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Ciena, an optical networking products supplier, will report its third-quarter fiscal 2026 results on 3 September. The company's stock has already risen 62% this year and may climb further following the earnings release. Ciena has exceeded Wall Street's earnings expectations in each of the past four quarters. For the third quarter, the company has guided for revenue of $1.62 billion, a 33% increase year over year, and a non-GAAP adjusted operating margin of 19%–20%, nearly double last year's 10.7%. Analysts expect earnings of $1.72 per share, representing a 157% year-over-year increase. Goldman Sachs predicts the total addressable market for optical components could grow from $15 billion this year to $154 billion in 2028. Strong demand for optical networking components is driving this growth, as hyperscalers and AI companies invest heavily in data centre infrastructure.

Ciena survey highlights AI network services and network upgrades. A recent Ciena survey of service providers underscores the revenue potential of AI-driven networking. Ninety percent[1] of respondents expect high-capacity AI network services - connectivity to AI infrastructure required by enterprises, hyperscalers, and neoscalers - to drive revenue growth over the next three to five years, with 56% citing them as their primary source of net-new revenue. Confidence is equally strong in managed optical fiber network (MOFN) services, with 96%[3] expecting them to generate revenue from connecting distributed AI compute clusters over the next three years, and 51% identifying MOFN as their primary vehicle for delivering data center interconnect (DCI) services. However, as service providers pursue new AI-driven revenue opportunities, the majority (88%[2]) of survey respondents had a strong sense of urgency on the need for optical network upgrades to support the demands of premium enterprise AI service level agreements (SLAs). Additionally: * Nearly half (48%) believe those upgrades are critical, and 39% said they are needed within the next 12-18 months. * Only 11% believe routine upgrades will be sufficient to meet the demand. * Advanced network automation, including agentic AI, is seen as essential (96%[4] surveyed agree) to capitalize on AI-driven opportunities. The Ciena survey, conducted in collaboration with Censuswide questioned more than 1,200 telecom, wholesale, and regional service provider experts across 12 countries and found that service providers see multiple emerging opportunities to expand AI-related revenue streams: * AI Inference: Nearly half (49%) of those surveyed believe growth in AI inference data centers will create new revenue opportunities by increasing demand for data center interconnect (DCI) services. * GPU-as-a-Service: Service providers see significant opportunities to capture GPU-as-a-service revenue, with 94%[5] viewing strategic partnerships with cloud and neocloud providers as essential to success. Among those surveyed, 44% plan to adopt revenue-sharing models as their primary go-to-market strategy. * Connecting AI in day-to-day life: The growing use of AI in everyday life is presenting additional revenue opportunities for service providers. Almost all respondents (95%[1]) believe immersive and AI-driven entertainment will contribute to new revenue streams in the next three years. Nearly one-third (29%) named AI wearables and personal devices, including smart glasses and health trackers, as the leading consumer hardware category expected to drive premium service revenue. * The network edge: 39% of service providers surveyed believe services hosted at the network edge, such as edge compute, GPUaaS and localized AI inference, will drive more than 20% of enterprise revenue over the next three years, while 88% expect it to drive at least 10%. * Physical AI: Nearly two-thirds (60%) of respondents expect physical AI ecosystems, including industrial robotics and remote-control systems, to account for more than 15% of their total enterprise AI revenue within five years. Beyond revenue opportunities, the survey highlights how AI is reshaping service provider priorities, from network performance and cloud connectivity to security and new service delivery models. Additional findings include: * The race for reliability, not just bandwidth: AI workloads are increasingly critical to business processes and the networks supporting them must be capable of delivering high-performance connectivity consistently to keep applications running satisfactorily. 35% of service providers identify network consistency - including guaranteed performance stability and low jitter - as the top opportunity for monetization through premium service offerings. * The rise of scale-across AI infrastructure: As power constraints limit data center expansion on a single campus, hyperscalers are scaling compute capacity across distributed locations. These facilities need to be tightly integrated requiring ultra-high-speed synchronous communications. In the case of distributed synchronous training of large frontier models, these connections can reach tens of petabits-per-second, requiring up to hundreds of fiber pairs lit in parallel at full capacity. 95%[6] of the respondents see hyperscaler scale-across demand as a substantial contributor for wholesale revenue growth. * Revenue drivers for multi-cloud enterprise environments: Service providers are shifting toward dynamic connectivity models as their main revenue drivers. Multi-cloud connectivity management (56%) and consumption-based bandwidth services (50%) rank highest, outpacing traditional fixed-capacity services (38%). Additionally, 47% expect enterprises moving large datasets between cloud environments for AI processing to drive demand for high-capacity, flexible cloud connectivity. * Quantum-safe encryption is critical: Secure networking remains top of mind with quantum-safe technology emerging as a key focus for service providers preparing their networks for AI-driven demand. More than half of respondents (51%) stated that they have already launched or expect to launch commercial quantum-safe encryption services, including QKD-protected links and/or PQC-ready managed security, within 12 months. Another 48%[7] are in the early stages of development or evaluation, underscoring the importance of preparing for quantum computer threats. Additionally, 'advanced physical and cyber security' capabilities were cited as the leading commercial driver of sovereign network infrastructure. Brodie Gage, Chief Product and Technology Officer, Ciena The survey findings show that service providers are approaching AI with both optimism and urgency. Service providers see significant opportunities around AI inference, GPU-as-a-Service, high-capacity network services, and quantum-safe encryption, while recognizing that many existing networks must evolve to meet new performance demands. The message is clear: AI is creating new sources of revenue, and success will depend on having the network foundation to support them. Ray Sharma is an Industry Analyst and Editor at The Fast Mode. He has over 15 years of experience in mobile broadband technologies and solutions, conducting research and analysis on various technology segments and producing articles and write-ups on the latest developments within the sector. He is also in charge of social media engagement and industry liaisons. The Fast Mode 9658 likes TWEETS 28.4K FOLLOWING 3479 FOLLOWERS 13.2K

Quintessent has raised $40 million in an oversubscribed Series A funding round led by Cycle Capital, with participation from Goldman Sachs XIG-Industry Ventures, Hina Liberty Capital, Susquehanna International Group, and others. The Santa Barbara-based company is developing optical interconnect products for AI datacentres. Quintessent has begun customer sampling of its single-chip quantum dot-based DWDM comb laser, which generates eight wavelengths from a single laser with one bias control. The technology aims to simplify optical connectivity for AI clusters whilst reducing power consumption and manufacturing complexity. The company's laser architecture uses Gallium Arsenide quantum dot gain material integrated on silicon photonics, avoiding capacity constraints in the Indium Phosphide supply chain. Quintessent claims the design can deliver up to 40% reduction in data movement power compared to alternative architectures. The funding will support product maturation, manufacturing scale-up, and development of additional optical components for AI infrastructure applications.