Ten ways AI can improve IT efficiency

Every IT leader wants to build an efficient organization. Artificial intelligence is ready to help.

When it comes to maximizing productivity, IT leaders can turn to a range of motivating factors, including regular breaks, free snacks and drinks, workspace upgrades, mini-competitions, and more. However, there is now another cutting-edge tool that can significantly increase your team's productivity and innovation: artificial intelligence.

Jeff Orr, head of digital technology research at ISG's Ventana Research, said any repetitive task or activity that can be standardized on a checklist can be automated through AI. "IT team members tend to have a better experience when they engage in meaningful activities," he noted. "Better employee engagement leads to employee retention."

How can AI help your IT team members become more creative and productive? Take a look at the 10 ideas below.

1. Provide more scenarios for alerts

Receiving an error text message that simply states "something went wrong" usually requires IT staff to check the logs and determine the problem. This is very inefficient, Orr said. Software that incorporates observability technology, powered by generative AI, can intuitively trace the source of the error information and provide recommended steps to address the cause.

"This approach to better information can benefit IT teams in most areas, from e-commerce store errors to security risks to connectivity breaks," he said.

2. Create a self-service option

Leveraging AI to automate existing processes provides a powerful new self-service tool for the enterprise sector. For example, onboarding a new employee follows a series of known processes, such as location, role, working hours, and more, Orr said.

"Creating employee credentials and access, pre-configuring security settings, and getting employees ready for their first day on the job all require human intervention," he added.

3. Scale more efficiently

Alok Shankar, AI engineering manager at Oracle Health, said AI can automate a range of routine tasks, ensuring consistent operations across the entire IT infrastructure. "This scalability allows you to scale your business without having to scale your IT team."

Shankar noted that AI can also provide IT teams with data-driven insights to optimize resource allocation, prioritization and future planning. Easy access to continuous improvement is another benefit of AI growth. "Many AI systems use machine learning, constantly learning and adapting, becoming more effective over time," he said.

4. Identify potential problems

By analyzing large amounts of data, AI can identify potential technical and security issues before they escalate into system outages.

"This proactive approach minimizes downtime and keeps the system running smoothly," Shankar said. "With AI's lightning-fast processing speed, you can pinpoint and resolve issues quickly, reducing the impact on your business."

5. Improve the ticketing system

Machine learning scientist Justin Halff, an engineering services company? Justin Roberts said that adding AI to service management processes, especially automated ticketing systems, can greatly improve employee productivity.

Roberts noted that AI can automatically classify, prioritize and route tickets. "It can analyze impending problems and use historical data to make recommendations and even implement solutions without human intervention," he explained. "For complex problems that require human attention, AI can prepare a detailed background (report), which greatly reduces the time to resolution."

6. Speed up business processes

Jim Liddle, CIO of hybrid cloud storage provider Nasuni, said that by infusing AI into business processes, businesses can achieve productivity, efficiency, consistency and scale that would have been unimaginable a decade ago. He observes that mundane repetitive tasks such as data entry and collection can be easily handled around the clock with intelligent AI algorithms.

"Complex business decisions, such as fraud detection and price optimization, can now be made in real-time based on large amounts of data." Workflows that took days or weeks can now be completed in hours or minutes. ”

At its core, AI is about automation, including tasks, workflows, and decisions that previously required human effort. "Businesses have long sought to increase efficiency and scale through automation, first with simple programmed rules systems and later with more advanced algorithmic software," Liddell said. Now, innovations in machine learning and artificial intelligence are driving the next generation of intelligent automation. ”

7. Cut back on repetitive work

Enrique, head of data at Loka, a data science and software development company? Ribeiro? Delgado? According to Da Silva, AI can significantly improve the productivity of IT teams by controlling routine tasks and optimizing processes.

"By reducing templates, teams can save time on repetitive tasks, while automated and enhanced documentation can keep pace with code changes and project development." He points out that AI can also automate the creation of pull requests and integrate with project management software. In addition, AI can generate suggestions to fix bugs, suggest new features, and improve code reviews.

Teams looking to automate routine tasks should use tools like ChatGPT to write simple examples and GitHub Copilot to provide coding assistance. "This approach works because it's fast, requires very little effort to achieve satisfactory results, and is scalable enough to handle projects of varying size and complexity," daSilva said.

8. Enhance the observability of ITOps

As businesses seek zero downtime and lower IT running costs, IT operations teams find themselves in an urgent need to improve and adapt quickly to meet changing demands. To help meet performance goals, AI operations are now moving toward unified observability, shifting IT operations from traditional reactive monitoring to proactive IT management, said EfrainRuh, field CTO at Digitate, a provider of AI and automation software.

Ruh believes that AI will take ITOps observability to the next level by providing the ability to analyze large data sets, identify patterns, detect anomalies, correlate, predict, and even predict problems. All of these benefits promise to give IT teams extra time to focus on more complex issues.

AI can also identify hidden dependencies, capture normal behavior, and perform impact analysis. "In the event of a system failure or anomaly, AI can help IT teams respond automatically, which can have a significant impact on system availability and performance," Ruh noted.

When planning an AI-based ITOps observability initiative, Ruh suggested bringing together teams responsible for IT management, platform management, tools, and security to collaborate. "It's important to start with the right expectations and do it in phases with different teams."

9. Automated monitoring and maintenance

According to Aravindh Manickavasagam, Advanced Technical Software Product Manager at Instacart, AI can significantly improve the productivity of IT teams by automating routine monitoring and maintenance tasks. "Leveraging AI-driven predictive maintenance can help teams anticipate potential system failures and mitigate them before they cause any major downtime," he explained. AI can automatically generate reports, system updates, and even handle first-level customer support queries through chatbots. ”

According to Manickavasagam, AI can reduce the operational overhead of IT teams, allowing members to focus on strategic and complex tasks that require human intervention. "Automating routine tasks with AI not only increases efficiency but also reduces the potential for human error, while increasing system uptime and improving overall service quality," he said.

As with any AI program, the program team should include IT managers, system architects, data scientists (to assist with AI model training and integration), and end users (to get feedback). "The involvement of executive leadership ensures that the project is aligned with broader business objectives and that the necessary support and resources are available," Manickavasgam noted. ”

10. Speed up coding

Pavel Torbin, COO and co-founder of data management and machine learning solutions provider Arc53, said the AI co-pilot tool provides intelligent completion capabilities that can greatly speed up coding tasks. "Unlike earlier systems that only suggested a single word, today's AI co-pilot can suggest entire features, greatly reducing coding time and error rates."

Looking ahead, Torbin expects significant progress in AI tools to address dependency management and code translation issues. He also believes that as IT infrastructure evolves, AI can automate and secure the update process, reducing the risks associated with relying on obfuscation attacks. AI will play an important role in transforming legacy software into a modern framework, facilitating a smoother transition while maintaining business continuity.

Torbin advises IT leaders to keep an eye on the accuracy of AI and be wary of "illusions" when a model suddenly starts giving confident but incorrect or irrelevant answers. "In addition, relying on artificial intelligence for all queries without regular verification by human experts could lead to misinformation becoming a norm in IT operations," he warned.

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