Today’s CEOs have three top priorities for their CIOs: improve the customer experience, strengthen IT and business collaboration, and improve the employee experience, according to the Foundry 2023 State of the CIO.
There’s certainly room for improvement: 80% of respondents to a Juniper Networks survey said poor network connectivity interrupts their work, on average, two to three times per day.
Your network is the heartbeat of the user experience. When it goes down, employees and customers get frustrated, which can lead to reduced productivity, abandoned sales, and other unwelcome business results. And there’s further frustration if users must call or submit a support ticket to IT. This extra step slows resolution. How can an organization avoid this scenario?
The answer is experience-first networking, which includes a strong network infrastructure with visibility into how it’s performing. This approach provides the best possible experience for network operators who must keep the network heartbeat thrumming, as well as end users who keep the business moving.
Trust is a critical factor in most aspects of life. But this is especially true with complex concepts like artificial intelligence (AI). In a word, it’s essential for day-to-day users to trust these technologies will work.
“AI is so complicated that it can be difficult for operators and users to have confidence that the system will do what it’s supposed to do,” said Andrew Burt, Managing Partner, BNH.AI.
Without trust, individuals will remain uncertain, doubtful, and possibly even fearful of AI solutions, and those concerns can seep into implementations.
Artificial intelligence (AI) solutions are grabbing headlines for good reasons. These technologies — which include intelligent automation, machine learning (ML), and natural language processing (NLP) — are delivering business value and easing the workloads of IT and network teams.
For example, an AI-driven network can reduce the need for IT staff to:
AI-enabled network solutions can also help IT teams rapidly deliver network enhancements and get ahead of issues before they become problems. The combination of AI, ML, and data science enables automated event correlation, root cause identification, anomaly detection, and more. Together, these technologies optimize operations across wireless, wired, and SD-WAN networks.
Network admins and engineers have enough work on their plates, especially considering increasing numbers of access points amid the hybrid workforce. They’re also grappling with ever-more sophisticated cybersecurity threats across a highly complex network that now includes data centers, clouds and edge computing.
Yet, there’s little forgiveness from end users when there is network disruption leading to down time. High availability and low latency are crucial.
Artificial intelligence (AI) technologies — such as machine learning (ML), natural language processing (NLP) and enhanced automation — can provide relief for overstretched IT teams, while ensuring highly performing networks.
Many organizations modernize or upgrade their network only when it’s time for a refresh. However, transformation doesn’t have to be a wholesale, do-it-all-at-once project to start improving customer and employee experiences today.
For example, a large food retailer was happy with its existing Wi-Fi network vendor. “It was a good product, it served us well for over a decade,” said the organization’s network architect.
Although the company typically has a five-year refresh cycle, its IT leaders became open to making a change after seeing a demo of Juniper Mist™ AI, a wired and wireless network platform. It uses artificial intelligence (AI) and machine learning to optimize user experiences and simplify network operations.
There are multiple benefits to gain from investing resources into sustainability and environmental, social, and governance (ESG) efforts — including operational efficiencies, swift compliance with regulations, employee and customer satisfaction, as well as the criticality of addressing climate change.
IT leaders have a significant role to play here. Estimates project that by 2040, IT operations will produce 14% of the world’s carbon-dioxide emissions — up from 4% today.
There is an opportunity to reduce these emissions, support sustainable business growth, and achieve other advantages by addressing IT systems and processes. And it should start with the network architecture.
The hybrid workforce will continue for the foreseeable future, according to the Foundry 2022 Future of Work study. And the trend is affecting hiring and retention, with 62% of IT leaders saying their organizations are guaranteeing flexible work options to stay competitive in the marketplace.
Just as important: The technology and systems these employees use must be reliable and secure. Poor connectivity or network downtime not only frustrates users but also eats into productivity.
And yet both hybrid and on-site workers are experiencing a high volume of network interruptions, according to a Juniper Networks survey. For example:
The cyberthreat landscape weighs heavily on the minds of business and IT leaders — and for good reason. Statista reports that in this year’s third quarter alone, nearly 15 million data records were exposed worldwide.
The risk of data breaches places intense pressure on IT and security teams to ensure corporate networks are not only protected, but also kept up to date. That’s a tall order given the increasingly complex network architectures that mix on-premises and cloud infrastructure. In addition, hybrid workforces have created multiple paths for data and apps traffic that must be secured.
Sixty-two percent of organizations are planning to guarantee flexible work options to remain competitive in the marketplace, according to Foundry’s 2022 Future of Work Study. That’s causing some concerns around effective collaboration, IT staff and employee burnout, and the ability to maintain secure systems and processes.
But a network driven by artificial intelligence (AI) can help address these issues. Technologies including automation, machine learning, and natural language processing are used to gather data, analyze it, and then deliver insights or proactive recommendations for a more efficient, robust, and secure network.
Automation represents perhaps the clearest embodiment of Benjamin Franklin’s legendary “time is money” aphorism -- and artificial intelligence (AI)-driven networks are one area where it’s relatively easy to see the near-term benefits that give new meaning to Franklin’s simple phrase.
Network automation simplifies operations for network teams and reduces configuration errors. So, it stands to reason that greater automation through AI will deliver a more predictable and reliable network that seemingly can speed up time while saving lots of money. We turned to the CIO Experts Network of IT professionals and industry analysts to collect their views on AI-driven networks and how the technology is likely to change the lives of network teams.
Business spending on artificial intelligence (AI) technologies is growing by leaps and bounds as organizations strive to improve efficiency, simplify, and automate processes, and build more proactive capabilities. Global spending on AI-centric systems is on track to surpass $300 billion in 2026, with the U.S. accounting for more than 50% of the total, according to IDC forecasts. But the success of these investments may ultimately hinge on trust.
A National Institute of Standards and Technology (NIST) study points out that “determining that the AI system is trustworthy because it meets its system requirements won’t ensure widespread adoption of AI. It is the user, the human affected by the AI, who ultimately places their trust in the system.”
Over the past two years, institutions of higher education (IHEs) have undergone a tremendous amount of change. The future is more uncertain than ever. To prepare for the future, today’s institutional leaders must navigate the complexities of hybrid-first learning and operations to create flexible, high-quality digital experiences.
Artificial intelligence (AI) has emerged as a leading focus of IT investment for higher education leaders with the aim of enhancing the student experience, improving the financial health of their organization, and driving institutional excellence. But without a network capable of meeting these expectations and IT staff equipped to manage this complex IT landscape, institutions risk delivering a poor end-user experience.
By: Arun Gandhi, Senior Manager of Product Marketing at Juniper Networks
When you’re trying to convince companies to modernize, it can seem like you’re shouting into the void. Sure, they understand that what you’re advocating is important, but knowing you should do something and actually doing it are two different things.
This has been the story around data center network automation for the last several years.
We all know that data centers have become more complex and critical to most businesses. So, finding a way to enable more agile and efficient operations should be on every company’s to-do list. Yet, even with organizations that could benefit most from automation — communication service providers (CSPs) and enterprises managing large, distributed data centers — actual implementation has been slow. Fortunately, we seem to be turning a corner.
By: Todd Johnson, Director of Vertical Marketing at Juniper Networks.
Delivering an exceptional customer experience has never been more challenging. Retailers need to leverage technology to embrace new consumer habits and shopping styles while also meeting their in-store expectations with enhanced and personalized experiences and an interactive physical shopping journey.
To understand the emerging demands for retail customer experience, Juniper conducted two surveys: the Juniper Workplaces and Public Spaces Enterprise IT Survey and the Juniper Remote Workplaces and Public Spaces Consumer Survey.
You know it better than anyone: the network has become essential infrastructure for any successful enterprise. COVID-19, migration to multicloud, and new application requirements have only amplified pressure on enterprise IT to deliver high-availability, secure network services anywhere, anytime, and on any device.
This isn’t a passing fad. Several key trends will drive network growth and complexity for years to come, including:
To address these challenges and best position themselves for the future, enterprises must implement more intelligence in the network. Modern AIOps uses artificial intelligence and machine learning to assist IT in managing, troubleshooting, and fixing network problems. As a result, AIOps is becoming a key success factor in managing modern enterprise networks.
The rate of SD-WAN adoption is quickly rising to the point of ubiquity. In an era of distributed environments — including applications, employees, cloud, Edge, and data centers — navigating network complexity has become an increasing common challenge.
Recent ESG research found that 54% of survey respondents felt restrained by network complexity in terms of both operational efficiency and user experience. Impacted companies have two solutions for deploying SD-WAN: Do It Yourself (DIY) and or via Managed Service Providers (MSP). It’s up to IT leaders to choose the approach that will most effectively manage their deployments.
By Michael Bushong, VP of Data Center Product Management at Juniper Networks.
At Juniper Networks, we know that Juniper Apstra provides superior benefits to customers over the entire data center lifecycle, from Day 0 design and planning, to Day 1 deployment, through Day 2+ and ongoing operations. The problem? An assertion coming from a vendor sounds too salesy, even if our suspicions are right. So, we ran a detailed analysis through a third party, and it turns out, if anything, the results suggest we’ve been underselling the value Apstra can deliver. This blog is designed to walk through the findings. The conclusion? Those that aren’t shortlisting Juniper in the data center are likely leaving money – and capability – on the table.