The latest GSA tracking shows 89 commercial 5G Standalone launches across 73 nations. Meanwhile, 2,518 compatible devices now sit on shelves, easing migration fears. Carriers aim to exploit the platform’s low Latency promise and differentiated service tiers. Therefore, early adopters expect meaningzful new revenue streams rather than another price war. This article unpacks the momentum, technology, business cases, and obstacles surrounding the Standalone transition, with Connectivity AI threaded through every theme.

Global Standalone Rollout Momentum

Analyst reports show a clear acceleration during 2024 and 2025. Moreover, GSA counts 181 operators currently investing in public Standalone deployments. Ericsson places the launched or soft-launched figure slightly higher, at more than 90 communications providers. Consequently, boardrooms now view Standalone as inevitable rather than optional.

T-Mobile and AT&T highlight measurable gains after switching 5G traffic to the new core. In contrast, European groups like Orange prioritise orchestration consistency across affiliates before scaling. Connectivity AI surfaces in these plans through automated slice design and predictive capacity steering. Additionally, Vodafone aligns with Ericsson on programmable radio upgrades that feed AI optimisation engines. These collaborations illustrate how Connectivity AI converts raw telemetry into actionable rollout intelligence.

Market momentum is unmistakable and AI-driven. Nevertheless, understanding the foundational mechanics remains critical. The next section dissects core technology basics.

Standalone Core Technology Basics

Standalone architecture pairs a new 5G service-based core with radios free from LTE anchors. Therefore, the system unlocks native slice management, RedCap IoT onboarding, and tight edge integration. These capabilities drive end-to-end quality guarantees impossible on earlier hybrids.

Latency falls because control signalling no longer detours through a legacy EPC. Meanwhile, Connectivity AI monitors packet flows, predicts congestion, and reallocates microservices before delays appear. Cisco and Nokia position such AI modules as the next differentiator inside the core. Furthermore, open APIs expose network data to application developers seeking deterministic performance.

Core innovation sets the performance bar higher. In contrast, monetisation potential determines whether these gains translate into shareholder value.

Monetization And Network Slicing

Service providers hope slices will finally decouple revenue from simple gigabyte bundles. Ericsson counts 65 commercial slicing offers across 33 operators and notes 21 launched during 2025. Consequently, early enterprise trials are maturing into paid contracts for manufacturing, XR, and public safety. Connectivity AI orchestrates slice templates, aligns QoS policies, and adjusts charging based on intent.

• 118 documented slicing use cases across 56 providers (Ericsson)
• Up to 2,518 Standalone-ready devices available (GSA)
• 6% CAGR forecast for mobile core revenue 2024-2029 (Dell’Oro)

Moreover, some carriers already quote premium margins for guaranteed throughput or ultra-low Latency lanes. Connectivity AI supports real-time SLA enforcement, which reduces rebate costs when conditions drift. Nevertheless, mainstream consumer willingness to pay remains uncertain despite expanding 5G footprints. AT&T pilots consumer hotspot slices, yet executives stress that enterprise wholesale APIs look richer.

Slicing shows credible revenue potential today. However, significant operational hurdles could still derail mass adoption. The following section details those obstacles in practical terms.

Operational Hurdles Still Persist

Capital intensity tops executive concern lists. Regulated spectrum auctions and site acquisitions stretch balance sheets before returns materialise. Consequently, some operators restrict Standalone rollout to targeted enterprise zones instead of nationwide coverage. Device readiness also lags, requiring firmware updates or refresh cycles for many handsets.

Latency targets suffer when older radios coexist with new cores, producing unpredictable handovers. Meanwhile, Networks still rely on parallel LTE infrastructure, which keeps certain threat surfaces alive. Connectivity AI can detect anomalous signalling patterns faster, yet no tool erases fundamental architectural complexity. Nevertheless, skills gaps in cloud, automation, and security widen as software dominates telecom stacks.

Cost, skills, and device timing slow progress. Therefore, understanding the changing supplier landscape becomes vital. The next section reviews vendor dynamics and partnership models.

Vendor And Ecosystem Dynamics

Ericsson, Nokia, and Huawei field end-to-end portfolios that promise rapid Standalone activation. In contrast, open RAN advocates push disaggregated builds to avoid vendor lock-in. Cloud hyperscalers lease edge capacity and managed core functions on consumption terms. Additionally, Qualcomm and MediaTek accelerate device availability, supporting more than 2,700 Standalone models.

Connectivity AI often enters through these cloud alliances, using Kubernetes hooks and telemetry APIs. Moreover, some Carriers co-create AI modules with academic labs to maintain sovereignty over data. Dell’Oro expects the 5G mobile core market to expand at six percent annually through 2029. Meanwhile, consolidation risk persists as Networks move from hardware to software revenue streams.

Supplier choices shape long-term agility. Consequently, strategic planning must integrate both technology and commercial considerations. The final section outlines actionable steps for decision makers.

Strategic Roadmap For Carriers

Executives should prioritise cloud-native core deployment and phased radio upgrades. Furthermore, they must embed Connectivity AI governance early to avoid data silos. Structured pilots, such as public-safety slices, validate SLAs before broader consumer release. Operators should also benchmark Latency across mixed access layers to guide investment sequencing.

Certification programs help teams acquire trusted skills quickly. Experts can upskill with the AI+ Network Security™ certification. Moreover, Connectivity AI skill sets will underpin future job descriptions across operations and product teams. Finally, an explicit Standalone business case must accompany every new capital request.

A disciplined, AI-augmented roadmap minimises risk. Nevertheless, timing decisions require continuous market intelligence. Readers can stay competitive by following industry trackers, engaging with vendor labs, and pursuing professional certifications.

Conclusion And Call-To-Action

Today’s telecom race has clearly shifted from hype to execution. Early launches prove that Standalone cores deliver service agility and measurable performance benefits. Slicing pilots now generate income, yet monetisation models will evolve as enterprise requirements mature. Cost, skills, and regulatory issues remain sizeable but manageable with disciplined planning. Executives who combine cloud infrastructure with advanced automation stand to lead the next connectivity wave. Readers can stay competitive by following trusted trackers and strengthening staff capabilities. Act now to position your organisation at the forefront of the Standalone revolution.