AI-powered automation is poised for significant advancements in 2025 as enterprises enhance their automation platforms with advanced artificial intelligence (AI) features. This integration promises substantial improvements in network troubleshooting, minimization of configuration errors, and overall workload management.
Historically, automation technology has been vital in managing the growing complexity of IT environments. Bill Lobig, vice president of product management at IBM Automation, emphasizes that 2025 will mark a turning point for AI initiatives, transforming AI-powered automation from an optional addition to a critical business necessity. Automation will be essential in tackling AI’s inherent complexity, allowing organizations to shift from maintaining AI applications to proactively identifying and resolving issues, thereby gaining a competitive edge.
As AI technologies evolve, businesses can expect to leverage AI to help detect patterns and trends in their data. This enhancement will improve the quality of insights drawn from various metrics and logs, addressing the challenges posed by increasingly complex hybrid cloud environments.
Enterprise Management Associates (EMA) further highlights the need for advanced automation in light of the complications introduced by hybrid and multi-cloud networking. They note that many network operations teams are overwhelmed by infrastructure complexity. By adopting AI and machine learning (ML) algorithms, organizations can enhance their network operations, enabling them to automate processes that resolve issues, optimize capacity, and ensure resilience.
Despite the evident benefits, the journey towards full AI integration varies among organizations. Research indicates that while interest in AI-driven automation is high, many companies still rely on traditional methods for network management. As a result, while there is potential for AI to alleviate configuration errors—which currently account for over 40% of network outages—full reliance on AI solutions may take more time.
Cisco asserts that intelligent automation tools have the capacity to dramatically improve network management by ensuring every action taken has traceability, thereby minimizing misconfigurations. This capability is vital, especially for businesses striving to mitigate risks associated with network outages.
The efficacy of these AI-driven automation tools will ultimately depend on where organizations stand in their digital transformation journey. Some companies still manage their networks with outdated manual processes, while others have adopted sophisticated automation practices.
Enhancements to network observability, notably through tools like Cisco’s ThousandEyes, further illustrate how automation can be pivotal. These tools are designed to provide real-time insights into network performance, allowing for swifter responses to any operational challenges.
As businesses move toward the future, the symbiosis of AI and automation represents a transformative opportunity to address staffing shortages and improve responsiveness. While the technology landscape is rapidly evolving, the strides made in AI and automation are set to bring about significant efficiencies in network management by 2025.
