In today’s rapidly evolving digital landscape, the adoption of artificial intelligence (AI) applications has become essential for businesses to stay competitive. However, to unlock the full potential of AI, organizations must ensure that their networks are ready to handle the increased demands of these innovative technologies. This article explores the key challenges faced by networking professionals, the importance of setting up an AI task force, the pressure on traditional network infrastructures, the role of hybrid cloud and multi-cloud, the significance of performance testing for SaaS-based applications, the need for end-to-end visibility into network performance and security, the potential of Secure Access Service Edge (SASE), the importance of SD-WAN connectivity, and the steps to implement a successful AI strategy.
The Challenges for Networking Professionals
Cisco’s 2023 Networking Report highlights a prevalent challenge faced by networking professionals: providing secure access to applications distributed across multiple cloud platforms. In a survey of 2,500 global companies, 41% of respondents identified this as their key challenge. To overcome this hurdle, a comprehensive strategy is required.
Setting up an AI Taskforce
To effectively address all aspects of AI strategy, organizations should establish an AI task force. This task force should comprise experts from different departments who can collaborate to ensure a cohesive approach to AI implementation. By dedicating resources and expertise to AI initiatives, businesses can streamline processes and maximize the potential benefits of these technologies.
Pressure on Traditional Network Infrastructures
Modern advancements, such as the rise of cloud services, the Internet of Things (IoT), and data-intensive applications, have already placed immense pressure on traditional network infrastructures. With the integration of AI applications, this pressure is expected to further increase. Networking professionals must anticipate and prepare for this growing demand by upgrading their networks to handle the substantial computing needs of AI applications.
Leveraging Hybrid Cloud and Multi-Cloud
To effectively desilo operations and strengthen network and security controls, IT teams should embrace a hybrid cloud and multi-cloud approach. This strategy allows for seamless integration of various cloud platforms, optimizing data accessibility and enhancing network performance. By adopting a cloud-centric model, organizations can leverage the benefits of different cloud providers while maintaining agility and flexibility.
Performance Testing for SaaS-Based Applications
To ensure successful AI solutions, businesses must prioritize the performance testing of Software-as-a-Service (SaaS)-based applications. This testing evaluates the efficiency and reliability of applications, identifying any potential bottlenecks. By addressing performance issues proactively, organizations can optimize their AI solutions and enhance overall productivity.
End-to-End Visibility for Network Performance and Security
Businesses need complete visibility into network performance and security to provide secure access to applications across multiple cloud platforms. Effective monitoring tools that offer comprehensive insights into network performance, identify potential vulnerabilities, and enable a rapid response to threats are critical for maintaining a secure and reliable network infrastructure.
The Role of Secure Access Service Edge (SASE)
Simplifying network security tools and achieving consistency across the network is vital. Secure Access Service Edge (SASE) provides a unified framework that combines network security and connectivity functions into a single cloud-native service. By adopting SASE, organizations can streamline operations, enhance security, and ensure a consistent approach to network protection across all cloud platforms.
SD-WAN Connectivity for Cloud-Agnostic Connectivity
For organizations utilizing multiple cloud platforms, consistent Software-Defined Wide Area Network (SD-WAN) connectivity is crucial. SD-WAN automates and optimizes cloud-agnostic connectivity, ensuring seamless communication between different cloud environments. By leveraging SD-WAN, organizations can enhance application performance, simplify network management, and improve the overall user experience.
Implementing a Successful AI Strategy
To successfully implement an AI strategy, IT teams must focus on three key steps. First, ensure network readiness by upgrading network infrastructure to handle the increased computing demands of AI applications. Second, adopt a cloud-centric operating model to maximize the benefits of hybrid cloud and multi-cloud approaches. Third, monitor global internet health and the performance of top SaaS applications to proactively identify potential issues and optimize network performance.
As AI applications become increasingly prevalent, organizations must ensure their network infrastructure is prepared to support these technologies effectively. By addressing the challenges faced by networking professionals through the establishment of an AI taskforce, upgrading traditional network infrastructures, leveraging hybrid cloud and multi-cloud, prioritizing performance testing, enhancing visibility into network performance and security, adopting SASE, and implementing SD-WAN connectivity, businesses can successfully implement their AI strategies. By taking these necessary steps, organizations will be able to harness the true potential of AI and stay ahead in today’s rapidly changing digital landscape.