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How IT can leverage AI for incident management

The integration of AI in incident management is not just about enhancing efficiency but also about revolutionizing user experience.

The consumer credit rating giant Equifax was fined $13.4 million on October 13, 2023, for its role in one of the most significant cyber-security breaches in history by the Financial Conduct Authority (FCA), Britain's financial watchdog.

The fine was imposed on Equifax for failing to protect the data of nearly 14 million UK customers. The exposed data included names, dates of birth, phone numbers, addresses, and some credit card details of UK consumers. 

The FCA called the incident “entirely preventable”.

To set some context, in 2017, Equifax suffered one of America’s largest data breaches that exposed the personal information of 147 million US citizens. 

That’s roughly 40% of the country’s population. 

The reasons for the hack – a known server vulnerability issue, an outdated email list, and an expired digital certificate.

Equifax had notified its sysadmins to patch the issue, but the person responsible did not get the message because Equifax’s email list was out of date. Additionally, an expired digital certificate allowed malicious network activity to stay hidden. The attack lasted about 76 days before it was discovered.

The result?

$1.7bn in legal settlements and other costs. 

Equifax lost $5.3 billion in market valuation as its stock price fell by 31%.

Entirely preventable.

While it’s easy to speculate, one can only imagine if this incident could have been averted with the help of AI. 

AI is increasingly playing a crucial role in shaping and modernizing IT Service Management (ITSM). The integration of AI in ITSM processes like incident management is not just about enhancing efficiency but also about genuinely revolutionizing how ‘traditional’ IT services are delivered.

How can AI help with incident management? 

Incident prevention

By analyzing historical data, ML algorithms can predict and even prevent incidents before they occur. Without human intervention, these ‘self-healing’ systems can detect and resolve incidents automatically. Self-healing systems are designed to identify anomalies, errors, or failures and initiate corrective actions autonomously. This reduces downtime, enhances system reliability, and minimizes the need for continuous human monitoring and intervention.

Conversational IT support

AI can comprehend users' queries in natural language without needing the usual keywords or phrases that traditional systems need. This helps understand the user's actual needs and issues and, most importantly, on the platform of their choice instead of one specific portal.

Once the user's query is understood, a GenAI assistant can tap into the right resource: a knowledge base, chat history, or even transcripts from past support calls and provide a natural language solution. 

The thing to note is that the AI assistant is constantly learning. Over time, it will be to handle and deflect trivial and repetitive issues that IT support agents often find monotonous and time-consuming. The AI agent thus frees up human agents to focus on more complex and challenging problems.

24/7 support

We recently conducted a study across IT professionals and end users to understand how they feel about their IT teams. One of the things we asked end-users was what they’d like their IT team to start, or stop, doing. One of the most popular answers was “Provide 24/7 support”.

Another noteworthy insight from the study was that “Let me fix IT issues myself” ranked among the lowest. So, if driving self-service is in IT’s best interest, it would benefit them to give employees a natural and human-like experience. AI can help do this at scale while being available around the clock.

Faster resolution

The AI assistant can quickly solve L1 issues and route the problems that require a human agent's involvement, thus resulting in faster resolution. Even if the issue is escalated, the bot can be used for incident triaging and routing, thereby ensuring that the incident is rightly categorized and prioritized. The bot can also determine the best-suited agent to handle the issue. This streamlining results in faster resolution. 

The AI bot can provide human agents with detailed insights and relevant information by analyzing past instances of similar issues and suggesting potential solutions. This speeds up resolution and also enhances the quality of support provided to the user.

Finally, the bot can also summarize call transcripts or text-based conversations into concise notes, significantly reducing the time agents spend on the task. The AI can highlight key issues discussed, steps taken, and solutions provided, making the documentation process more efficient and accurate.

Upskilling IT teams with AI

AI can analyze vast amounts of data, identify emerging trends, and provide insights. These insights include identifying new threat patterns, technology trends, or operational efficiencies and will help IT teams foster a culture of continuous learning. 

Furthermore, AI can help create personalized learning pathways for IT professionals by analyzing an individual’s current skills, past learning history, and the evolving needs of the IT landscape. This learning can be further accentuated with a hands-on approach by generating realistic simulations and scenarios that mimic emerging challenges in the IT landscape. 

Finally, as incident management practices evolve with new technologies and methodologies, AI can help IT professionals stay updated on best practices by assisting them to understand new security protocols and learn about innovative technologies.

Conclusion

AI can make a world of difference for the IT team, especially incident managers, to not only improve efficiency, but also enhance the quality of the IT services and user experience.

It's important to approach things with a user-centric mindset while focusing on the outcomes that AI can help you achieve, rather than sticking with traditional processes and tacking on AI as an afterthought.

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