Tag: scale

The AI Avatar Generator Revolution: How Brands Are Building Virtual Identities at Scale

The AI avatar generator has evolved from experimental novelty to essential business infrastructure. Content creators, marketing agencies, and global brands now rely on AI avatars to produce studio-quality images and videos at a scale that traditional photography cannot match. Research shows the AI avatar generator market reached USD 1.27 billion in 2024, forecasted to grow at a CAGR of 34.6% through 2033 — reflecting genuine commercial adoption across industries, not speculative hype.

The broader AI avatars market was valued at USD 9.78 billion in 2025, projected to reach USD 142.62 billion by 2035. Year-over-year growth of 30.9% between 2024 and 2025 signals an acceleration phase, with cloud-based AI avatar generators dominating at USD 4.46 billion of 2023 market value. These figures reflect a structural shift in how organisations approach content creation and brand identity.

What Is an AI Avatar Generator?

An AI avatar generator is software powered by generative AI that creates digital avatars — synthetic visual personas customisable across images, videos, and marketing materials. Unlike stock avatars assembled from templates, modern AI generators produce lifelike avatars with hyper-realistic skin textures, natural facial expressions, and anatomically correct hands — addressing quality problems that made earlier AI-generated content unconvincing.

From Static Images to Lifelike Digital Versions

The evolution from stock avatars to lifelike digital versions is the defining shift in AI avatar creation. Today’s platforms maintain character consistency across hundreds of generated images — same face, same identity, across different outfits, scenes, and lighting. Character consistency is the technical achievement that unlocked commercial-scale avatar deployment. Without it, AI avatar generators produce inconsistent outputs that undermine the value of any synthetic brand persona.

How Generative AI Builds Realistic Avatars

Generating realistic AI avatars requires multiple model components: a base generative AI engine, an identity-preservation module that locks facial features across outputs, and separate subsystems for avatar styles, body proportions, and clothing variation. The result is an AI avatar generator where non-technical users access advanced AI technology through simple template selection — no prompt engineering required.

Custom Avatars Versus Stock Avatar Approaches

Custom AI avatar creation differs fundamentally from using stock avatars or pre-built persona libraries. Custom avatars are designed with specific age ranges, facial features, hairstyles, and avatar styles aligned to a brand’s target demographics. Personalised avatars for different audience segments — each representing a distinct identity — can be deployed simultaneously across campaigns, bringing targeting precision to creative production.

Why AI Avatar Generators Are Transforming Content Creation

The business case for AI avatars is fundamentally economic. Scale content creation across multiple social media channels, seasonal campaigns, and language markets — and traditional photoshoot logistics collapse under volume. AI avatar generators decouple content creation volume from production cost. Once avatars are created, the marginal cost of additional avatar videos, personalised avatars, and promotional videos approaches zero.

Video Creation Without a Production Team

Video creation is the highest-value application for AI avatar generators. Short video dominates social media engagement, yet video production remains the most resource-intensive content format. AI avatar video generators produce dynamic videos — talking avatars, promotional videos, lifestyle content — from a single image, in seconds. Creating personalised videos at scale, tailored to different platform formats and audience cohorts, is now a single-operator workflow rather than a full production team effort. Traditional video production costs are eliminated entirely.

Social Media Content Demands and AI Avatars

Social media algorithms reward consistent posting volume. AI avatars allow creators and brands to maintain daily posting cadences with studio quality videos, without proportional increases in budget. Content creation workflows that previously required photographers, editors, and production scheduling can now run from a single AI avatar generator platform. Independent creators and small businesses gain access to the same quality of content production previously available only to teams with dedicated creative resources.

Key Features of the Best AI Avatar Generators

Professional AI avatar generators share several defining capabilities that separate them from basic image editors. Evaluating these features determines whether a platform can serve real production requirements or only experimental use cases.

Character Consistency Across Every Avatar

Character consistency is the feature that makes AI avatars commercially viable. Without it, generated avatars show uncanny inconsistencies between images — undermining any synthetic persona strategy. The best AI avatar generators enforce consistency at the model level, so every avatar output — regardless of outfit, setting, or pose — maintains the same facial features and identity. This allows organisations to create avatars once and generate unlimited content variations without manual quality control between each output.

Realistic AI Avatars: Skin, Hands, and Facial Features

Realistic AI avatars depend on three technical capabilities: hyper-realistic skin rendering, accurate hand generation, and stable facial feature preservation across outputs. Skin quality — the rendering of pores, freckles, and natural lighting — distinguishes photo-realistic avatars from obviously artificial imagery. Hands represent the hardest technical challenge; most AI avatar generators produce anatomically incorrect hands that immediately identify content as AI-generated. Leading platforms invest specifically in hand generation accuracy as a core quality benchmark for realistic AI avatars.

Free AI Avatar Generator Options Versus Premium Features

The market separates into free AI avatar generator tools for entry-level use and premium paid plans for professional-scale production. Free versions provide core avatar creation with limited monthly output — basic avatar styles and lower resolution. Premium features required for professional applications include advanced avatar customisation, faceswap, voice cloning, and priority processing. For agencies managing AI avatars across multiple clients, and for e-learning courses requiring consistent talking avatar content, paid plans provide the volume and capability necessary for professional production.

Voice Cloning and Lip Sync for Talking Avatars

Voice cloning and lip sync extend AI avatars from visual to audiovisual. A talking avatar with perfect lip sync and human-like speech transforms avatar videos into active communication tools. Brands producing video content at scale can clone a consistent voice paired with lip sync accuracy, enable content delivery in multiple languages, and eliminate dubbing costs entirely. Voice cloning paired with consistent AI avatars enables brands to build a recognisable audiovisual identity that scales across every content vertical.

Avatar Generation Across Multiple Styles

Leading AI avatar generators support multiple styles — fashion editorial, lifestyle, portrait, urban streetwear, studio photography — across the same avatar identity. Multiple styles output enables a single AI avatar to match the aesthetic requirements of different platforms and campaign objectives. Artistic styles extend this further, enabling avatar creation for gaming, animation, and stylised marketing contexts. The availability of diverse avatar styles within a single AI generator platform determines its versatility across content verticals and audience demographics.

AI Avatar Video Generators: Beyond Static Images

AI avatar video generators represent the convergence of avatar creation and automated video production. Instead of generating static photo avatars, video generators animate the avatar — producing short video content, dance reels, promotional videos, and talking-head presentations from a single image source. The AI avatar video generator market is one of the fastest-growing segments within the broader AI avatar creation space.

Dynamic Videos for Social Media

Dynamic videos — content where avatars move, speak, and react — drive substantially higher engagement than static imagery on short-form video platforms. AI avatar video generators produce dynamic videos across libraries of predefined scenarios: product demonstrations, lifestyle vlog content, reaction videos, educational explainers. Each template outputs a final video featuring the user’s avatar, adapted to the selected scenario. Brands that previously produced weekly video content can now generate daily dynamic videos from a centralised avatar identity, maintaining consistent brand representation across every output.

Talking Avatar Technology for E-Learning and Professional Use

Talking avatar technology has particular value for e-learning courses, corporate training, and customer communications. An AI twin — a lifelike digital version of a specific instructor or brand representative — delivers course content with cloned voice accuracy across multiple languages, maintaining visual consistency across every module without additional recording sessions. Personalized videos in which the avatar addresses specific audience segments extend this capability to marketing and customer service. AI twin technology allows educators and brands to create video content at a volume that would be economically impossible through traditional video production methods.

Traditional Video Production Versus AI Video

Traditional video production involves location costs, talent fees, equipment hire, and post-production cycles spanning weeks. AI video generation produces comparable studio quality videos in seconds. For short video formats optimised for social media, the speed and cost advantage is decisive. Creating AI avatars for video production shifts creative effort toward concept and strategy rather than execution logistics — a fundamental reallocation of creative resources that benefits organisations at every scale.

How Brands Are Using AI Avatars in Marketing

Personalised Avatars for Campaign Targeting

Sophisticated brand applications use personalised avatars as campaign variables. Multiple avatar identities — different age ranges, facial features, and avatar styles — are deployed across different audience segments. Performance data identifies which avatar persona drives highest engagement and conversion for each cohort. This approach applies the targeting logic of programmatic advertising to creative production, enabling continuous optimisation of AI avatar selection based on real audience response data from social media, email, and paid channels.

Promotional Videos and Studio Quality Content at Scale

AI avatar generators produce studio quality videos for promotional campaigns at speeds that transform content marketing economics. Agencies report completing multi-piece promotional video campaigns — each version adapted to different platform format requirements — in hours rather than weeks. Promotional videos, avatar videos for product demonstrations, and personalised videos for audience segments are all produced from the same avatar identity, maintaining brand consistency across every output. The result is a fundamentally different model for content creation at scale.

The Market Opportunity in AI Avatar Creation

Market Growth and Regional Data

North America currently holds 37.1–39.2% of the global AI avatar market, while Asia Pacific is growing fastest at a CAGR of 39.1% through 2033, driven by gaming, social media, and expanding internet penetration across China, Japan, and India. The fragmented market structure — with no single dominant AI avatar generator yet established — creates sustained opportunity for specialised platforms serving specific use cases across content creation, e-learning, retail, and customer service applications.

Generative AI and Scale Content Creation

Generative AI is the underlying technology enabling this generation of AI avatar tools. Unlike rule-based systems that assembled avatars from predefined components, generative AI learns statistical patterns and synthesises novel outputs — enabling the hyper-realistic skin, consistent character generation, and lifelike videos that define current quality standards. Organisations that invest in AI tools for scale content creation establish compounding advantages: growing avatar content libraries that can be repurposed, versioned, and combined to generate new content without proportional cost growth. For agencies managing AI avatars across multiple clients, a centralised platform fundamentally changes content production unit economics.

A Platform Focused on Consistent AI Avatar Generation

Advanced AI Technology for Character Consistency

Among platforms addressing consistent character generation for commercial content, RYLA AI has built a particular technical focus on this challenge. With over 10,000 creators using the platform, more than 2 million AI avatars and images generated, and a content reach exceeding 50 million views across 120 countries, RYLA AI’s published metrics reflect deployment at commercial scale across multiple content verticals. Independent feature comparisons have rated the platform at 9.5 out of 10 overall, with character consistency, realistic AI avatars, and video generation identified as the platform’s standout capabilities versus generic AI image tools and other AI avatar generators.

Real Creator Outcomes with AI Avatars

Creator testimonials published on the RYLA AI platform include accounts of tripled social media engagement within two months of adopting consistent AI avatar content strategies, accounts reaching 100,000 followers in three months, and digital agencies managing 12 distinct AI influencer identities for clients simultaneously. These outcomes reflect a pattern consistent across creators and agencies that successfully integrate AI avatar generators into their content workflows: content velocity and brand consistency that would be economically impossible through traditional production methods.

Evaluating AI Avatar Generators for Professional Production

Lifelike Avatars Across All Output Types

When evaluating AI avatar generators for professional use, test lifelike avatar quality across all output types — not just static photo avatars. Studio quality videos, avatar videos for social media, and talking avatars for e-learning courses should all maintain equivalent visual standards. Platforms that produce excellent photo avatars but inconsistent video output reveal model limitations that surface only in real production conditions. Testing generate-an-ai-avatar workflows, avatar video quality, and talking avatar lip sync accuracy together provides a complete picture of production capability.

Avatar Customisation, Multiple Languages, and Professional Applications

Avatar customisation depth — control over facial features, age, body type, hairstyle, and avatar styles — determines whether a platform supports diverse campaign requirements or only a narrow template range. The best AI avatar generators combine custom avatar creation with video generation, voice cloning, and multiple language support. Multiple languages paired with voice cloning allow a single avatar identity to deliver content for a global audience — same face, same brand persona, localised message — without multilingual production teams. Professional applications across e-learning, retail, HR training, and social media marketing all benefit from this combination of avatar customisation depth and language flexibility.

The Future of AI Avatars and Digital Content

Human-Like Speech and Natural Facial Expressions

Human-like speech and natural facial expressions represent the remaining quality frontiers for AI avatar generators. Current platforms produce impressive results but retain subtle artificialities in vocal cadence and micro-expression rendering that trained observers can identify. Ongoing research in voice cloning and neural video synthesis is closing these gaps. Platforms investing in human-like speech and facial expression accuracy now will define the next generation of quality benchmarks for realistic AI avatars and lifelike videos across every content application.

AI Twin Technology and Endless Possibilities

AI twin technology — where generative AI creates a lifelike digital version of a specific individual, rather than a synthetic persona — represents the most advanced current application of avatar generation. AI twins deliver e-learning course content, respond to community questions at scale, and maintain consistent content cadence in multiple languages without the individual’s direct involvement. The endless possibilities of AI twin deployment, combined with continued advancement in generative AI capabilities, reinforce why the AI avatar generator market is positioned for sustained growth. As avatar generation quality continues to improve and costs continue to fall, the case for integrating AI avatars into content strategy grows stronger across every industry and audience segment.

Choosing the Right AI Avatar Generator: A Practical Checklist

Creators looking to create an ai avatar — whether building their own ai avatar from scratch or starting with a free avatar generator — should evaluate platforms against real production requirements. The ability to create custom avatars with consistently high quality avatar output, create realistic avatars with accurate hands and skin detail, and own an avatar persona that maintains identity across every output are the core criteria that separate professional platforms from basic tools. Owning your own avatar identity — a persistent, consistent digital persona — is increasingly a strategic asset for creators and brands building long-term audience relationships.

In evaluations comparing heygen ai avatars, Synthesia, and other AI avatar generators, artificial intelligence platforms that achieve character consistency while preserving a creator’s own voice and own ai avatar identity consistently outperform avatar generator ai tools that optimise for novelty over consistency. Practical factors also matter: maximum file size limits, output resolution, and credit allocation affect real production workflows. For agencies that need to create custom avatars for multiple clients or create an ai avatar at volume, these operational details determine which platform delivers sustainable value beyond the initial demo.

Conclusion

The AI avatar generator has become a core content infrastructure component for brands, agencies, and creators at every scale. With AI avatar creation market growth exceeding 34% CAGR, commercial adoption spanning social media to e-learning to customer service, and rapid technical improvement in character consistency and video quality, AI avatar generators represent a durable strategic investment. The fundamental value proposition — unlimited studio-quality content from a single avatar identity, at a fraction of traditional production cost — continues to strengthen as the technology matures and the market expands across new industries and use cases.

Enterprise LMS Trends: What’s Shaping the Future of Workplace Training

Workplace training looked very different five years ago. Employees sat through long classroom sessions. They clicked through endless compliance slides. They forgot most of it within weeks. That model is crumbling. The pace of business has accelerated dramatically. Skills expire faster than ever before. A static annual training program simply cannot keep up. 

Organizations need something more agile. They need learning that flows with the work, not against it. A major transformation is underway. The trends emerging today will define the next decade of workforce development.

Why Even an LMS for Manufacturing Companies Must Evolve

Manufacturing floors have changed completely. Sensors cover every machine. Data streams from every production line. Workers interact with complex digital interfaces. Training must reflect this new reality. Traditional approaches cannot handle the complexity. 

Even the most sophisticated LMS for manufacturing companies must adapt constantly. The trends shaping enterprise learning affect every industry. Manufacturing just feels the pressure most intensely. What works on a factory floor will work in any environment. The evolution happening now touches everyone.

AI Moves From Buzzword to Backbone

Artificial intelligence dominated headlines for years. Much of it was hype. That phase is ending. AI now delivers real, practical value in learning platforms. It personalizes content recommendations automatically. It adapts learning paths in real time. It predicts which employees might struggle before they fail. 

No human could perform these tasks at scale. AI makes them possible. The technology fades into the background. It just works. Learners barely notice its presence. They only notice that training feels more relevant and helpful.

Microlearning Becomes the Standard

Attention spans keep shrinking. Workdays keep fragmenting. Long courses no longer fit anyone’s schedule. Microlearning solves this problem elegantly. Short bursts of focused content take just minutes to consume. A three-minute video explains one concept clearly. A five-minute interactive scenario practices a single skill. 

Learners fit these pieces between meetings and tasks. Completion rates soar. Retention improves dramatically. The shift toward smaller units continues accelerating. Organizations now design for micro from the start. Long-form content becomes the exception.

Learning Flows Into Daily Work

Separate learning platforms create friction. Employees must remember to log in. They must navigate away from their actual work. This barrier kills engagement. The solution embeds learning directly into existing tools. A Slack notification suggests a relevant video. A Teams message shares a quick tip. A Salesforce sidebar offers coaching during a live call. 

Learning appears exactly when and where needed. It does not require a separate visit. This “learning in the flow of work” trend dominates forward-thinking organizations. The platform becomes invisible. The knowledge becomes immediate.

Social Learning Comes Front and Center

People have always learned from each other. Formal courses only tell part of the story. Most practical knowledge travels through conversations. Enterprise platforms now embrace this reality. They build robust social features intentionally. Users can ask questions and share discoveries. They can follow experts and form interest groups. 

Popular content rises based on peer activity. This social layer captures tacit knowledge. It makes learning collaborative instead of solitary. It builds community across distributed teams. The platform becomes a living network, not just a content library.

Skills Intelligence Drives Strategy

Tracking course completions offers limited insight. Organizations need deeper understanding. Skills intelligence platforms map competencies across the workforce. They identify gaps before they become problems. They connect learning activities to business outcomes. 

A leader can see exactly which skills exist where. They can plan development strategically. They can measure the impact of training investments. This data transforms learning from a cost center into a strategic driver. It guides hiring and promotion decisions. It reveals where the organization truly stands.

Content Curation Over Creation

Building everything from scratch takes forever. It also duplicates effort across the industry. The smartest organizations now focus on curation. They aggregate existing high-quality content from everywhere. YouTube videos explain technical concepts clearly. Industry blogs share emerging practices. Podcasts feature expert interviews. 

The learning platform becomes a gateway to this external knowledge. Internal teams add context and guidance. They do not reinvent every wheel. This approach scales dramatically. It keeps content fresh without endless production cycles. It exposes learners to diverse perspectives beyond company walls.

Personalization at Population Scale

One-size-fits-all training never really worked. It just felt unavoidable. Technology now enables true personalization for thousands of employees. Every learner sees a unique dashboard. Every learner follows a different path. The system adapts based on role and behavior. It respects individual pacing and preferences. 

This feels respectful and efficient. Learners engage more deeply with relevant content. They waste zero time on material they already know. Personalization drives completion and retention. It makes training feel like a service, not a mandate.

Data Privacy and Ethical AI Grow Critical

Powerful tools bring new responsibilities. Learning platforms collect vast amounts of personal data. They track behavior and performance. Organizations must handle this information carefully. Employees need transparency about what gets tracked. They need control over their own data. 

Ethical AI principles guide how systems make decisions. Algorithms should not reinforce existing biases. Privacy protections must be baked in from the start. This trend will only intensify. Trust becomes a competitive advantage. Organizations that respect learners will win their engagement.

The Takeaway

The future of workplace training looks nothing like the past. It feels personal and flows naturally. It builds community instead of isolation. It provides intelligence instead of just content. 

Organizations that embrace these trends will build more skilled, adaptable workforces. Those that cling to old methods will fall behind. The choice is clear. The time to evolve is now.

Uber scales on AWS to help power millions of daily trips and to train its AI models

Uber, the world’s largest ride-sharing and on-demand delivery company, is expanding its infrastructure and artificial intelligence (AI) capabilities on Amazon Web Services (AWS). Uber is using AWS Graviton instances to support more of its Trip Serving Zones, the real-time infrastructure behind every ride and delivery, and has started pilot training some AI models on Trainium—enabling faster rider and delivery matching, global demand handling, and smarter, more personalized experiences for millions of daily users.

Every time you open Uber and request a ride or delivery, a series of split-second decisions happens behind the scenes. Which driver is closest? What’s the fastest route? How long will it actually take? Getting those answers right instantly—for millions of people at once—requires the right infrastructure for Uber to deliver these capabilities at scale during rush hour and major events.

How Graviton helps power millions of trips in real time

Uber’s Trip Serving Zones are part of the system that makes sure every ride and delivery runs smoothly, which requires making millions of predictions and processing location data in milliseconds.

Now, Uber is expanding its use of AWS compute, storage, and networking to help power real-time operations for Trip Serving Zones. By running more of these workloads on AWS Graviton, Uber can reduce energy consumption while scaling rapidly during demand spikes, both reducing latency and optimizing costs. Graviton’s high performance enables some of the real-time calculations that help match riders with drivers faster—without compromising reliability, availability, or security.

“Uber operates at a scale where milliseconds matter,” said Kamran Zargahi, vice president of engineering at Uber. “Moving more Trip Serving workloads to AWS gives us the flexibility to match riders and drivers faster and handle delivery demand spikes without disruption.”

Improving Uber rides at scale with AWS Trainium chips

Uber has also begun experimenting with AWS Trainium to train some of the AI models that help power its apps. These models analyze data from billions of rides and deliveries to determine which driver or courier to send, calculate arrival times, and recommend the best delivery options to the customer. Training AI at this scale requires enormous computing power—Trainium provides an efficient, cost-effective way to do it. As the models learn from more trips, Uber delivers faster matches, more accurate arrival time estimates, and more personalized recommendations to customers worldwide so they can get where they are going faster and receive their deliveries sooner.

“By starting to pilot some of our AI models on Trainium, we’re building a technology foundation that will make every Uber experience smarter—so we can keep our focus where it belongs: on the people who use Uber every day,” Zargahi said.

“Uber is one of the most demanding real-time applications in the world, and we’re proud to be an important part of the infrastructure powering their global operations,” said Rich Geraffo, vice president and managing director of North America at AWS. “We’re helping Uber deliver the reliability hundreds of millions of people count on today—and the AI-powered experiences that will define ride-sharing and on-demand delivery tomorrow.”

Learn more about how AWS Graviton and Trainium are helping companies build faster, more efficient AI applications.

Qumulo Selects Ireland for European Software Research and Development Hub

Qumulo, the enterprise leader in unstructured data management and provider of cloud data platforms, announces the official launch of its European Software R&D hub in Cork. Through this strategic expansion, Qumulo will create 50 highly skilled R&D positions in the coming three years to solve the major challenges for data management at enormous scale and scope for global business.

This project is supported by the Irish Government through IDA Ireland.

Minister for Enterprise, Tourism & Employment, Peter Burke TD, said, “Qumulo’s decision to establish a new European software R&D hub in Cork is a strong endorsement of Cork as a location where cutting-edge engineering and global ambition meet. It highlights the depth of talent emerging from our universities, the strength of the region’s technology ecosystem, and Ireland’s ability to support companies delivering pioneering innovation on a global scale. I wish them the best of luck in their new office.”
Minister of State at the Department of Rural and Community Development and the Gaeltacht and at the Department of Transport, Jerry Buttimer TD said: “Today’s announcement by Qumulo is a testament to Cork and the South-West region’s capacity for fostering meaningful collaboration and technological leadership. This expansion highlights Ireland’s reputation as a dynamic environment where innovation thrives and partnerships flourish.”

 

Information, derived from data, is now the core asset driving the modern global economy. The success of autonomous AI systems integrated into business operations depends on their ability to make real-time decisions with instant, trustworthy access to colossal datasets.

“After actively reviewing a wide variety of options for our second R&D centre, we found that the stellar third-level institutions in the South-West were the basis for a deep talent pool in Cork,” said Qumulo Chief Technology Officer Kiran Bhageshpur. “Additionally, the excellent support infrastructure for companies like Qumulo provided by IDA Ireland made Cork the obvious choice for us to build a team focused on leveraging AI to help businesses manage global-scale data infrastructure.”

For Qumulo’s global customers, this new site in Cork will also see an expansion of its Customer Success team in the region as a commitment to the long-term partnership and the outcomes that customers expect. To explore career opportunities at Qumulo, visit www.qumulo.com/careers .

“Cork is a milestone, not just a milestone for Qumulo — but for every customer who depends on us to be present, responsive, and invested in their success,” said Qumulo VP of Customer Success Dave Coughlan, “This investment is a direct reflection of the trust our customers place in us, and our responsibility to honour that trust every single day.”

This new R&D and Customer Success hub in Cork is a recognition of the challenges and opportunities presented by this new global, digital landscape. This team will research and develop solutions to enable the secure, frictionless, and instantaneous transfer of exabyte-scale workloads across the globe, delivering the trusted, AI-ready data requirement to power next-generation enterprise applications.

“Qumulo’s establishment in Cork is a statement of the ambition of Qumulo to continue its growth to meet customer demand, and Cork’s capacity to deliver on that future with the talent base and ecosystem to drive innovation,” said Qumulo Engineering Director Diarmaid Hogan. “Building and growing a European Hub for R&D is the next chapter in Qumulo’s already exciting story.”

CEO of IDA Ireland Michael Lohan said, “Ireland offers a compelling combination of talent, research excellence, and an open, collaborative business environment, and Qumulo’s expansion in Cork is another example of how that proposition continues to resonate with global technology companies.”

Siemens expands data centre partner ecosystem to scale next-generation AI infrastructure

As AI drives unprecedented demand for data centre capacity, the industry faces a growing challenge in aligning rapidly expanding compute infrastructure with available power. To address this, Siemens Smart Infrastructure is expanding its data centre ecosystem through a strategic investment in, and partnership with, Emerald AI, alongside the integration of Fluence battery energy storage solutions, and the addition of collaborative physics-based AI modeling with PhysicsX. Together, these capabilities create flexibility across compute, energy, and infrastructure systems, helping data centre operators connect to the grid faster, scale efficiently, and operate reliably in a power-constrained world.

“Scaling AI infrastructure isn’t just a computing challenge, it is equally an energy and infrastructure challenge,” said Ruth Gratzke, President of Siemens Smart Infrastructure U.S. “As demand for AI processing accelerates, data centre growth is increasingly constrained by grid capacity and interconnection timelines. Addressing this requires complex coordination across both the digital and energy domains. Siemens is actively investing in key technologies

and partnerships to expand the ecosystem required to scale AI responsibly and support the next generation of data centre infrastructure.”

Emerald AI enables AI workloads to shift in time and location to align with grid conditions, allowing data centre demand to respond dynamically to available power. By coordinating when and where AI workloads run alongside dispatching onsite energy resources, this approach helps smooth peak demand, achieves faster and larger grid connections for data centres, and reduces pressure on constrained power infrastructure. The strategic investment in Emerald AI strengthens Siemens’ ability to introduce flexibility at the compute layer. When combined with Siemens’ expertise in power infrastructure and operational technology, this creates true IT/OT convergence between AI workloads and power systems.

A key element of this expanded ecosystem is the addition of Fluence’s grid-scale energy storage solutions, designed to support the next generation of high-performance AI data centres. As compute clusters grow in size and density, Fluence energy storage solutions enable data centres to accelerate grid connection by shaping load and coordinating ramp rates, making large AI-scale demand more predictable and easier for utilities to approve. This can turn power-constrained locations into viable data centre sites and accelerate time to power, which can enable deployment of energy storage in months rather than years of grid upgrades. Fluence’s energy storage solutions can also provide dispatchable, on-site power that aims to enable data centres to operate during grid build-outs, capacity shortfalls, or outages. By supporting consistent power quality and flexible scaling, Fluence can help data centre operators bring capacity online faster while maintaining the reliability required for mission-critical AI workloads.

Strengthening this ecosystem further, Siemens is collaborating with PhysicsX to apply physics AI to the design and operation of data centre power distribution systems. Using AI models trained on Siemens’ multi-physics simulation data, engineers can predict thermal behavior in complex busway systems in real time. With PhysicsX, simulations that once took days can run in under a second, enabling faster design iteration, optimized infrastructure for dynamic AI workloads, and the foundation for predictive monitoring across entire facilities.

The rapid growth of AI will continue to place new and often highly dynamic demands on power systems, with large training and inference clusters creating rapidly shifting loads that challenge traditional grid planning and data centre design. As a result, operators must find new ways to manage these demands while maintaining the performance and reliability required for AI infrastructure. Siemens’ expanded ecosystem is designed to help address this challenge by bringing together AI workload orchestration, grid-integrated energy systems, and AI-optimized physical infrastructure to support the next generation of AI infrastructure.

For more information on Siemens Smart Infrastructure, please see Siemens Smart Infrastructure.

AI is accelerating but is your infrastructure keeping pace?

AI is rapidly transforming businesses across Europe, the Middle East, and Africa (EMEA), unlocking innovation and potential in vital areas from retail personalisation to medical research. But Irish organisations in particular are feeling both the excitement and the strain. Many businesses find their AI ambitions stalling – as no one expected they’d need to support AI workloads when designing their infrastructure strategy. Colin Boyd, Data Centre Solutions Sales Director, Dell Technologies Ireland tells us more

The investment momentum is strong. Projections show the AI market in Europe alone is experiencing robust growth, projected to expand from approximately $105B in 2024 to over $640B by 2031, at a CAGR of 35% (Statista). But in Ireland the legacy systems remain one of the biggest barriers to progress with almost 28% of businesses saying their servers need upgrading to support AI workloads and 34% saying the same for their storage systems, according to Dell Technologies Innovation Catalyst Study. And as data volumes surge, 97% organisations that are planning to increase their storage capacity expect to face challenges of some sort when doing so, underscoring the scale of the infrastructure gap.

To truly unlock AI’s potential, leaders must first look inward and assess if their infrastructure is a launchpad for innovation or a barrier to progress. Here are five indicators that your infrastructure might be holding you back.

  1. Data Access is a Bottleneck, Not an Enabler

AI models are fueled by data. The more high-quality data they can process, the more accurate and insightful they become. However, many local businesses still struggle with fragmented or slow-moving data. If data scientists spend more time waiting for datasets to load than they do building models, that is a problem. Legacy storage systems often struggle to deliver the high-speed, parallel throughput required for training complex algorithms.

The challenge is further amplified by Ireland’s strict regulatory environment as seen 40% of the organisations say they face challenges when it comes to meeting regulatory data requirements when it comes increasing storage capacity and 37% cite data security and privacy concerns as barriers when planning to scale their storage infrastructure.

The need for strong data management in the EMEA region is further amplified by stringent regulatory requirements. Regulations like the General Data Protection Regulation (GDPR) in Europe set high standards for data privacy, consent, and localisation. Businesses need to ensure that data used for AI is not only accessible and timely but also managed and transferred in compliance with these legal mandates.

Consider a financial institution in London aiming to use AI for fraud detection. Real-time analysis is essential, but a fragmented or slow data landscape not only risks missed threats but can also lead to breaches of privacy mandates. Modern, compliant data platforms help unify, streamline, and accelerate access – enabling safe, rapid innovation, while meeting the complex requirements for privacy and governance.

  1. Scaling Server Infrastructure for the Next Wave of AI

Running AI in production is still a highly-compute intensive challenge for most businesses. While few enterprises are training large language models from scratch, many are deploying AI to support real-time decision making, analytics, computer vision, and increasingly autonomous workflows alongside existing business applications.

Almost 28% of Irish organisations say their servers need upgrading to support AI workloads, as it places sustained pressure on server infrastructure, particularly when general-purpose servers are already operating close to capacity. When AI inference, data processing and core applications compete for the same resources, performance suffers and the value of AI is harder to realise. Purpose built infrastructure, including accelerated compute, helps businesses support these mixed workloads efficiently while maintaining reliability and predictable performance.

  1. The Network Is a Traffic Jam

AI doesn’t just demand powerful computing and storage; it also requires a robust network to move massive datasets between storage, processing units, and end-users. But many businesses are discovering that their networks weren’t designed for this level of throughput. A slow or unreliable network can create significant bottlenecks, effectively starving your powerful AI processors of the data they need to function. Signs include long data transfer times, network congestion during peak processing hours, and dropped connections that can interrupt critical training jobs.

A slow network means a frustratingly delayed user experience, which can directly impact on customer satisfaction and retention. A growing number of Irish businesses recognise that improving data transfer speeds is essential to support AI tasks. A high-speed, low-latency network fabric is essential to ensure a smooth, continuous flow of data, enabling your AI applications to perform as intended.

  1. Deployment and Management Are Overly Complex

Getting an AI model from the lab to a live production environment should be a streamlined process. However, many businesses find themselves entangled in complexity. If your IT team struggles to provision resources, manage software dependencies, and scale applications, your infrastructure is creating unnecessary friction. A rigid, manually configured environment makes it difficult to experiment, iterate, and deploy AI models efficiently.

The challenge is compounded by skills gap and operational pressures. 34% of Irish organisations cite a lack of in-house expertise as a key barrier to managing growing data and infrastructure demands.

Lack of agility can be a significant disadvantage. Businesses across the EMEA region are looking to AI for a competitive edge, and speed to market is critical.

Modern infrastructure simplifies this journey with integrated software stacks and automation tools. This approach empowers teams to deploy AI applications quickly, manage them with ease, and scale them on demand, fostering a culture of rapid innovation.

  1. No Clear Path to Scale

While an organisation’s first AI project may start small, the infrastructure should be ready for what comes next. A critical sign of an unprepared system is the absence of a clear, cost-effective strategy for scaling your AI capabilities. If expanding the AI environment requires a complete and costly overhaul, the initial success will be difficult to replicate and these challenges are already being felt across businesses, with 40 % reporting difficulties when ensuring infrastructure scalability, while 37% cite high cost of expanding data storage as one of the key obstacles.

Infrastructure built on a scalable, modular architecture allows businesses to grow AI resources incrementally. This “pay-as-you-grow” model provides the flexibility to meet evolving demands without overinvesting, ensuring your AI journey is sustainable in the long term.

Building the Foundation for Progress

The journey to AI is not just about algorithms and data; it’s about building a powerful and agile foundation. By addressing these five signs, businesses in Ireland can move beyond the limitations of legacy systems. Investing in modern, purpose-built infrastructure is an investment in your future. It empowers your teams, simplifies complexity, and creates the conditions for AI to deliver on its promise of driving meaningful progress and creating new opportunities.

As organisations look to advance their AI ambitions, understanding how to modernise infrastructure becomes essential. The same principles that drive transformation – strengthening core systems, managing data securely and scaling AI workloads with confidence will be at the heart of the conversation at Dell Technologies Innovate. Bringing together industry experts and technology leaders, the event will explore how organisations can build resilient, AI‑ready environments while maintaining security, compliance, and performance.

For organisations looking to take the next step in their AI journey, understanding how to modernise infrastructure will be key.

Join us at Irish Museum of Modern Art on 26th March to dive deeper into these strategies and chart a clear path forward. For more information and to register, click here.

Dell Technologies Ireland reveals top technology predictions for 2026

Mark Hopkins, General Manager of Dell Technologies Ireland, has unveiled his top five technology predictions for 2026, outlining how Artificial Intelligence (AI), data and intelligent automation will fundamentally reshape how Irish businesses and public services operate.

The technology leader is forecasting a major acceleration in AI adoption, as organisations move from pilots and proof-of-concept projects to enterprise-wide deployment. In 2026, AI will become embedded into everyday operations, delivering measurable gains in productivity, efficiency and resilience across the Irish economy. Key predictions include the rise of physical and agentic AI, a step-change in public sector adoption, and a renewed focus on infrastructure and workforce upskilling.

“In 2026, AI will be treated not just as a tool but as a strategic asset capable of delivering measurable impact across operations, innovation and customer engagement,” said Mark Hopkins, General Manager of Dell Technologies Ireland. “Leaders who act now to integrate AI thoughtfully, modernise infrastructure and upskill their workforce will gain a decisive competitive edge.”

“From Bantry to Belfast, organisations are discovering that speed, data and intelligent automation are now the defining levers of competitiveness,” Hopkins added. “By anticipating the technology trends that will shape Ireland’s economy, Dell Technologies is helping organisations adopt AI responsibly and turn promise into real business advantage.”

  1. AI will take on a physical form – but not in the way many expect

In 2026, AI will step out of the digital shadows and take on tangible roles in the real world. Humanoid robots on every street are not expected; instead, purpose-built machines such as drones, mobile robots, and autonomous systems will be deployed to address specific challenges.

Examples include AI-powered crawlers that navigate power lines to identify issues and coordinate repairs to critical infrastructure. In healthcare, logistics robots will streamline hospital operations, freeing up staff for patient care. This new wave of “physical AI” will tackle repetitive, dangerous, and physically demanding work, delivering speed and safety at scale.

For Ireland, with its dispersed population and infrastructure needs, these innovations will help bridge geographic gaps and enhance resilience.

  1. Agentic AI will shift from helpful assistant to an integral manager

AI will move beyond chatbots and copilots to autonomous agents capable of managing complex, multi-step workflows. These systems will validate data, trigger approvals, coordinate with other agents and ensure compliance across business processes.

With nearly 90% of organisations identifying strong opportunities to create value from Agentic AI, according to the Dell Innovation Catalysts Study, Irish organisations – particularly in regulated sectors – will need secure, auditable infrastructure to manage the explosion of data and system interactions these agents create.

  1. Public sector will go all-in on AI, with healthcare leading the charge

After a period of cautious pilots, 2026 will see the Irish public sector move decisively to scale AI, with healthcare leading the way. AI-driven diagnostic support, automated clinical documentation and predictive resource planning will move from trial to production, helping to reduce waiting lists and improve patient outcomes.

As adoption increases, the focus will shift from theoretical debates about AI ethics to practical governance, with public-private partnerships playing a central role in delivering secure, sovereign AI solutions.

  1. Data deluge will redefine IT infrastructure

AI both consumes and generates vast volumes of data, much of it unstructured. As agentic AI becomes mainstream, hybrid IT architectures will become the norm. Critical data and high-value workloads will remain on-premises for control and security, while cloud platforms provide flexibility and scale.

Edge computing will push AI processing closer to where data is generated, reducing latency and keeping sensitive data local. Organisations that successfully align workloads to the right environment will gain a significant competitive advantage.

  1. Focus shifts from long-term STEM education to upskilling today’s workforce

While long-term STEM education remains critical, 2026 will be defined by immediate, practical upskilling. Almost 80% of Irish businesses expect their workforce to require digital upskilling in the coming years, with AI literacy becoming essential across every role.

The most effective programmes will combine sector expertise with hands-on AI tools, whether in healthcare, manufacturing or financial services. They will deliver immediate productivity gains when embedded into daily work and supported by strong governance.

Visa Helps Launch Klarna App in Ireland

Visa today announced it has enabled the launch of three brand new digital wallets across Europe, in partnership with BBVA, Klarna and Vipps MobilePay, and is collaborating with BANCOMAT on a pilot planned for early 2026.
These are the first Visa-enabled wallets to use NFC (Near Field Communication) technology to allow HCE (Host Card Emulation) on iOS wallets.
A major regulatory shift under the EU’s Digital Markets Act opened NFC access to third-party wallets, paving the way for greater competition and innovation in mobile payments. This allows more European players to bring new experiences to market and give consumers more choice.
According to Visa research*, mobile payments now represent more than half (59%) of all e-commerce transactions in Europe, and that figure is expected to rise to three quarters (75%) by 2030. With just under a third (32%) of Europeans saying they plan to rely exclusively on mobile wallets for purchases, there is a clear shift toward wallet-centric ecosystems, driven by demand for speed, simplicity, and control.
Visa has worked with three issuers and a domestic scheme across Europe to launch the new iOS wallets:
  • BBVA Pay, available through the BBVA Mobile Banking App, is a single issuer wallet launched in Spain. It is the first wallet in the world to use Visa’s own software developer toolkit (SDK) to directly integrate the Visa Token Service (VTS), a technology that protects sensitive card information by replacing it with a secure digital token. The wallet offers a new payment experience along with a secure, future-ready experience.
  • Klarna (the Klarna app), has launched its wallet in 14 European countries**, enhancing the app’s functionality and making the Klarna app a single, seamless experience for Klarna users on both iOS and Android.  Klarna, having launched the Klarna Card powered by Visa Flexible Credential, gives consumers further choice, and a truly integrated experience, with the addition of tap to pay as part of the Klarna app.
  • The Nordic mobile wallet company Vipps MobilePay has launched a Visa co-badged wallet in Norway, with Denmark, Finland and Sweden to follow. The wallet combines local familiarity with global reach as existing users can now tap and pay anywhere Visa is accepted, with their stored cards automatically enrolled for seamless contactless use—alongside the everyday features they already enjoy in Vipps MobilePay.
  • Italy’s domestic scheme BANCOMAT, has announced launched a pilot project with Visa to enable users of BANCOMAT wallet to make secure and contactless payments through the BANCOMAT Pay service, anywhere Visa is accepted. The pilot is based on VisaPay, Visa’s new wallet solution, which provides security and scalability by leveraging Visa’s advanced tokenisation capabilities. Testing of the solution is scheduled for early 2026.
“These launches reflect growing demand for mobile wallet-based payments and Visa’s commitment to supporting local and regional players with the scale, security and reliability of our global network,” said Mathieu Altwegg, Head of Product & Solutions, Visa Europe. “As a ‘hyper-scaler’, we’re enabling partners of all sizes to innovate faster and deliver more choice and convenience to consumers, while helping drive broader digital and economic growth across Europe.”
“This launch reflects BBVA’s strong commitment to innovation and to delivering an exceptional customer experience. It also positions BBVA as the first bank in Europe to offer a proprietary wallet powered by Apple technology — marking a milestone in the European banking industry,” said Luis Simoes, Head of Retail Experience and Value Proposition for Retail Banking at BBVA.
“Tap to Pay brings us closer to our vision of Klarna being everywhere for everything. Now you can set up a flexible payment plan and tap to pay in seconds, all inside the Klarna app. It makes the everyday shopping moments significantly smoother for our Klarna customers across Europe, giving them even more flexibility and choice at checkout.” said David Fock, Chief Product & Design Officer at Klarna.
“We’re pleased that our Vipps users can now tap seamlessly all over the world with Visa. It’s an important step toward our vision of making payments simpler and more unified for people wherever they go,” said Rune Garborg, CEO of Vipps MobilePay.
“The pilot project launched with Visa marks an important step in the evolution of BANCOMAT products, with the aim of offering Italian banks and users increasingly digital services that can also be used outside national borders,” says Fabrizio Burlando, CEO of BANCOMAT S.p.A.. “This collaboration will allow us to enhance the value of the BANCOMAT infrastructures, based in Italy, integrating them with Visa’s global network to enable new features and expand the user experience for customers. The model allows us to maintain a strong local presence, while benefiting from the international acceptance network and the capabilities of a global player. We are confident that this partnership will bring greater value to Italian banks and their customers.”
Looking Ahead: The Expanding Role of Digital Wallets
Digital wallets are quickly evolving: from simple payment tools to platforms that support peer-to-peer transfers, real-time bank payments and government IDs. With expanded NFC access, wallets could also store digital keys, loyalty cards, event tickets and more, opening the door to richer, more personalised services through a single, secure interface.
As Europe’s digital landscape evolves through advances in open banking, embedded finance and digital identity, financial institutions and fintechs have new opportunities to create more seamless, secure, and personalised experiences for their customers.
Visa’s infrastructure supports multiple payment types, including cards, account-to-account, and tokenised assets, giving partners the flexibility to build future-ready solutions that meet the needs of today’s consumers.

BUYER’S GUIDE: Should I buy a Portable or Whole-House Dehumidifier?

Between damp winters and humid summer months, keeping indoor humidity at the right level isn’t just a matter of comfort, but one of protecting both your home and health. Too much moisture creates the perfect conditions for mould and mildew to flourish, which can trigger allergies, aggravate asthma and damage fabrics, woodwork, and paint over time. That’s definitely something you’ll want to avoid.

According to building surveyors, the ideal indoor humidity sits between 40% and 60%. Anything over that and you’ll start to see moisture buildup on windows, walls, and hidden voids, creating problems you might not spot until it’s too late. Some “healthy home” strategies like insulation, ventilation, and air purification can help, but you might consider other options as well…like a dehumidifier.

If you’re thinking about tackling humidity, most households have essentially two routes to choose from; a portable room dehumidifier or a whole-house system. To be clear, both are designed to keep moisture levels in check, but they do it very differently, and making the right choice for you and your home will depend on a few aspects – including your space, budget, and overall lifestyle.

Penned with the aid of experts, this article offers a guide of things to consider before deciding which solution to implement into your home.

Cost and Upfront Investment

Since nobody likes to talk about money, let’s get the ugly(ish) details out of the way. For most people, portable dehumidifiers offer an easy and affordable entry point, and they tend to be the most common starting point.

With prices for a quality option generally starting at around £200, portable units don’t need professional installation, meaning you can have one up and running straight out of the box within minutes. This makes them ideal for rented accommodation, or for anyone looking for a quick fix in a specific problem spot.

Whole-house systems, on the other hand, are a larger commitment. Units typically cost between £800 and £2,500, and you’ll need to budget extra for installation costs. That said, if you’ve got a large property, or you know you’re in it for the long haul, this initial investment can pay off in both comfort and peace of mind.

Flexibility, Placement, Coverage and Scale

The main perk of a portable unit is that – as the name suggests – it’s portable. This means you can take and place it wherever you might need it – from a damp basement to a steamy bathroom, or even in your bedroom. Naturally, whole-house systems are a different story, and are built into your HVAC system, regulating humidity evenly across the entire property. The plus point here is the consistency, but it does mean giving up the flexibility to move it around to specific problem points.

The real gap between the two solutions starts to show when talking about coverage. A portable dehumidifier will handle a single room with no problems, typically up to around 700 square feet. Whole-house systems – as the name suggests – are designed to manage thousands of square feet at once, making them the natural choice for larger homes or multi-storey properties. If you want every room to feel equally comfortable, it’s hard to beat full-home coverage – but it’s worth considering whether you really need that much.

Energy and Efficiency

We’re all trying to save on energy bills at the moment. Thankfully, running a single portable unit is fairly efficient, but once you get into the territory of having several units dotted around the house, the costs can creep up. Whole-house systems may seem like heavy hitters in both scale and upfront cost, but they’re often more economical per square foot. By keeping humidity in check, they can even lighten the load on your heating and cooling systems, which could mean savings in other areas down the line.

Maintenance and Upkeep

Despite their overall convenience, portable models do need a bit of hands-on attention, from emptying water tanks to cleaning filters and simply making sure they’re positioned correctly. Some do allow for continuous drainage, which helps, but whole-house systems are far simpler to maintain once they’re in: connected directly to drainage, they usually only need a filter change and a yearly check-up.

Noise and Everyday Comfort

Portable dehumidifiers aren’t completely silent (yet), so if you opt for one of these, you’ll need to be comfortable with a little added white noise in the chosen space. Most aren’t too invasive (at least, not as invasive as your neighbours drilling on a Sunday morning), but it’s a factor to consider if you’re sensitive to background noises. Whole-house systems are installed out of sight — usually in a loft, basement, or utility space – so you’ll barely even notice them. In some ways, that’s a plus…though you also might not notice if there are problems that you might have clocked if you’d been able to hear the unit struggling.

So, Which Should You Choose?

The simplest way to frame your decision goes like this; If you’re renting, on a budget, or only need to dehumidify one or two problem areas, go for a portable solution. If you own a larger property, want a “fit and forget” solution, or see it as part of a long-term investment in your home’s comfort and value, you’ll want a whole-house solution.

Whatever you opt for, managing indoor humidity is one of the smartest (and simplest) things you can do to protect your home and your health. Of course, make sure you shop around to find the best solutions and keep your budget in mind when purchasing.