The global networking landscape is rapidly evolving, driven by increasing demands for more robust, secure, and efficient communication networks.

This evolution is marked by the adoption of cloud technologies, the necessity for robust cybersecurity measures, and the integration of AI and machine learning into network operations, according to Juniper Networks vice president and general manager for Australia and New Zealand, Bruce Bennie.

“In Australia, with the rapid adoption of cloud services and the push for digital transformation, bolstered by initiatives like the Digital Economy Strategy, these changes present both opportunities and challenges,” he told Retailbiz in a recent interview.

“The country’s geographical position and economic landscape also mean a tailored approach is needed to ensure connectivity, security, and innovation in networking solutions that meet the specific needs of businesses and consumers in the country.”

Juniper Networks leverages AI-Native Networking to address these challenges with an approach that emphasises the integration of AI from the ground up, ensuring networks are more adaptable, resilient, and capable of anticipating and resolving issues proactively.

“For Australia, a country with vast distances and diverse infrastructures, Juniper’s innovations could significantly enhance connectivity, streamline operations, and support the growing needs of digital economies and smart cities,” Bennie said.

At Juniper Networks, being AI-native is about reimagining network operations while maintaining a human-centric approach. Designed with AI at its core but with emphasis on reliability, efficiency and user-centricity, it’s about looking beyond the nuts and bolts to prioritise uninterrupted experiences.

“Our AI-Native Networking Platform is the culmination of years of dedicated AI research. It harnesses the power of artificial intelligence, machine learning, and data science to revolutionise how networks operate. This platform is not merely an add-on to our existing technologies but is ingrained into the architecture of our products, ensuring that our networking solutions are built for AI from the outset,” he said.

Incorporating AI deeply and fundamentally into network operations and management ensures proactive problem-solving and experience-first networking.

“By being AI-Native, we have been able to proactively solve network issues before they even affect users, significantly reducing network trouble tickets and enhancing overall network performance,” Bennie explained.

“This is brought to life through our deep integration of AI into network operations, leveraging a cloud-hosted AI Operations (AIOps) system and a virtual Network Assistant (VNA) to collect and utilise the right data. This approach prioritises experience-first networking, focusing on delivering seamless experiences rather than merely on technical network metrics.”

How companies can best utilise their AI networking portfolio

AI plays an increasingly critical role in taming the complexity of growing IT networks. It enables the ability to discover and isolate problems quickly by correlating anomalies with historical and real-time data, according to Bennie.

“In doing so, IT teams can scale further and shift their focus toward more strategic and high-value tasks and away from the resource-intensive data mining required to identify and resolve needle-in-the-haystack problems that plague networks,” he said.

“Companies can best utilise their AI networking portfolio by leveraging automation and insights to optimise operations, enhance security, and ensure network reliability. By adopting a strategy focused on automation, firms can streamline network management tasks, reduce operational costs, and improve overall efficiency.”

Bennie suggests five things that are needed in an AI virtual Network Assistant (VNA) for a successful outcome:

  1. The right data – Bad data in, bad data out. The right data is required to build an AI model. Not just the quantity of data but the quality of data.
  2. Modern microservices cloud– To achieve agility and scale resiliency, a unified portfolio is critical.
  3. Rich data science – With AI, algorithms get better in time as there are fewer false positives.
  4. Continuous learning– Ensure that the vendor is using real AI, taking feedback from customers and putting it into the system to learn better.
  5. Full stack portfolio– Having the ability to correlate all relevant information ensures that the AI is not working in a silo.

Retail case studies

Juniper Networks helped Gap, Inc. transform its business with technology that transformed the way shoppers interact. With multichannel experience the new normal, and e-commerce sales continuing to grow rapidly, consumers don’t simply want to shop for products; they want to seek out a more engaging experience.

To give customers and retail associates the best experience with in-store Wi-Fi, Gap Inc. found AI-driven networking to be a perfect fit. The solution saw an 85% reduction in visits to stores by technical staff.

While in Australia, My Muscle Chef sought a new network solution with the most advanced, intelligent technology available. Employees worked too hard to deal with poor Wi-Fi performance and IT leadership wanted a network that supported automation and IoT, as well as security across the business.

As such, My Muscle Chef consolidated three sites into its new headquarters and rolled out the full stack of Juniper wireless, wired, and security. This includes Juniper’s AI networking solution, Mist AI, which delivers insight and automation, and the Marvis Virtual Network Assistant, which assists staff with troubleshooting and AI-driven actions to keep the network healthy.  

“Across APAC and in Australia, Juniper powers some of the largest service providers, enterprises, banks, and nationwide government-owned networks, and we continue to do so through our fully integrated AI-Native portfolio,” Bennie said.

“To us, the network is more than just about connecting people. It’s understanding how to utilise and convert network performance data into valuable insights. With the launch of Juniper’s AI-Native Networking platform, we are further primed to compete and lead in the next era of AI and IT, enabling businesses to have an optimised, reliable and efficient IT infrastructure.

“With that in place, our goal – now and in the future – is to bring exceptional experiences to end users and IT operators by making it easier and more cost-efficient for them while making network outages, trouble tickets, and application downtime things of the past.”