IT include process documentation, workflow automation, data and cybersecurity, data analytics, software development, service management and social media.
  • The benefits of AI for IT teams include task automation, better decision-making, streamlined and optimized operations, predictive analysis for incident management, predictive maintenance for asset management, enhanced customer experience, and cost reduction.
  • Scribe's AI-powered process documentation tool can help transform your IT operations.

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‎AI‎ applications: How AI is used in IT operations

AI is an advanced technology trained to model human behavior. Its primary selling point is its ability to simplify complex tasks to improve productivity and efficiency, with a sophisticated ability to process massive datasets.

AI has found many applications in the IT industry, transforming various aspects of:

  • Software development.
  • Data analysis.
  • Automation.
  • User experience operations.

Let's explore how AI is currently being used in IT operations.


1.‎ AI in process documentation

Business documentation is essential for most in the IT sector. Still, proper documentation is complicated for these companies for different reasons.

Sometimes the process can be manual and lengthy. Other times, only a few people know the rules and have to explain them to others—which isn't sustainable.

AI-powered tools can streamline the documentation process by translating technical documentation into different languages or even localizing documentation by adapting it to the cultural contexts of a region.

AI can also assist in making sure that IT teams create quality documentation adhering to industry standards and regulatory compliance. AI-powered algorithms also help provide intelligent search and retrieval to make it easier to find search results instead of spending so much time scanning through endless documentation repositories.  

It is also possible to fully automate the process of creating documentation. All you have to do is install an extension, click a button to capture your process and get a fully documented procedure.

How? Use Scribe to automate process documentation.


Scribe is the go-to tool for creating SOPs, user guides, manuals, tutorials, or technical documentation. The AI-powered tool is designed to boost productivity and team efficiency by helping you create step-by-step guides for any process in seconds.

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See how it works for yourself. Here is a Scribe made in 21 seconds that shows you how to make GitHub Repository Public.

How to Make GitHub Repository Public - AI in IT


‎2‎. AI in workflow automation

AI plays a critical role in workflow automation by enabling businesses to automate specific or even all aspects of their operational processes, saving time and extra costs.

This technology is key for companies with process complexity. They can hire fewer employees to do the same tasks or have employees focus on tasks that require creativity, ingenuity and originality.

For example, AI chatbots automate workflow processes like incident management when users experience challenges utilizing a product or service and with a faster turnaround time than humans.

AI can also automate inventory management processes, tracking and monitoring the usage and lifecycle of all business inventories. This reduces the risks of human errors more likely with manual entries.

There are many other process automation applications in the IT industry today, from HR to quality control to production processes. AI workflow automation completely streamlines and optimizes all aspects of business processes.

3.‎ AI in data & cybersecurity

The IT industry thrives on collecting and processing a lot of private data that must be kept secure and protected at all times.

The challenge is that many bad actors want access to this data to perpetuate cybercrimes and fraudulent activities.

No business wants this outcome, so AI technology is used to build a secure system and promote cybersecurity practices to fight fraud.

Many IT companies now use machine learning algorithms to:

  • Detect suspicious activities.
  • Identify patterns that indicate cyber threats or data breaches.
  • Defend against them.
  • Reduce the risk of attacks.

4.‎ AI in data analytics

AI technology also plays a vital role in data analytics by:

  • Enabling organizations to analyze data faster and more accurately.
  • Uncovering patterns, trends and correlations that are sometimes not easily identifiable by humans.

AI technologies like machine learning (ML) and natural language processing (NLP) are used to make meaningful insights from data to drive innovation quickly, inform strategic initiatives and drive business growth.

5. AI‎ in software development

Quality assurance during software development is another common application of AI in the IT industry. Before this, testing software was a tedious and manual process and took more time because it required human testers.

With AI-powered machine learning algorithms, the process can now be automated, with increased test coverage and reduced need for manual effort.

Developers can also use AI tools to:

  • Perform code reviews and bug detection tasks.
  • Automatically detect coding errors.
  • Write cleaner codes.
  • Identify security vulnerabilities.
  • Provide recommendations for improvement.

NLP techniques also help software developers, engineers and IT professionals extract information from technical documents, API documentation and user guides, giving them access to contextual documentation relevant to their work.

6.‎ AI in service management

Customer support and management teams use NLP to help computers understand and interpret human languages and translate these languages worldwide.

Tasks like language translation and transcribing can be simplified, allowing for efficient use of chatbots and speech recognition features to understand and respond to customer queries in real time.

This technology is widely used by creating popular virtual assistants available on mobile devices, like Amazon's Alexa and Apple's Siri. These assistants can understand and respond to voice commands and offer personalized responses to help users solve problems or simplify tasks.

Customer support AI tools also have many other applications, like:

  • Intelligent problem resolution.
  • Analyzing customer behavior and sentiment analysis.
  • Helpdesk and customer service automation.
  • Predictive analysis for incident management to help identify patterns, correlations and potential root causes.
  • Recommending relevant self-help options and knowledge base articles to agents or users when needed.

‎7.‎ AI in social media analysis

Machine learning (ML) is a subgroup of AI technology that enables computers to learn patterns and make predictions without being programmed.

On many social online platforms, ML technology is used to create personalized marketing, handle image recognition and manage fraud detection on a large scale.

Social media platforms like Tiktok, Instagram and Snapchat use this technology to analyze user behaviors, preferences and interactions to:

  • Create recommendation engines that show users more personalized digital content.
  • Perform video and image processing to assist in content filtering and visual content search.
  • Identify emerging market trends, topics and hashtags.

With computer vision, another AI technique, computers can interpret visual information from images or videos, detect objects, classify pictures, perform facial recognition, and create augmented reality. These technologies are widely used today when shopping online or scrolling on your favorite social media applications. 

Deep learning has revolutionized computer vision by enabling machines to recognize objects, detect patterns, and even understand complex scenes. With deep learning, AI-powered systems can now accurately analyze visual data, leading to advancements in fields like autonomous vehicles, surveillance and medical imaging.

Wh‎at are the benefits of AI in IT?

As AI technology innovations increase daily, at least 44 percent of businesses plan to integrate AI into their operations. Here are a few ways AI is transforming business operations.

1. Task automation

The greatest asset to any business is time. AI helps companies gain more time to focus on other core operations. One of these ways is through routine and repetitive tasks automation, enabling organizations to achieve new levels of efficiency.

For many developers, engineers or IT professionals, AI tools are taking out long hours spent on necessary yet painstakingly repetitive tasks.

Now, they can block out all the noise,  processing information to give better outputs faster. All of these allow productivity levels to increase.

2. Better decision-making

Deciding on the next ''right'' business decision requires lots of data—and time to analyze that data.

ML shortens this process and makes it more accessible. Businesses can now quickly observe, gather and analyze large amounts of data to influence product development, go-to-market strategy and even revenue predictions.

For example, a company may quickly perform deep analysis on large amounts of data with AI to determine if a product is doing well, gaining mass user adoption or tanking without manually counting these numbers.

And the insights drawn from this can impact their next steps. Maybe they can decide to pull the product out of the market or run a survey to determine why adoption is low.

3. Streamlines & optimizes business operations

There's so much that goes on in IT operations. AI technology enables businesses to bring it all into one organized place for efficient IT operations management. Teams can get a holistic, real-time view of systems and operations.

For example, if an application has issues, AI operation tools can quickly determine what's causing the slowdown and suggest ways to boost its performance. The technical team can fix things before they affect the user.

4. Predictive analysis for incident management 

AI enables businesses to come up with actionable strategies by leveraging predictive analytics.

Predictive analytics is an AI technique that analyses past incident and operational data, including large amounts of information from performance metrics, system logs, network traffic, and events.

Predictive analytics find patterns that can point out anomalies before they happen and provide recommendations for preventing them.

If the issue is recurring, you can use AI to automate actions to resolve them.

Deep learning algorithms, such as recurrent neural networks and long short-term memory (LSTM) networks, have also proven to be highly effective in time series forecasting and predictive modeling. Deep learning is a subset of machine learning that focuses on training artificial neural networks to learn and make decisions on their own.

By analyzing patterns and trends in data, deep learning models can make accurate predictions in various IT applications, such as demand forecasting, network traffic prediction, and system performance optimization.

5. Predictive maintenance for asset management

Traditionally, companies had to stick to a fixed maintenance routine and often experienced unplanned downtime or resource allocation to resolve the issues.

With AI technology, IT teams can minimize disruptions and reduce the risks of unexpected failures or breakdowns to IT infrastructure by using AI algorithms to forecast potential hardware failures.

6. Enhancing customer experience

Customer service and experience can be complex. Many businesses can't afford to hire enough customer attendants to answer all queries. Even if they're fully staffed, there's still a high risk of human error. This leads to frustrated customers, extended customer service times and high churn rates.

With AI technology, companies can now provide 24-hour instant support, answer customer queries and offer recommendations based on individual preferences without human interference, thanks to chatbots and virtual assistants.

AI-powered virtual assistants guide customers through self-service options so they can resolve their issues independently. When a customer experiences a challenge after work hours, they can find a solution quickly and more independently instead of waiting for business hours.

Companies can also use it on various communications channels, websites, mobile apps, and platforms and—even better, handle customer requests in their preferred format, like live chat, voice assistance or article recommendation.

7. Cost reduction

AI outperforms humans in terms of precision and accuracy on error-prone tasks. Businesses can now identify inefficiencies, and automate data processing and manual tasks using AI tools. AI can keep operational costs low and encourage increased revenue growth.

For example, predictive AI can help IT companies save money on buying excessive inventory or hiring more maintenance personnel than they need.

AI‎ in IT will continue to evolve

These advancements are just the tip of the iceberg of what is to come, and soon companies using AI will be better positioned than those that don’t.

The scope and magnitude of what is possible with AI will also increase. We can't wait to see how this innovation will advance the IT industry.


What is AI used in technology?

Artificial Intelligence (AI) is used in technology to automate tasks, improve decision-making and enhance overall performance.

  • In IT, AI is used to automate repetitive tasks such as data entry, system monitoring and software testing.
  • AI algorithms can analyze large volumes of data and provide insights and recommendations to help IT professionals make informed decisions.
  • AI is used in IT to continuously monitor infrastructure, detect anomalies and predict potential issues before they occur.

How is AI used in information systems?

Artificial Intelligence (AI) is used in information systems to enhance capabilities and improve decision-making processes.

  • AI technologies such as machine learning, natural language processing, and data analytics are integrated into information systems.
  • AI algorithms can analyze large volumes of data, identify patterns and provide data-driven decisions.
  • AI is utilized in natural language processing (NLP) to interact with users in a more natural and intuitive way.
  • AI is used in anomaly detection and cybersecurity to identify suspicious activities and enhance system security.

Tr‎ansform your IT operations with AI

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