Pipe Dreams & AI Realities: Networking’s Midlife Crisis
Examining the Promise of AI in Networking in 2024 & Beyond
AI Has the Power to Transform Networking
What near-term value can companies capture using AI/ML and GenAI in networking?
Predictive AI including ML (machine learning) and DL (deep learning) techniques have a proven history in networks, while GenAI is still rapidly evolving. Leaders are faced with a challenge: maximize innovation and embrace the transformation AI can bring, while ensuring they stay clear of hype and minimize risk.
This new report from AvidThink explores the variety of roles AI can play in networking’s future, across multiple use cases at every point in the network lifecycle. According to the report, AI has the potential to “transform how networks are designed, deployed, managed, optimized, and secured.” However, to achieve success, there are important barriers to overcome.
By balancing innovation with caution, organizations will be able to use AI to transform their networks and continue working toward a goal that has long remained out of reach: fully autonomous networks.
Reshaping Network Infrastructure With AI Automation
with Itential CTO, Chris Wade
Challenges, Barriers, & Recommendations
AI — both the newer GenAI, and ML techniques that have an existing track record in networking — can enable a more scalable, adaptable network infrastructure that will drive efficiency and meet the demands of modern hybrid deployments. To achieve the potential that AI promises, organizations must address technical challenges, cultural challenges, and business challenges.
Top barriers to widespread AI adoption:
- Trust in AI-driven decisions and activities, including the ability for decisions to be interpreted and understood by humans.
- The scalability and reliability of RAG (retrieval augmented generation) architecture for augmenting LLMs with proprietary and context-specific data.
- Network fragmentation and the need for AI deployments to support multiple vendors and multiple infrastructure domains.
- Data privacy.
- Lack of clarity around which GenAI use cases will deliver highest ROI.
AvidThink recommends that organizations begin with proven solutions (predictive AI/ML), and adopt a phased approach to GenAI. Key priorities for enabling GenAI include investing in robust data infrastructure, greater focus on testing and digital twins, and enhanced security measures and privacy controls.
By addressing barriers to adoption and prioritizing infrastructure modernization, organizations will be able to successfully implement AI in the network to deliver transformative benefits.
The Journey Toward Autonomous Networks
AvidThink’s report primarily focuses on practical next steps and actionable, value-generating AI use cases. But, as the report states, advancements in AI have brought the industry closer than it has ever been to the long-held goal of fully autonomous networks.
The concept of a fully autonomous network isn’t new. But as GenAI continues to evolve and teams identify the most reliable and valuable ways to implement the technology, we will see renewed progress on this journey. Modern networks are larger and more complex than ever, and communications infrastructure is more critical to how business operate than ever. As a result, it is critical that organizations redouble their efforts to achieve higher levels of autonomy.
Technology leaders have the chance to transform how networks are designed, configured, managed, optimized, and secured. If implemented correctly, AI can finally bring the vision of autonomous networks to reality.
Read the AvidThink report to learn:
- How predictive AI/ML technologies have already impacted network design and management.
- Why GenAI brings transformative potential to networking for multiple use cases across the network lifecycle, including design generation, discovery, and orchestration.
- The barriers to AI adoption that must be addressed to embrace rapid innovation.
- What’s available on the market today, and what will be possible in the future — including the eventual goal of fully autonomous networks.
- AvidThink’s recommendations for leaders to adopt AI responsibly while maximizing innovation potential and return on investment.
DISCLAIMER: By downloading the report, you agree that you will respect the report publisher’s (AvidThink LLC) copyrights and not use the content for any training or fine-tuning of AI models, including private large language or foundation models.