Digital Lifescapes

Employee sentiment toward workplace AI is shifting fast.Gartner's HR survey makes one thing clear: enthusiasm is no longer the constraint. The real bottleneck is leadership’s ability to translate that energy into disciplined governance, thoughtful deployment, and measurable business outcome value.Executives have blamed employee resistance for underwhelming AI outcomes in HR and broader business workflows. The latest market research tells a different story.Sixty‑five percent of employees now say they are excited to use AI at work. That is not a grudging tolerance of automation; it is a clear signal that the workforce is ready to experiment, learn, adapt, and integrate AI into daily work.Enterprise Applied-AI Market DevelopmentYet, according to the research, 37 percent of employees do not use Generative AI tools even when they have access, simply because their coworkers are not using them.This 'peer inertia' effect highlights a social adoption challenge rather than a purely technical one: people look sideways before they look up. When colleagues are not leaning in, AI tools remain an optional add‑on instead of becoming a core part of the routine operating model.The survey results undercut the persistent myth that employees are the primary barrier to AI value creation in the enterprise. Gartner’s analysis points instead to executive urgency and rushed implementations that gloss over workforce readiness.Gartner found that many AI deployment decisions are made without HR at the table, leading to misaligned expectations between leadership and employees and, ultimately, to underuse or misuse of the tools.This misalignment typically plays out in three common failures:AI point solutions rolled out as 'shiny objects' with minimal change management, leaving managers unclear on when and how to use them.Employee training is offered as one‑off events, rather than continuous learning journeys that build confidence and capability over time.Governance frameworks that focus on compliance and information security, with little attention to employee experience or role redesign.The result is a paradoxical situation: high excitement, low realized value. HR leaders surveyed in related Gartner research overwhelmingly report that their organizations have yet to see significant business impact from AI, despite growing investments.The Key Workforce Behavior IndicatorsBeneath the latent employee excitement, several key behavioral signals should inform a more strategic HR and IT deployment roadmap. Employees are not just curious; they are willing to invest in their own personal and professional development.In one Gartner data set, 77 percent of employees who are offered AI training actually take it, underscoring latent demand for skill building when organizations provide structured support.Among those who already use AI tools at work, 62 percent report time savings, with employees in AI‑relevant roles saving an average of 1.5 hours per day.That is the kind of enterprise workflow productivity uplift executives expect from AI, but it is still unevenly distributed and often not intentionally reinvested. Yet another disconnent.Only a small share of organizations provide guidance on how employees should utilize the time freed up by AI, which means that potential gains in innovation, customer engagement, or strategic work often dissipate into ad-hoc tasks.Gartner’s marketplace segmentation work goes further by identifying four employee archetypes that stand to benefit most from AI augmentation: Consumers, Communicators, Coordinators, and Creators.Each group interacts with information differently — whether synthesizing insights, crafting messages, orchestrating workflows, or generating content — and therefore requires tailored tools, training, ongoing coaching, and insightful success metrics.Strategic Implications for Business LeadersFor C-suite leaders, this research reframes AI as a workforce design issue, not just a technology procurement decision. Gartner recommends three critical shifts:Reframing AI governance to incorporate employee experience alongside compliance and security.Involving HR directly in AI deployment decisions, from use‑case selection to communication and training.Identifying curious, collaborative employees as adoption champions, then segmenting the broader workforce by attitudes and behaviors toward AI.These actions move organizations from mere 'AI tool rollouts' to systemic change.For example, aligning AI co-pilots with high‑curiosity employees in a sales operations team, coupled with targeted learning paths and clear performance metrics, can generate internal case studies that address both the peer‑inertia problem and executive skepticism.Similarly, HR can partner with digital workplace and security teams on an integrated governance council to ensure that policies address trust, transparency, and job redesign — not just access control and risk reduction.Where Strategic Value and Growth EmergeThe most compelling opportunities are less about buying new AI platforms and more about orchestrating employee behavior change at scale. The data suggests three growth vectors for enterprise organizations and solution providers:  Workflow‑embedded AI: Tools that integrate seamlessly into existing HR and line‑of‑business systems, with clear prompts, guardrails, and feedback loops aligned to specific roles and archetypes.Governance and enablement services: Advisory offerings that help enterprises design policies, segmentation models, learning journeys, and performance frameworks that translate AI excitement into measurable productivity and engagement gains.Manager‑centric capability building: Programs that equip managers (often the weakest link in AI maturity) with practical playbooks for using AI to redesign team processes, not just individual tasks.Outlook for Applied-AI Business Value CreationOrganizations that treat AI as a workforce transformation initiative, grounded in HR‑led governance and a nuanced understanding of employee behavior, will unlock disproportionate value.Those that continue to pursue AI as a series of disconnected tools, launched in a hurry and managed on the sidelines of HR, will continue to see enthusiasm without business outcomes."To achieve high employee adoption and effective use of AI solutions, CHROs and their teams should segment employees by adoption attitudes and behaviors using surveys and usage data," said Eser Rizagolu, senior director analyst at Gartner.That being said, I believe single-event employee training is inadequate to achieve the desired level of adoption and progressive usage of AI tools that business leaders crave. Employee 1:1 coaching with a skilled practitioner is the best way to ensure that lessons learned during training are applied in practice.More...

Embodied AI is shifting industrial robotics from precise to perceptive — from rigid automation to adaptive execution in messy, variable production environments.For manufacturers and logistics providers, this isn't just a technology upgrade; it's a structural change in how work gets organized and business value gets created.Industrial robots have long excelled in static workflows: automotive assembly, fixed production lines, repetitive tasks. Where variability or human interaction arose, they stalled or required prohibitive engineering.Embodied AI Market DevelopmentEmbodied AI changes this by closing the "sim-to-real" gap.According to the latest worldwide market study by ABI Research, AI-augmented robots have reached genuine adaptive automation with tangible ROI for early adopters.The shift rests on robust algorithms — particularly Dynamic Policy Adjustment and robotics foundation models — that learn and adapt in real time rather than following hard-coded rules. These systems handle unpredictability on factory floors and in warehouses.Where Robot Value ConcentratesLegacy manufacturing flows will continue using conventional automation. Real growth lies in "under-automated" markets where variability dominates and manual labor persists despite clear automation pain points:Life sciences and lab automation: Complex sample handling, flexible assays, and high-mix environments under strict regulatory requirements.Niche high-value manufacturing: Semiconductor production requiring precise yet adaptable manipulation in clean rooms.Logistics and warehousing: Endless SKU heterogeneity, packaging variations, volatile demand, and labor constraints. Adaptive robots handling changing inventory and shared workspaces create operational leverage.ABI Research sees a multi-billion-dollar retrofit market plus larger greenfield opportunities. Retrofits layer AI onto existing assets, extending utility without replacing hardware. Greenfield deployments build AI-native systems optimized for flexibility from the ground up.Technology Stack and Market LeadersThe ABI Research "physical AI" taxonomy spans: reinforcement learning for continuous improvement; robotics foundation models as generalized priors for perception and control; LLM interfaces for natural language guidance; and advanced SLAM, world models, and machine vision for situational awareness.The ecosystem includes adaptive automation leaders (InBolt, Apera, Cambrian AI, NVIDIA), machine vision specialists (SICK, Cognex, Mech-Mind, Universal Robots), and foundation model developers (Google DeepMind, Covariant, Intrinsic, Physical Intelligence) building infrastructure that could cut integration timelines and make robots more plug-and-operate.Tech Vendor Commercial RequirementsThe barrier is now commercial, not algorithmic. Vendors must deliver:Usability: Operable by engineers, not just roboticists — requiring low-code tools and pre-packaged workflows.Transparency: Explainable AI with robust monitoring for safety-critical and regulated environments.ROI clarity: Quantified benefits tied to specific use cases — cycle-time reductions, throughput gains, error-rate improvements.Vendors coupling strong technology with clear business value will define the emerging marketplace in conservative industrial segments.Embodied AI Strategic TrendsEmbodied AI expands what counts as "automatable," moving robotics from structured cells to complex operational edges. Dominant trends:Retrofit platforms: AI upgrade kits transforming legacy systems without wholesale replacement.Verticalized solutions: Bundled hardware, AI, and services around specific problems — bin picking in e-commerce, kitting in electronics, sample handling in genomics.Human-robot collaboration: Cobots as co-workers, not caged machines — safety and intuitive interaction shaping purchases.Data network effects: Large fleets and shared platforms compounding performance advantages.Outlook for Embodied AI Apps GrowthFor savvy business technology leaders, embodied AI is now a strategic automation layer intersecting OT, IT, and AI governance."The critical challenge now is translating this technical readiness into widespread commercial adoption," said George Chowdhury, senior analyst at ABI Research.That being said, I believe early movers aligning deployment pilots with high-value, variable workflows will capture efficiency gains and competitive differentiation as this era unfolds.More...

The global smartphone market closed 2025 with a story less about recovery and more about transformation. Premium product, ecosystem lock-in, and manufacturing scale are now the forces shaping competition.For business and technology leaders, the latest IDC market study data confirms that smartphones remain a critical indicator of consumer demand, supply chain health, and AI commercialization at the edge.Smartphone Market DevelopmentGlobal smartphone shipments grew 2.3 percent year-over-year in Q4 2025, reaching 336.3 million units and bringing full-year volumes to 1.26 billion units — a modest 1.9 percent annual increase, according to IDC.This smartphone growth emerged despite a memory shortage crisis, tariff volatility, supply chain disruption, and macroeconomic headwinds.What stabilized demand? Two factors: sustained growth in premium devices and strong foldable momentum, combined with accelerated purchases as consumers bought ahead of anticipated price increases.Buyers weren't just returning — they were trading up, and doing so earlier than planned.The strategic insight: pricing power and differentiation have migrated decisively to the premium tier. Volume recovery is no longer the headline; mix and margin are.Apple and Samsung Command the Premium TierThe headline from IDC's data is unmistakable — Apple and Samsung now function as dual anchors of the premium segment, and their dominance is intensifying.For full-year 2025, Apple shipped 247.8 million units (19.7 percent share), up 6.3 percent, while Samsung shipped 241.2 million units (19.1 percent share), up 7.9 percent. Their combined 39 percent share represents a two-percentage-point gain from 2024, signaling clear consolidation at the market's summit.Q4 2025 performance was particularly striking. Apple shipped 81.3 million smartphones (24.2 percent share), posting 4.9 percent growth and maintaining leadership for both quarter and year.Samsung delivered its strongest Q4 since 2013, with 61.2 million units (18.2 percent share) and 18.3 percent year-over-year growth.Two product narratives define their success. Apple's iPhone 17 series fueled record shipments and a strong China rebound, delivering the company's best Q4 since 2021 and highest-ever quarterly revenue.This demonstrates the enduring power of Apple's ecosystem strategy, where hardware refreshes, services, and chipset innovation reinforce one another.Samsung's performance was driven by the Galaxy Z Fold 7 and AI-enabled Galaxy A-series devices, showing the company successfully operates on two fronts: aspirational foldables at the high end and accessible AI-powered devices at mid-tier prices.The pattern is clear: both vendors use premium devices not merely to sell hardware, but to deepen ecosystem engagement through AI features, services, and accessories — creating demand stability even during macroeconomic volatility.The Pressure on Positions Three Through FiveOutside Apple and Samsung, the three remaining Top 5 vendors — Xiaomi, vivo, and OPPO — are holding ground but facing structural pressure as the market shifts toward higher price bands.Full-year 2025 results show diverging fortunes. Xiaomi shipped 165.3 million units (13.1 percent share), down 1.9 percenet. Vivo shipped 103.9 million units (8.2 percent share), up 2.7 percent. OPPO shipped 102.0 million units (8.1 percent share), down 2.7 percent.Q4 brought sharper contrasts. Xiaomi maintained third place with 37.8 million units (11.2 percent share) but posted an 11.4 percent decline, reflecting challenges in repositioning toward premium and intensified China competition.Vivo delivered stability with 27.0 million units (8.0 percent share) and just 0.4 percent decline, powered by India growth. OPPO, statistically tied with vivo at 26.9 million units and 8.0 percent share, achieved 7.6 percent quarterly growth from new launches and stronger China performance, though full-year results suffered from weakness outside its home market.Meanwhile, "Others" accounted for 30.4 percent of Q4 shipments and 31.7 percent for the full year — both down slightly year over year. Smaller vendors are gradually ceding share to the scaled Top 5, raising the differentiation bar.Competing on price alone in a premiumizing market is becoming a shrinking opportunity.The Impact of Smartphone Supply ConstraintsThe most significant challenge facing 2026 is the memory shortage, which IDC describes as an unprecedented supply chain disruption likely to drive market decline this year.The shortage's duration and intensity will determine the contraction's depth, but one implication is already evident: vendor scale has become a defensive asset.Larger manufacturers can secure favorable supply and pricing from component vendors, cushioning cost spikes and enabling focus on high-margin segments.IDC expects average selling prices to rise due to cost pressures, reinforcing premiumization even in a down year.For mobile operators, distributors, and ecosystem partners, this demands more selective portfolio planning. Prioritizing vendors with negotiating power, resilient supply chains, and clear premium strategies will be critical for maintaining availability and profitability.Where Smartphone Growth Opportunities EmergeThe smartphone market is entering a phase where value creation comes less from aggregate unit growth and more from targeted strategies around premium positioning, AI capabilities, and regional dynamics.Three growth themes emerge from IDC's data:Apple and Samsung's expanding combined share and record ASPs show consumers will pay more for tangible value in performance, AI capabilities, camera quality, and ecosystem integration. Vendors that articulate a clear "why upgrade now" story — especially tied to AI-enhanced experiences — will capture disproportionate wallet share.Samsung's success with the Galaxy Z Fold 7 and AI-enabled A-series demonstrates how next-generation form factors and on-device intelligence can scale beyond niche status. For component suppliers, app developers, and cloud providers, this creates opportunities around optimized silicon, edge AI frameworks, and new UX patterns designed for foldables and AI-forward devices.Vivo's India reliance and OPPO's China dependence illustrate a broader pattern: regional champions can grow through precision execution in core markets, even as global competition intensifies. Growth opportunities increasingly favor vendors and partners with deep understanding of local regulatory environments, channel structures, and consumer financing models.Outlook for Premium Smartphone InnovationThe strategic question for industry stakeholders isn't whether the smartphone market will grow in 2026 — it likely won't — but rather who will use this constraint period to strengthen their innovation and positioning for the next up-cycle."While 2025 was a positive year for smartphones, the industry is now facing a distinctly different outlook. The memory shortage, which is widely considered an unprecedented supply chain disruption, will cause the market to decline in 2026, and the duration of the shortage will ultimately determine the extent of the market contraction," said Ryan Reith, group vice president at IDC.That being said, I believe those vendors investing now in premium experiences, AI capabilities, and supply chain resilience will be best positioned to capture value when volume growth returns. However, the core smartphone category does appear to be saturated in some key markets.More...

In the span of just two decades, mobile money offerings have transformed from a simple money transfer mechanism into a comprehensive financial ecosystem serving billions of under-served people worldwide.What began as an experiment in leveraging mobile phones for basic transactions has evolved into sophisticated financial super-apps that rival traditional banking infrastructure.This transformation represents a fintech innovation, and a fundamental re-imagining of how financial services can reach those left behind by conventional banking systems.Mobile Money Market DevelopmentAccording to the Juniper Research latest market study, more than 1.6 billion adults globally remained without access to a bank account in 2025.The distribution of this un-banked population reveals stark regional disparities: Africa and the Middle East account for 691 million un-banked adults, while the Indian Subcontinent contributes 497 million.In regions like Africa and the Middle East, over half of the adult population lacks access to traditional financial rails, while Asia (excluding the Far East and China) shows just over a third of adults remaining un-banked.These aren't merely statistics; they represent real barriers to economic participation. Traditional banks struggle to serve these populations due to geographical constraints, high operational costs, and the mismatch between their service offerings and the needs of lower-income customers.The result has been reliance on informal financial networks that are expensive, inefficient, and vulnerable to theft. Mobile money addresses these challenges through a fundamentally different approach.By leveraging widespread mobile phone penetration and establishing networks of local agents, providers have created accessible touch-points where traditional banks could not. These agents — often existing retail outlets or airtime shops — enable users to convert between cash and digital value, effectively bridging the gap between the informal cash economy and formal financial services.The Path to Mobile Money MaturityThe evolution of mobile money demonstrates remarkable sophistication. What started as basic peer-to-peer transfers has expanded to encompass micro-credit, micro-insurance, and micro-savings products.This progression draws on lessons learned from pioneering initiatives like Muhammad Yunus's Grameen Bank in the 1980s, which demonstrated that low-income individuals could responsibly use financial services when products were appropriately designed.The research reveals that smartphone penetration across emerging markets averaged approximately 62.5 percent in 2025 and is forecast to reach 74.25 percent by 2030.This technological shift is pushing providers beyond simple USSD-based interfaces toward sophisticated user experiences that incorporate personalization, enhanced security, and integration of multiple financial services.Perhaps most significant is the industry-wide movement toward interoperability.According to GSMA research cited in the report, roughly two-thirds of mobile money providers now offer open APIs to third parties. This shift from closed, siloed systems to open, modular platforms is accelerating innovation and expanding use cases.Successful vendors like MTN Mobile Money in Africa have experienced substantial developer engagement following the launch of public API platforms, illustrating the commercial value of openness.The Mobile Money Regulatory CatalystRegulation has emerged as a powerful growth catalyst in markets where policymakers have struck the right balance between consumer protection and innovation.Kenya's M-PESA stands as the exemplar: launched by Safaricom in 2007, it succeeded partly because the Central Bank of Kenya adopted a pragmatic regulatory approach that enabled telecommunications companies to offer financial services without imposing full banking requirements.This regulatory flexibility allowed M-PESA to innovate rapidly while maintaining consumer protection standards, establishing it as one of the most successful mobile money platforms globally.By contrast, regulatory gaps, inconsistencies, or sudden policy shifts can significantly constrain growth. Providers must navigate complex anti-money laundering and Know Your Customer requirements while serving customers who simply want alternatives to cash.Cross-border transactions face additional complications due to varying standards and licensing requirements across jurisdictions.The Mobile Money Innovation Path to 2030The research forecasts that over 53 percent of the adult population in emerging markets will use mobile money services by 2030, representing an additional 370 million users from 2026 levels, reaching a total of 2.2 billion users.This growth will be driven primarily by expanding interoperability and integration with banks, financial institutions, and fintech partners.The opportunity lies in moving beyond basic transactions to comprehensive financial services. As platforms integrate with banks for account linking, connect with remittance networks for cross-border flows, and partner with retailers for merchant acceptance, they transform from simple payment tools into primary financial accounts for previously excluded populations.For stakeholders in this ecosystem — from mobile network operators to fintech startups — the strategic imperative is clear: build open API ecosystems, develop relationships with key partners, and prioritize interoperability.Outlook for Mobile Money Applications GrowthThe platforms that successfully navigate this transition will capture the next wave of digital financial inclusion. Those that remain siloed risk rapid obsolescence as users gravitate toward comprehensive, interconnected financial super-apps that meet their full range of financial needs from a single access point."The industry-wide push towards expanding interoperability between mobile money platforms is enabling growth and improving financial inclusion for low-and-middle income population groups," said Jawad Jahan, research analyst at Juniper Research.That being said, I believe the mobile money growth trajectory is far from complete. With 1.56 billion people still un-banked and technology continuing to advance, the opportunity to extend financial services to under-served populations remains substantial.Moreover, the potential impact on individual livelihoods and broader economic development in emerging markets is truly profound.More...

For two decades, enterprise Software-as-a-Service (SaaS) has been the dominant force reshaping how organizations consume business applications. Yet as artificial intelligence (AI) capabilities accelerate, a critical question emerges.Will AI apps render the SaaS model obsolete? The answer, as with most paradigm shifts, is far more nuanced than a simple yes or no.Enterprise SaaS isn't dying, but it's growing much older. And maturity, while a testament to success, brings its own set of challenges.Enterprise SaaS Market DevelopmentThe U.S. enterprise software market is now highly saturated, and the momentum that once seemed unstoppable has definitively slowed. And yes, AI is a contributing factor.The B2B SaaS expansion era that defined the last decade, characterized by rising customer counts and reliable growth within existing accounts, has reached its natural limits. What's particularly telling is the shift in CIO priorities. While SaaS vendors were racing to expand their footprints, something consequential was happening in enterprise IT departments: technical debt was accumulating rapidly.Today, that debt — especially siloed data sources — represents a strategic vulnerability in an AI-first world. As a result, enterprise leaders are pivoting from expanding SaaS procurement to prioritizing modernization under modern data platforms.This isn't a rejection of SaaS; it's a recalibration of where it fits in the IT stack.The Software Platform PivotRecognizing this shift, B2B SaaS incumbents are making strategic moves that reveal their understanding of the changing landscape.According to the latest market study by TBR, SAP's Business Technology Platform has achieved attach rates above 80 percent in modernization cycles.That demonstrates how successfully the company has re-positioned platform capabilities not as optional middleware but as mandatory infrastructure for modernization.By integrating Signavio and LeanIX, SAP has built a comprehensive portfolio spanning process intelligence to coherent data and extension strategies. Salesforce is pursuing a data-first approach with Data Cloud as the centerpiece of modernization discussions, working to consolidate fragmented CRM data models and unify cross-cloud metadata.MuleSoft remains essential for stitching legacy systems into AI-ready architectures. Early Data Cloud wins indicate customers view it as foundational for copilots and agentic workflows, not merely another add-on. Microsoft, Adobe, and ServiceNow are following similar paths, each developing proprietary AI small language models (SLMs) optimized for their specific domains.Microsoft's Phi family targets low-cost, low-latency inference across Azure and edge devices. ServiceNow has expanded its Now LLM with domain-tuned variants for IT, HR, and customer operations.Adobe is developing SlimLM with models ranging from 125 million to 7 billion parameters for on-device document assistance.The Prediction That MattersPerhaps the most significant insight from current market dynamics is this prediction: Platform-as-a-Service (PaaS) revenue will eventually outpace SaaS revenue for cloud software vendors.This is a recognition that the strategic center of gravity is shifting.Traditional B2B SaaS applications remain essential as systems of record and governance layers, but they're increasingly viewed as baseline infrastructure rather than the primary source of differentiation and growth.The market is entering what's best described as a long transition rather than a sharp break. Enterprises will likely operate in a hybrid state for years, with SaaS, PaaS, and AI agents coexisting and evolving in parallel.Current AI capabilities simply aren't advancing fast enough to support definitive claims about SaaS's decline. Agent reliability, regulatory frameworks, data architecture modernization, and small language model economics remain unresolved variables. Enterprise Software OpportunitiesFor technology leaders and investors, this transitional period presents distinct opportunities. Vendors with strong software platform portfolios and credible AI small language model roadmaps are best positioned to capture growth.The ability to harmonize data, reduce AI inference costs, and embed agentic automation across workflows will increasingly differentiate vendor winners from laggards.The strategic question has evolved from "Will SaaS survive?" to "How will its role change as intelligence layers mature above it?"Partner ecosystems will prove critical, as services partners and vertical industry specialists contribute task-tuned AI models through marketplaces and registries.Monetization models are still emerging, with usage-based AI SKUs and premium automation tiers representing early experiments in AI-driven app revenue growth. Outlook for Enterprise Software GrowthThe enterprise stack is undergoing its most significant reconfiguration since SaaS emerged. While uncertainty will persist and debates will continue, one thing is clear: the next decade won't be defined by the death of SaaS but by its transformation into foundational infrastructure supporting a new layer of intelligent automation.That being said, I believe for those vendors navigating this transition, success will depend on recognizing that disruption and evolution are not the same thing. The most valuable market position may not be replacing what came before, but building intelligently on top of it.Purpose-built, right-sized Applied-AI Initiatives will provide the next chapter of IT growth.More...

For years, the cloud computing sector operated on an elegant premise: compute and storage were borderless commodities, and scale wins. The hyperscalers built empires on that assumption. But a confluence of geopolitical friction, data nationalism, and hard-learned lessons about digital dependency is now rewriting that traditional rulebook.Gartner's latest market study found worldwide sovereign cloud Infrastructure-as-a-Service (IaaS) spending will reach $80 billion in 2026 — that's a 35.6 percent surge from 2025 — climbing further to $110 billion by 2027.This is a structural shift in how governments, enterprises, and critical infrastructure operators think about where their data lives, who controls it, and what national interests it serves.Sovereign Cloud Market DevelopmentThe regional breakdown is where the real strategic intelligence lies.China leads all markets at an estimated $47 billion in 2026, underscoring that state-driven infrastructure investment is a long-established playbook in Beijing.North America follows at $16 billion, though both regions are growing at a comparatively modest 20-29 percent rate. The more instructive change is unfolding elsewhere.The Middle East and Africa (89 percent growth), Mature Asia/Pacific (87 percent), and Europe (83 percent) are the three fastest-growing regions in this space.Europe's trajectory is perhaps the most consequential for the global cloud industry: spending is expected to jump from $6.9 billion in 2025 to $12.6 billion in 2026, and then to $23.1 billion in 2027; at which point it will surpass North America entirely.That progression, tripling in just two years, reflects not just budget increases, but a fundamental reorientation of business technology strategy across the continent.Two other Gartner data points deserve serious scrutiny.First, approximately 80 percent of sovereign cloud IaaS spend will come from net-new digital solutions or legacy on-premises workloads finally making their cloud transition, but now routing to local providers rather than global hyperscalers.Second, and perhaps most disruptive, Gartner estimates that 20 percent of existing hyperscaler workloads will be migrated to local cloud providers through what analysts are calling "geopatriation"; a term that didn't exist in the enterprise lexicon five years ago.Geopatriation, specifically the strategic repatriation of digital assets to align with national or regional interests, is the concept that global hyperscalers should find most alarming.A European bank moving core banking workloads off an American-owned cloud, or a telecoms provider opting for a locally governed infrastructure stack, represents real revenue migration. The recent high-profile case of senior International Criminal Court staff being cut off from cloud services for political reasons is precisely the kind of event that concentrates minds in boardrooms and government ministries alike.A growing number of European organizations are now making formal commitments to direct a fixed percentage of annual technology spending to local IT providers. That is not a technical choice, it is an executive policy posture.Cloud Computing Geopatriation MomentumThe hyperscalers are not standing still. AWS launched its European Sovereign Cloud as a generally available offering in early 2026, providing EU-resident infrastructure with governance designed to address regulatory concerns.IBM introduced its Sovereign Core platform, enabling customers to deploy and manage cloud computing and AI workloads under their own organizational authority.These are meaningful moves, but Gartner's analysts are clear that treating digital sovereignty purely as a compliance and security checkbox is a strategic miscalculation.Local cloud computing providers, purpose-built for sovereign requirements, are positioned to capture the most value as the market evolves and continues to restructure.Outlook for Sovereign Cloud Apps GrowthFor technology leaders, three trends will dominate in the next 24 months. The first is the rise of hybrid sovereign architectures; organizations maintaining hyperscaler relationships for some workloads while deploying local sovereign infrastructure for regulated or sensitive data.The second is Applied-AI Initiatives, as sovereign AI processing requirements accelerate investment in local compute capacity. The third is government procurement reform, with public sector buyers increasingly mandating sovereign cloud as a baseline requirement."Governments will remain the main buyers to meet digital sovereignty needs, followed by regulated industries and critical infrastructure organizations, such as energy and utilities and telecommunications," said  Rene Buest, senior director analyst at Gartner.That being said, I believe the forecast of $110 billion in IaaS spending is the one that should shape the strategic investment roadmap. Strategic IT infrastructure independence, and avoiding the predictable challenge of vendor lock-in, will drive investment decisions across the globe.More...

The most consequential infrastructure decision an electric utility executive will make this decade has nothing to do with poles, wires, or substations; it's a software decision.The global power grid is undergoing a transformation so fundamental to future economic growth. It's become a total re-imagining of energy generation and optimal delivery.From a predictable, one-way system built around centralized generation, to a dynamic, bidirectional network that must simultaneously balance millions of decentralized inputs, while bracing for the twin pressures of climate volatility and surging demand.For C-suite leaders across energy, technology, and finance, this shift is no longer a horizon event. It is the operational reality of today, and the strategic battleground of the next decade.Grid Intelligence Market DevelopmentAccording to the latest market study by ABI Research, the core Grid Management software market is projected to reach $77.2 billion by 2035. That figure is a proxy for how much value the world is placing on grid intelligence, stability, and infrastructure resilience.Today, investment is concentrated in Advanced Distribution Management Systems (ADMS) — the foundational layer that gives utilities real-time visibility over their networks.But the fastest-growing segment is Distributed Energy Resource Management Systems (DERMS). As rooftop solar proliferates and commercial battery storage becomes mainstream, utilities must manage not one power plant, but millions of them.By 2035, DERMS investment is expected to nearly rival ADMS; it's a signal that the "edge" of the power grid is becoming as strategically critical as its core infrastructure.Geographically, North America and Europe are leading, propelled by net-zero mandates and the urgent need to retire aging legacy infrastructure. However, the Asia-Pacific region is accelerating rapidly.Urbanization at scale and the leapfrogging of traditional grid architecture are creating extraordinary demand for Smart Grid software capable of powering the next generation of mega-cities.For modern technology vendors, this is where the long-term volume story lives.Forces Reshaping the Global Power IndustryThree structural trends will determine which utilities thrive, and which technology providers capture the forward-looking market opportunity.The first is the rise of the prosumer. The consumer who passively draws from the power grid is giving way to one who both consumes and produces energy.Mass EV adoption and residential solar have created a "Grid of Things"; it's an ecosystem where a vehicle battery might supply power back to the city during a peak demand event.Managing this bidirectional complexity at scale requires sophisticated orchestration software. Companies that can bridge residential hardware and utility-scale systems will define the next wave of competitive differentiation.The second is AI-driven predictive resilience. Reactive grid management is no longer sufficient in an era of intensifying extreme weather. The next generation of platforms will use artificial intelligence (AI) and machine learning to anticipate failures before they cascade.GIS technology is already evolving from static network maps into dynamic "Digital Twins" — essentially live virtual replicas of the grid that allow operators to stress-test scenarios in real time, compressing outage response from hours to minutes.For corporate boards and executives thinking about enterprise risk, this capability is quickly shifting from competitive advantage to baseline expectation.The third is cyber-security by design. A more digitized, interconnected grid is also a more exposed one. The integration of IoT sensors, cloud platforms, and remote management tools has expanded the attack surface for ransomware and state-sponsored cyber threats.Security can no longer be bolted on after the fact. Utilities will increasingly demand Sovereign Cloud architectures and zero-trust frameworks as non-negotiable procurement criteria, A meaningful share of that growing market will flow to vendors who can deliver it credibly.The Grid Intelligence Strategic ImperativeThe path to 2035 is not without friction. Regulatory frameworks are struggling to keep pace with technological change, and a persistent workforce skills gap continues to constrain deployment timelines. These are very real marketplace headwinds.But the strategic calculus is now clear. Software is the only mechanism capable of reconciling the intermittency of wind and solar with the relentless load growth driven by data centers and electrified transport.For investors, the energy transition is fundamentally a software investment thesis. For utility leaders, digital orchestration is not a modernization project; it is an existential capability."Grid management software solutions will be critical technologies for utility companies and grid operators to connect critical infrastructure, commercial buildings, and households to the grid and meet their energy needs," said Michael Larner, distinguished analyst at ABI Research.That being said, I believe the utilities that commit to this transformation today will be the ones with the operational agility to absorb tomorrow's disruption. Those that delay are not simply falling behind on technology; they are accumulating risk at a pace the grid can ill afford.More...

In the past decade, many organizations have pursued a singular vision of cloud-centric transformation; consolidating data, applications, and compute into centralized datacenters managed by hyperscalers.Yet, the explosive growth of connected devices, the rise of Applied-AI and real-time data requirements, and new operational models are reshaping that paradigm.Edge computing — the practice of processing data closer to the source where it is generated — has moved from niche experiment to strategic imperative.According to the latest market study by International Data Corporation (IDC), edge computing is now the new core in the distributed Global Networked Economy.Edge Computing Market DevelopmentIDC forecasts global spending on edge computing solutions will reach approximately $450 billion by 2029, that's up from $265 billion in 2025, driven by rapid advancements in edge-based AI workloads, distributed architectures, and enterprise transformation initiatives.Several key data points from IDC’s analysis stand out:Edge computing spending has grown significantly, indicating that distributed computing has already moved well past early adoption.IDC’s forecast now spans more than 1,000 named enterprise use cases across six domains (including AI, IoT, AR/VR, drones, and robotics), underscoring the breadth of application scenarios.Edge investment is no longer narrowly hardware-centric. While hardware, especially AI-accelerated processors, still leads early spending, services are expected to surpass hardware by the end of the forecast period.Taken together, these figures paint a picture of institutionalized demand for edge technologies, not just experimental pilots. Other IDC analyses reinforce this trajectory, with previous forecasts suggesting compound annual growth rates in double digits.Why Edge Apps Matter: Drivers and Use CasesThe strategic importance of edge computing stems from multiple converging trends:Latency, Local Context, and Real-Time InsightApplications such as autonomous vehicles, industrial automation, healthcare monitoring, and smart cities demand processing decisions in milliseconds — far faster than centralized cloud responses allow.Edge computing enables this low-latency capability by moving compute to where the data originates.Applied-AI at the EdgeAs enterprises deploy increasingly sophisticated AI models, there is a shift from cloud-centric inferencing to distributed, edge-enabled intelligence.Use cases include real-time predictive maintenance on the factory floor, real-time fraud detection in financial services, and context-aware customer experiences in retail.IDC’s expanded domain taxonomy highlights AI as one of the fastest-growing drivers of edge investment.Sector-Specific Business TransformationDifferent industries exhibit unique edge patterns:Retail & Services: Video analytics, personalized experiences, and inventory optimization demand distributed compute.Manufacturing & Resources: Predictive maintenance and autonomous quality control rely on low-latency processing.Financial Services: High-speed, secure fraud detection mandates compute at the network edge.Telecommunications Providers: Investments in multi-access edge computing (MEC), content delivery networks (CDNs), and virtualized network functions (VNFs) add up to significant infrastructure commitments.This breadth of commercial relevance explains why conventional cloud investments are now being complemented. And in some cases challenged, by a diverse portfolio of edge initiatives.Opportunities and Strategic ImperativesThe transition from cloud-dominant thinking to hybrid, distributed architectures opens multiple opportunities:Ecosystem ExpansionEdge computing ecosystems are expanding beyond traditional hardware vendors to include software platforms, middleware, and services players. Organizations that help orchestrate, secure, and manage distributed edge environments are poised for growth.Edge-as-a-ServiceAs IDC forecasts indicate that services will surpass hardware investments, offerings that simplify edge deployment and operations; from managed edge platforms to scalable infrastructure-as-a-service, will become strategic differentiators.Vertical-First SolutionsGeneric edge technologies are giving way to industry-specific solutions that address unique operational challenges. Vendors that tailor offerings to healthcare, manufacturing, logistics, or telecommunications stand to capture disproportionate share.AI and Data PartnershipsEdge computing accelerates real-time data insights; but it also intensifies the need for robust data governance, security, and interoperability. Partnerships spanning cloud providers, network operators, AI frameworks, and enterprise systems will define competitive advantage.Looking Beyond the NumbersEdge technologies are transforming from tactical performance enablers to strategic infrastructure that supports real-time AI, distributed decision making, and novel business models.Organizations that embrace this shift, while thoughtfully balancing cloud, edge, and centralized IT investments, will be better positioned to compete in an era where speed, context, and autonomy matter as much as scale."The combination of maturing edge architectures and rapid AI development is fundamentally redefining how organizations process and act on data," said Alexandra Rotaru, data & analytics manager at IDC.That being said, I believe Applied-AI Initiatives at the edge are no longer experimental. The impact is already visible across industrial automation, smart retail, connected vehicles, and next‑generation healthcare services.More...

Across the globe, the companies providing your mobile phone plan are no longer just the carriers you know. They are your bank, your supermarket, and soon your fintech app.The Mobile Virtual Network Operator (MVNO) model, long a niche mechanism for budget carriers to resell network capacity, has entered a bold new era of growth.It's driven by enterprises seeking to deepen customer loyalty and diversify revenue in an increasingly competitive Global Networked Economy.MVNO Market DevelopmentAccording to the latest Juniper Research market study, the global MVNO subscriber base will climb from 333 million in 2026 to 438 million by 2030; that's an addition of over 100 million users in just four years.While that subscriber growth represents just 3.4 to 4.2 percent of total global mobile subscribers, the total MVNO revenue is forecast to reach $54.4 billion by 2030.Fueling much of this growth is the emerging MVNO-in-a-box (or Telecom-as-a-Service) market; a category forecast to reach $1.9 billion in 2030.Where previously a provider would need to commit to large wholesale traffic agreements and absorb heavy sunk costs, today's MVNO-in-a-box solutions offer flexible, scalable, rapid-deployment models.Fintechs Leading the MVNO TransitionNo sector has embraced the MVNO opportunity with more urgency than fintech.Since 2024, high-profile launches from Nubank in Brazil, Revolut across the UK and Poland, Klarna in the U.S. market, N26 in Germany, and UK lender Lendable have signalled that mobile connectivity is fast becoming a core pillar of the modern digital banking proposition.The logic is straightforward: fintechs already operate sophisticated digital platforms, hold regulatory approvals (including eKYC capabilities that streamline subscriber onboarding), and manage large, data-rich customer bases.Adding mobile connectivity deepens ecosystem lock-in and gives these companies a new lever to reduce churn. When your bank also provides your phone plan, switching becomes an altogether more inconvenient proposition.Revolut's multi-country service rollout is perhaps the most instructive example. Rather than a single-market pilot, Revolut has used MVNO-in-a-box infrastructure to pursue a genuinely international strategy.It's a model that would have been prohibitively complex just a few years ago. Now it is a preview of how Superapp ambitions and mobile connectivity will increasingly converge.Retailers Were the Original MVNO DisruptorsIt is easy to forget that supermarkets and retailers were pioneers of the MVNO model.These retailers succeeded by leveraging formidable advantages: enormous existing customer bases, strong brand trust, and physical store networks that could serve as distribution and support channels for SIM products.Today, the opportunity has evolved.The next frontier for retail MVNOs is building ecosystem-focused mobile services that integrate with broader retail rewards programs and customer data infrastructure.When a mobile subscription earns you loyalty points and unlocks priority access to a retailer's services, the value proposition becomes more difficult for traditional carriers to replicate.Differentiation, Data, and the Superapp HorizonThe most significant risk for new market entrants is a poor customer experience that undermines the company's core business far more than a failed product line ever could.Mobile is personal. It is ever-present. Getting it wrong is very public.The enterprises most likely to thrive will be those that treat mobile not as a standalone revenue line, but as an integrated layer within a broader data and loyalty strategy.This means investing in analytics platforms that connect subscriber behavior to core business metrics, personalizing plan offerings based on customer insight, and building customer service capabilities.The celebrity and influencer MVNO space — exemplified by Ryan Reynolds' Mint Mobile, which grew to a $1.35 billion valuation before being acquired by T-Mobile in 2023 — offers a useful cautionary tale and template in equal measure.Fame drives awareness; it does not drive retention. Mint Mobile succeeded because it offered competitive pricing and innovative bulk-purchase tariff structures. The celebrity was not the reason.Outlook for MVNO Applications GrowthDuring 2030, the MVNO market's center of gravity will continue shifting away from pure-play discount carriers and toward embedded connectivity models within broader ecosystems.The Superapp vision, in which a single platform manages your finances, shopping, entertainment, and phone plan, is no longer a concept confined to Southeast Asia. It is being actively built in Europe, Latin America, and beyond."As MVNOs become increasingly easy to launch, new entrants will struggle to compete on unique selling points alone. Alongside quality connectivity, a seamless customer experienced backed by data analytics and personalized customer journeys will be critical," said Alex Webb, senior research analyst at Juniper Research.That being said, I believe for market leaders with the right infrastructure and the right MVNO partner, mobile connectivity can become the connective tissue that binds their entire customer relationship together.More...

Surging memory costs are about to reshape the economics of the global personal computer (PC) and mobile smartphone markets, and not in subtle ways.I see this as more than a cyclical component spike; it is a structural stress test for hardware vendor business models, channel strategies, and digital transformation roadmaps.When DRAM and NAND become the scarce fuel of an AI‑driven world, every assumption about price bands, refresh cycles, and good-enough devices comes under pressure.Device Memory Market DevelopmentGartner now expects soaring memory costs to drive worldwide PC shipments down 10.4 percent and smartphone shipments down 8.4 percent in 2026 versus 2025 – that's the steepest contraction in device shipments in over a decade.This is not about weak demand for compute; it is about a single component class overwhelming the bill of materials and forcing difficult trade‑offs.The key number: combined DRAM and SSD prices are forecast to surge by about 130 percent by the end of 2026. That increase alone is expected to push average PC prices up by 17 percent and smartphone prices up by 13 percent compared with 2025 levels.Device manufacturers must either absorb the cost and watch margins erode, or pass it on and watch unit volumes fall; and Gartner’s forecast implies most will choose margin preservation over chasing volume at any price.For device vendors that have spent years optimizing cost structures to hit aggressive entry‑level price points, this is a profound reversal.Memory is projected to rise from 16 percent of PC bill of materials in 2025 to 23 percent in 2026, turning what used to be one line item among many into a dominant profit lever.The End of True Entry‑Level DevicesPerhaps the most striking implication is Gartner’s view that the sub‑$500 entry‑level PC segment will effectively disappear by 2028.When memory alone consumes nearly a quarter of the BOM, the room left for CPUs, displays, connectivity, and industrial design in a budget device narrows to the point of being untenable.Gartner expects this pressure to be most acute in low‑margin, price‑sensitive segments.Entry‑level Windows laptops for education, basic SMB use, and emerging markets face a squeeze: either they ship with visibly compromised specs that undermine user experience, or they cross psychological price thresholds that send buyers looking for alternatives.A similar pattern is expected in smartphones, where basic models will take the biggest hit as memory‑driven price increases push buyers toward refurbished or second‑hand devices or lengthen replacement cycles.Premium devices, in contrast, are relatively insulated. Higher margins and customer willingness to pay for Applied-AI capabilities, better cameras, and premium materials make it easier to absorb component inflation or reposition products slightly higher in price tiers.Gartner even notes that higher AI PC prices may delay AI PC penetration reaching 50 percent of the market until 2028, slowing what many vendors had assumed would be a rapid AI‑everywhere inflection.For channel partners and OEMs, the strategic shift is clear: the growth and margin pool is moving up and over; up the value stack and over to adjacent offerings like services, warranties, and device‑as‑a‑service models, rather than down into volume‑driven, low‑end hardware.Longer Device Lifecycles and Mounting Risk  One of the most consequential, but often underappreciated, effects of rising device prices is on lifecycle management. Gartner expects PC lifetimes to increase by about 15 percent for business buyers and 20 percent for consumers by the end of 2026.On the surface, that looks like a cost saving; in practice, it transfers risk from enterprise CFOs to CISOs and CIOs. Longer device refresh cycles mean more endpoints running older operating systems and firmware, often beyond the period of full vendor support.Gartner explicitly flags increased exposure to security vulnerabilities and greater challenges managing aging devices as organizations delay upgrades.In regulated industries or zero‑trust initiatives, this creates an uncomfortable tension: budgets will feel less flexible just as the security case for modernization strengthens.On the consumer side, extended device life will amplify fragmentation in OS and app support. Developers and platform owners will need to decide how far back to support legacy devices whose hardware was never designed for today’s AI‑centric workloads, while operators and retailers may see refurbished devices play a larger role in their portfolios.Outlook for Device Market Growth PotentialThree key trends and growth opportunities emerge from this disruption.  Value will increasingly shift from pure hardware volume to orchestrated device ecosystems and services. Vendors can package PCs and smartphones with cloud management, security, AI productivity tools, and predictable lifecycle economics.The rise of refurbished and second‑life devices will become a mainstream, strategically managed channel rather than a peripheral afterthought.AI‑driven devices will need a thoughtful, outcomes‑based narrative to justify their higher price points in an environment of constrained budgets.Surging memory costs are acting as a forcing function for the entire device value chain. They are accelerating the shift toward premium, service‑wrapped, AI‑capable ecosystems, while simultaneously expanding the role of refurbished hardware and longer lifecycles."Overall, device vendors and channels face a critical window in the first half of 2026 to optimize pricing and protect margins before component inflation compresses profitability from the second quarter onward," said Ranjit Atwal, senior director analyst at Gartner.That being said, I believe for vendors willing to rethink their economics and engagement models, this memory shock is less an existential threat and more a catalyst to exit commodity traps and build more resilient, value‑centric device market development strategies.More...