Operationalizing AI for IT operations

Advances in artificial intelligence are rapidly transforming the IT operations landscape. According to Enterprise Strategy Group, 85% of organizations use or plan to deploy AI across many functional areas, including IT operations. Among its many benefits, AI can help ITOps teams:

• Improve operational efficiency.
• Accelerate incident management.
• Enhance observability and monitoring tools.
• Automate manual tasks so operators can focus on more important work.

AI has immense potential to transform how IT operations, service management, and infrastructure teams function. Adoption is the first step toward creating organizational change.

The importance of operationalizing AI in IT operations

To maximize the impact of AI investments, you must be able to operationalize them. Successfully operationalizing AI requires integrating solutions into day-to-day processes and systems in ways that deliver tangible business value.

Let’s say your organization is experiencing repetitive, costly IT outages that result in lost productivity due to unexpected downtime. Adopting an AI solution or system to help predict potential failures and trigger automatic alerts could help address this challenge. With unplanned downtime costing large enterprises an average of $1.5 million per hour, these solutions can also prevent massive revenue loss.

Operationalizing AI allows IT teams that once struggled under the weight of reactive, manual workloads to schedule maintenance proactively. Applying AI and automation to incident response can also significantly reduce the time required to detect, triage, and resolve incidents.

“By taking advantage of machine learning, automation, and artificial intelligence, we decrease the time it takes to identify the root cause of an incident,” explained Alvin Smith, vice president of global infrastructure and operations at IHG Hotels & Resorts. “This gives us more time to resolve the incident, reducing our MTTR and keeping our services running.”

Challenges to operationalizing AI

All the hype of AI comes with corresponding (and understandable) skepticism. In addition to privacy, security, and technical concerns, many organizations still need help identifying how to achieve tangible business value from these solutions.

AI is still new and unfamiliar territory, especially for the stakeholders responsible for showing benefits from their technology investments. It’s vital for AI product owners to regularly engage with these stakeholders to affirm and demonstrate its value. Showing tangible results can be daunting when you’re in the early phases of AI adoption and challenged by organizational and operational silos.

How BigPanda helps

BigPanda simplifies operationalizing AI using a business-value assessment framework that provides a structured approach to help you evaluate the platform’s efficacy. Two examples of the unique benefits of BigPanda’s approach to business-value assessment include the ability for you to:

• Benchmark your results against anonymized data from all BigPanda customers. These comparisons can help you identify gaps and highlight opportunities for operational improvements. This visual dashboard helps illustrate and compare your operational maturity to other companies. Share this dashboard information with stakeholders to demonstrate business impact and value.
• Assess organizational maturity and identify areas for operational improvement. The framework provides insights about where you need additional investments to support enrichment and correlation. These insights can also help identify process improvements that improve MTTR and operational efficiency and break down operational silos. You can compare this information with other BigPanda tickets and those from different systems and share these insights with leadership or teams for improved visibility.

Continuous innovation

BigPanda continuously focuses on innovation to ensure our platform offers the most up-to-date technological capabilities to support your organization. These innovations include the BigPanda Biggy AI, incident-management copilot.

“Our copilot not only uses machine-generated and historical data but is the first to leverage all sources of human-generated, institutional knowledge for AI-powered incident response,” said Jason Walker, chief innovation officer at BigPanda. “This broad spectrum of knowledge aggregated by BigPanda, known as the Unified Data Fabric, allows Biggy to deliver automatic, dynamic, and actionable insights to ITOps and ITSM teams as they investigate and respond to live incidents.”

Next steps

According to Gartner®, “It is essential that I&O leaders take advantage of the productivity benefits that generative AI offers, as well as chart a course to incorporate more use cases for I&O.” (Gartner Conference Agenda, Spotlight Track: Operationalizing AI, Gartner IT Infrastructure, Operations & Cloud Strategies Conference, 19-20 November 2024. GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved.)

Operationalizing AI in IT will become increasingly essential for long-term success. BigPanda will continue adapting to this changing landscape and trailblaze innovation paths to keep businesses running.

“BigPanda Generative AI empowers our ops teams by providing faster incident detection and independent resolution. The rapid, automated extraction of meaningful insights from our complex IT alert environment makes us better at L1 response and reduces escalations to our L2 and L3 experts.”

Jeremy Talley
Lead Operations Engineer, Robert Half International

• Watch “AIOps 101: Use GenAI to deliver context and remediate faster” to learn more about the benefits of AIOps for IT operations.
• Learn more about using AI to resolve incidents faster.