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At IFA Berlin 2026, AI remained the dominant theme, as it becomes increasingly embedded across consumer electronics experiences. Beyond AI, robotics stood out, with the show hosting a ‘Robots on the Runway’ spectacle. For players across the consumer tech ecosystem, the themes highlighted at IFA continue to spur opportunities such as monetisation but also challenges, including costs and privacy issues.

Growth in AI consumption is creating commercial opportunities across the AI value chain. Over the past year, investment in AI has increasingly extended towards revenue-generating services and enterprise propositions, with operators assuming a broader range of roles across the AI value chain. Telcos in Asia Pacific are particularly active across multiple layers of the AI value chain. They account for 43% of those participating in the infrastructure layer and 38% in the model layer. This position reflects the combination of large and linguistically diverse markets, government-backed national and sovereign AI agendas, expanding AI infrastructure investment, and the scale of leading regional operators and technology ecosystems.

B2B has emerged as a strategic growth area for operators and the wider tech/digital ecosystem. As the digital transformation of vertical sectors accelerates, gaining insights directly from enterprises is key. GSMA Intelligence surveyed enterprises from six countries and 10 vertical sectors across the ASEAN region to gain insight into their digital transformation. The research focused on strategic objectives, investment plans, use of technology, deployment challenges, supplier decisions, technology sovereignty, and policy and regulation.

Enterprises will spend 10% of their revenues on digital transformation through to 2032, which brings new B2B opportunities for technology suppliers, including operators. This report analyses the key findings and implications from a GSMA Intelligence survey, which surveyed 6,342 enterprises across 50 countries and 10 vertical sectors worldwide to gain insight into their digital transformation.

GSMA Intelligence surveyed 6,342 enterprises across 50 countries and 10 vertical sectors worldwide to gain insight into their digital transformation. This dashboard provides full survey data in a consistent and structured way – a valuable asset for technology suppliers looking to focus on specific vertical sectors, countries or customer size and for end users of digital transformation technologies, who can assess how they compare with their peers across multiple areas.

As operators pursue new growth opportunities in the digital era in both the consumer and enterprise markets, assessing innovation and achievement is more important than ever. This case study highlights how LG Uplus is positioning its ixi-O genAI offering as the consumer aspect of a broader push to build AI around people rather than technology.

As operators pursue new growth opportunities in the digital era in both the consumer and enterprise markets, assessing innovation and achievement is more important than ever. This case study highlights China Mobile's consumer genAI offering, part of the operator’s wider aim to use AI to support revenue growth in the consumer market.

As operators pursue new growth opportunities in the digital era in both the consumer and enterprise markets, assessing innovation and achievement is more important than ever. This case study looks at how Verizon is using generative AI to support its strategy to become an AI-first company, deploying AI at scale to reshape customer experience.

Developments in AI this quarter highlight telecoms operators moving beyond connectivity to offer bundled infrastructure for enterprises. Sovereign infrastructure is further strengthening their role in markets with local data requirements, making partnerships and focused industry solutions key to success.

As the market races to evaluate the opportunity of token-focused AI monetisation, perhaps the most important question is around the challenges and risks. Against the backdrop of an evolving and uncertain new market, this piece covers the potential pitfalls that operators need to be aware of.

With a 33% rise in international visitors this year, MWC Shanghai speaks to China’s influence and gravitational pull on the regional Asian tech economy and reciprocal demand from buyers to see and be seen on the MWC stage in an already busy event calendar. The analysis here highlights the key takeaways and implications from the meetings, summits and announcements at the event.

With network and service automation a hallmark of the TM Forum’s work, there was never any doubt as to the predominant theme at this year’s DTW Ignite event in Copenhagen. While AI is impacting nearly every aspect of telecoms networks and services, a key question was how this would be reflected in the event’s keynotes, launches and meetings. Agentic AI played a significant role in this year’s messaging – but, more surprisingly, core network automation garnered outsized attention.

Several dynamics have either emerged or intensified, materially altering the strategic role of the mobile core. These shifts demand a fresh review of how mobile core networks are evolving – and how they must continue to evolve. The mobile core remains an enabling layer. At the same time, it is becoming an intelligent, adaptive platform that will shape how operators compete, differentiate and grow in the AI era – as long as operators know how to put it to use and evolve its capabilities.

By investing in AI factories, telecoms operators can leverage their infrastructure, traffic, customer base and regulatory positioning to capture a meaningful share of the expanding AI and cloud revenue pool. Scenario analysis suggests AI factories could deliver an incremental uplift of 1.5–6.0% to total operator revenues, depending on execution and market share capture. This represents a meaningful growth lever in an otherwise mature industry.

Last month, China’s three major telecoms operators became the first to launch token-based AI plans, packaging AI usage in a way that resembles traditional mobile data bundles, signalling a broader push by operators to commercialise AI, cloud and compute capabilities. This reflects growing interest among operators in monetising AI by moving beyond internal AI efficiencies and towards commercial AI opportunities. The logic is simple – tap the surging interest in AI and put a meter on it – but the concept goes beyond just offering tokens for cash.

Many AI announcements in Q1 2026 focused on telecoms operators and partners building out sovereign capabilities to satisfy national requirements around data residency, compute and LLMs. Meanwhile, investment in agentic AI build-outs has extended beyond networks and software to machines, drones, cars and other industrial assets – so-called ‘physical AI’. As well as recent developments from the telco AI space and the Telco AI tracker, this edition provides a deep dive on the implications of the growth of on-device AI.

Digital transformation of enterprises is accelerating across all vertical sectors, with AI being an important driver and enabler and a top area of investment. GSMA Intelligence surveyed 5,320 enterprises across 32 countries and 10 vertical sectors to gain relevant insights into their digital transformation across a range of technologies. This report analyses the key findings and implications for AI.

For much of 2025 and early 2026, the development of sovereign AI and sovereign digital service strategies – including the role telecoms could play in supporting them – was regularly in the news. For operators, the strategies represent an opportunity to support national agendas, reassert their relevance in the digital economy and drive new revenues based on their position as highly regulated and trusted service providers. This analysis looks at the sovereign messaging conveyed in sessions at MWC from operators, vendors, regulators and cloud providers.

On-device AI is the next frontier for AI deployments in consumer and enterprise segments. Use cases include AI-based search and personal assistants, image analytics on a smartphone, AI-assisted driving and navigation in cars, industrial applications such as automated guided vehicles, and improved IoT analytics. This has implications for the device world and major tech companies whose business models depend on consumer time on the internet and digital platforms. It also matters for operators, given the ripple effect of AI-driven data traffic on mobile and fibre networks, and the direct revenue opportunity.