Efficient IT operation scaling is a challenge businesses need to overcome if they wish to keep up with evolving trends and stiff competition. Relying on static resource allocation, manual processes, and other traditional IT management methods is no longer adequate. Enter AI and its transformative ability to streamline workflows and optimize resource usage.
Read this article as we explore AI automation’s impact on scaling efforts within IT operations and examine what measures you should take for secure AI integration.
How Can AI Automation Tools Impact IT’s Scaling and Productivity?
AI is becoming integral to almost every facet of IT operations. As such, its ability to streamline workflows and reduce human error is widespread and diverse. Here are just some of the most beneficial use cases.
Rote task automation
System monitoring, patch management, and ticket prioritization are critical for maintaining the stability and efficiency of IT operations. Yet, they’re repetitive tasks you should automate. By doing this, you will free your team to direct their expertise and creative problem-solving skills toward more complex issues.
Resource optimization
Inadequate resource allocation can result in overworked IT team members, under or over-utilized infrastructure, and long project development cycles. Tasking the right automation tools with resource optimization can mitigate this problem.
On the one hand, they can allocate just enough system resources like central processing unit power and network bandwidth for each project. On the other, optimizing work schedules and task distribution balances workloads while accelerating project timelines.
Streamlined IT support
Simple queries take up much of any help desk’s time and resources. AI-powered virtual agents with natural language understanding capabilities can handle initial internal and external support. Integration with the backend allows them to perform tasks like service request logging or ticket escalation.
Cloud cost optimization and capacity planning
Cloud services are costly as is, and companies spend even more because of inefficiencies. Automated cloud cost handling takes usage patterns into account, identifying these inefficiencies and proposing cost-saving measures.
Moreover, AI automation can make your capacity planning strategy proactive. Rather than relying on thresholds, it can recommend needed upgrades based on current and predicted resource consumption, seasonal spikes, etc.
AI Automation’s Cybersecurity Implications
While it’s tempting to enthusiastically embrace as many AI automation tools as your operations can benefit from, there are risks to consider.
Secure access to AI tools
Keeping AI tools and their associated accounts from becoming vulnerable access points that increase the likelihood of data breaches is a priority. Doing so involves ensuring each team member has strong, unique credentials for every AI account they use. This practice mitigates brute force and credential-stuffing attacks while limiting potential compromises to single accounts.
A password manager for IT teams can be a good solution to prevent risks associated with accounts by generating and storing secure credentials inside encrypted vaults. It’s also possible to use password managers to set up role-based access controls, limiting low-level team member exposure to the most sensitive accounts.
Moreover, password managers allow for secure temporary credential sharing and autofill without exposing account information. Finally, advanced password managers offer two-factor authentication to keep compromised credentials from escalating to account takeovers.
Vulnerability assessment and identification
Each AI automation tool represents a third-party asset you’re integrating into your operations and workflows. You have no control over the safeguards their developers implement, and hackers may exploit popular yet poorly secured tools to gain access to your assets.
Threat intelligence tools or management platforms are an effective and proactive countermeasure. These tools continuously monitor your infrastructure and the underground forums of the Internet for emerging threats. Consequently, this lets them notify you of misconfiguration issues and impending attacks, allowing for timely and appropriate responses.
Conclusion
Integrating AI automation into business IT automation is both logical and inevitable. Hopefully, this balanced overview of associated benefits and risks will help you do so responsibly.
