The effective use of IT resources to support business goals can be a game changer for any organization. But significant challenges delay the integration of transformative technology into business processes. Business owners often grapple with the frustrating reality of discovering IT issues impacting their operations only after customer complaints have arisen, leaving them with little opportunity to mitigate problems proactively. The lack of timely awareness hinders swift issue resolution and leads to a disconnect between the IT team’s efforts and the overall organizational business objectives. This disconnect is exacerbated further by the necessity of using multiple vendor support teams for problem resolution, siphoning time and resources away from core business functions.
The transformative potential of generative AI technology, along with strategic implementation and collaboration, can bridge the gap between IT and business objectives to drive continued success and ensure your organization delivers targeted business outcomes.
Breakthroughs in generative AI powered by large language models (LLMs) continue to inspire new solutions that help companies overcome these longstanding organizational challenges. These breakthroughs come hot on the heels of evolutionary leaps in IT and cloud technologies that enable enterprise businesses across industries to grow at scale, expand into new markets and find new pathways to success. Chief among these advancements is improvement in hybrid cloud technology, which makes it easier to deploy, manage and secure applications across multiple cloud environments.
However, an extensive hybrid cloud estate can quickly become a complicated one that IT teams must spend significant time observing to ensure security and operationality. Many organizational IT networks host tens of thousands of applications operating within their hybrid cloud network. With this many applications, it becomes a significant challenge for IT operations to focus on achieving desired business outcomes. Every application creates a signal that IT professionals need to observe and understand quickly to determine application and network health, so they can react if something negatively impacts business performance. In a complex hybrid cloud IT landscape, it is difficult to correlate IT operations to business outcomes and take proactive actions.
The gap between IT observability and stakeholder communication
IT teams observe and make decisions by using various application performance monitoring tools to determine the health of the many applications running throughout their IT and hybrid cloud ecosystem. Business leaders don’t have easy access to this crucial information (or the technical training needed to understand it), which often leaves them in the dark about IT complications and how they may impact day-to-day work and business goals. This communication disparity can lead to confusion and inefficiency in addressing critical issues.
Effectively conveying the impact of technical issues to relevant business stakeholders is a big challenge. Organizations struggle with tailoring communication to different business personas, as various stakeholders have varying technical expertise.
IT operations must be sure that different integrated systems and platforms remain comprehensively observable, which requires considerable effort and coordination. Establishing the appropriate key performance indicators (KPIs) to measure the effectiveness of observability efforts can also be challenging, as relevant metrics must demonstrate the value and impact of observability on business operations (which isn’t always clear from an IT context). IT operations must show how observability directly contributes to business success and outcomes.
Unlocking the potential of generative AI for IT solutions and business impact
Standard observability tools allow IT experts to monitor and analyze IT alerts to determine their relevance to the business. However, this process often lacks alignment with business priorities, leading to inefficiencies and miscommunication. Communicating the business impact of IT issues to the right stakeholders is a complex task, as business leaders require contextualized information to make informed decisions.
Despite these challenges, the application of generative AI offers a promising solution to help organizations maximize business value while minimizing negative IT impacts. IT operations can put generative AI’s flexibility (in terms of multi-domain and broader functionality around content generation, summarization, code generation and entity extraction) to the task of observing the network to inform IT experts about possible issues and IT events. Meanwhile, large language models can provide detailed, contextual insights to articulate and specify IT impacts on different segments of the business.
Generative AI helps bridge the gap by conveying IT alert information to the right business stakeholders in language they can understand, with relevant details. It can deliver personalized information based on the business persona, enabling stakeholders to understand how the issue will impact them specifically.
The generative AI solution uses LLMs to inform business users about the impact on their processes, pointing out what specific aspect of their process is affected. It can provide information such as the point of impact, the implications for their division or profit center, and the overall effect on the organization.
For example, suppose an interface between Salesforce and SAP goes down. In that case, generative AI can provide details on how the IT event occurred (such as an interface or data load issue) and identify every downstream process that could affect business outcomes. IT ops can then inform stakeholders of the problem using AI-generated, domain-specific language to help leaders on the organization’s business side comprehend the event’s context and potential impacts. Additionally, generative AI can offer workarounds or alternative steps for business users to continue operations if their standard processes are affected. This level of contextualized information allows business leaders to continue their operations smoothly, even in the face of IT challenges.
Leveraging generative AI for business-driven decision making
Generative AI using LLMs provides faster and more precise analysis. This allows organizations to transform IT operations by prioritizing business-driven decision making, which leads to more effective and efficient operations. Using generative AI to validate and prioritize IT issues based on their relevance to the business and providing personalized communication of IT issues to appropriate stakeholders further empowers business leaders in making informed decisions.
While a fully integrated solution is still under development, generative AI using LLMs facilitates a more feasible way of notifying business leaders with contextual information and providing possible resolutions beyond basic event notifications. Organizations can begin incorporating various tools and systems to harness these benefits today. Integration efforts can focus on incorporating generative AI into existing technologies (such as SAP, CPI interfaces, Signavio and Salesforce) to achieve targeted outcomes.
These integrations allow for a holistic view and effective handling of IT alerts across different systems. IBM Consulting offers integrations across various tools, and we can ensure an enterprise-wide solution beyond specific proprietary platforms.
Generative AI presents a transformative opportunity for organizations to maximize business value while minimizing negative IT impacts. Generative AI empowers organizations to make informed decisions and maintain smooth operations by aligning IT operations with business priorities, leveraging contextualized information and providing targeted workarounds.
Learn how to improve efficiency, enable faster issue resolution and enhance business outcomes
Partner, Americas Enterprise Applications Managed Services Leader
Associate Partner, Executive Architect, Data Scientist, AOT Member, RISE with SAP, IBM Senior Inventor
