As artificial intelligence redraws the boundaries of work and learning, Udemy is making a pointed statement: instructors still matter—and the platform is building its next phase around them.

At its semiannual Front Row event, Udemy unveiled a slate of new instructor-focused offerings aimed at helping educators adapt, earn more, and stay central in a rapidly evolving, AI-shaped skills economy. The announcements come at a moment when global demand for upskilling is surging, the shelf life of technical skills continues to shrink, and nearly 60% of professionals worldwide require reskilling, according to the World Economic Forum.

Rather than positioning AI as a replacement for human-led learning, Udemy is framing instructors as “AI orchestrators”—guides who shape, validate, and elevate learning experiences as automation takes on more of the heavy lifting.

Why Udemy Is Rethinking the Instructor Model

Udemy’s timing reflects broader shifts in how people want to learn. Learners increasingly expect continuous, bite-sized, and community-driven experiences, often accessed on mobile or embedded directly into daily work. Long-form courses still matter, but they’re no longer enough on their own.

At the same time, instructors are experimenting across formats—live sessions, short-form lessons, communities—sometimes outside Udemy, when the platform doesn’t support those modalities. Udemy sees this fragmentation as both a risk and an opportunity.

“As AI reshapes the landscape of work and accelerates learning, instructors remain the catalyst for real skill-building,” said Hugo Sarrazin, Udemy’s President and CEO. The company’s new offerings are designed to help instructors grow alongside Udemy, not around it.

The strategy is clear: expand beyond one-off course sales toward recurring engagement, diversified revenue, and learning experiences that fit modern attention spans.

Instructor Subscriptions: Recurring Revenue Comes to Udemy

One of the most significant announcements is Instructor Subscriptions, a model that brings live sessions, short-form content, and community features directly onto Udemy. Expected to roll out through 2026, subscriptions aim to give instructors tools they’ve increasingly sought elsewhere.

Instead of relying solely on individual course purchases, instructors will be able to build recurring revenue streams, publish frequent and flexible content, and foster ongoing learner communities. Udemy plans to unify these activities under a single analytics and engagement layer, giving instructors clearer visibility into what resonates.

The move mirrors a wider trend across creator platforms, where subscriptions are becoming the backbone of sustainable income. For Udemy, it also helps shift the platform from a transactional marketplace to a longer-term learning relationship.

AI-Powered Micro-Learning, With Instructors in Control

Udemy also previewed AI-powered micro-learning tools that transform long-form courses into interactive, short-form learning experiences. The goal is to meet learners “in the flow of work”—on mobile devices, between meetings, or during short study windows.

What’s notable is Udemy’s emphasis on instructor oversight. Rather than auto-generating content with minimal human input, the company positions instructors as curators and validators, responsible for accuracy, quality, and instructional integrity.

These tools are designed to help instructors:

• Reach new learner segments and expand total addressable market

• Support mobile-first, just-in-time learning

• Increase engagement and retention through shorter formats

• Maintain authority over AI-generated activities

This approach reflects a growing industry realization: AI can scale content creation, but trust and credibility still depend on human expertise—especially in professional and technical learning.

A $2.5M Bet on Experimentation

To encourage instructors to embrace new formats, Udemy announced plans for a $2.5 million Content Innovation Fund. The fund is intended to support experimentation with subscription models, short-form content, and AI-driven micro-learning.

Support is expected to include grants, funding for new learning formats, resources for adopting AI tools, and acceleration for next-generation experiences. In effect, Udemy is subsidizing the transition costs for instructors navigating an uncertain but inevitable shift.

This move also benefits Udemy itself. By funding experimentation, the company gains early insight into what works—and what doesn’t—before scaling those formats platform-wide.

Competing in an AI-First Learning Market

Udemy’s announcements come as competition intensifies across corporate learning, creator education, and AI-powered training platforms. Rivals are racing to embed AI tutors, adaptive learning paths, and personalized content into their offerings.

Udemy’s differentiator is its insistence that AI should augment, not replace, instructors. By expanding formats, monetization options, and analytics, the company is betting that instructor success will drive platform resilience.

The shift toward subscriptions and micro-learning also strengthens Udemy’s broader ecosystem, particularly its enterprise and subscription businesses, where ongoing engagement matters more than one-time course purchases.

What It Means for Instructors and Learners

For instructors, Udemy’s roadmap signals a future with more control, more revenue options, and deeper relationships with learners. For learners, it promises more flexible, modular, and continuous learning experiences aligned with how skills are actually used on the job.

At a time when AI is compressing learning cycles and reshaping job roles faster than ever, Udemy is positioning itself as a platform where human expertise still anchors the experience—even as machines help scale it.

If successful, this strategy could help Udemy evolve from a course marketplace into a more durable learning ecosystem, one where instructors lead, AI accelerates, and skills keep pace with change.

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Avnet and AMD aren’t just talking about Australia’s AI future—they just drove it more than 4,000 kilometers across the country.

The partners have wrapped up the inaugural “AMD on Wheels” national roadshow, a multi-city tour spanning Sydney, Canberra, Melbourne, and Adelaide, designed to bring advanced AI and high-performance computing (HPC) solutions directly to Australia’s innovation hubs. The message was clear: the next phase of AI growth won’t be built on isolated components or lab demos, but on deployable, energy-efficient systems that can scale responsibly into real-world use.

Fittingly, the roadshow itself reflected that philosophy. The entire journey was completed using pure electric vehicles—the ZEEKR 7X and ZEEKR 009— underscoring a parallel commitment to sustainability and energy-efficient computing.

From Components to Complete AI Systems

Rather than spotlighting individual chips or boards, Avnet and AMD focused the tour on end-to-end AI and HPC solutions—secure, adaptable infrastructure that can move from pilot projects to production environments. This shift mirrors a broader trend across the enterprise and public sectors: AI success increasingly depends on integration, supply chain reliability, and operational readiness, not just raw performance.

That context matters for Australia. Analysts estimate that AI could add as much as AU$142 billion annually to Australia’s GDP by 2030 in an ambitious scenario, according to the Australia’s AI Opportunity report (2025). Capturing that value, however, requires infrastructure that balances performance with power efficiency, governance, and long-term sustainability.

Avnet and AMD positioned themselves as enablers of exactly that foundation.

“Avnet and AMD are strategically invested in advancing Australia’s capability in Responsible AI and next-generation computing,” said Tan Aik Hoon, Regional President for South Asia, Korea and Avnet United. “Beyond distribution, Avnet helps innovators transform advanced AMD hardware into scalable, sustainable solutions that strengthen Australia’s competitive edge.”

Responsibility and Efficiency as Competitive Advantages

A recurring theme throughout the roadshow was that responsible AI is no longer optional. Energy consumption, secure supply chains, and system resilience are now core considerations for governments, enterprises, and research institutions alike.

AMD reinforced this point by emphasizing its focus on energy-efficient computing, particularly in embedded and adaptive platforms that can deliver AI performance without excessive power draw.

“The next wave of AI innovation in Australia must be built on a foundation of Responsibility and Efficiency,” said Steven Fong, Corporate Vice President, Asia Pacific & Japan Embedded Sales at AMD. “We are committed to delivering the energy-efficient computing power that fuels this responsible acceleration.”

That positioning resonates as organizations weigh the environmental and operational costs of AI at scale—especially in sectors like defense, space, and advanced manufacturing.

Scaling AI Requires Collaboration, Not Silos

One of the roadshow’s central discussions, the “Industry Collaboration for AI at Scale” panel, tackled a challenge that plagues many innovation ecosystems: moving from promising pilots to full-scale deployment.

The consensus was blunt. Australia’s next innovation leap depends on cross-sector collaboration—linking academia, startups, enterprise, and global technology partners. Without that connective tissue, breakthroughs risk stalling before they reach market.

The roadshow backed up that argument with concrete examples from Australian companies already making the leap.

Advanced Navigation: Space-Grade Precision, Made Local

Advanced Navigation showcased how local innovation can reach global, space-ready standards. Through the “Avnet to the Moon” initiative, the company developed its Laser Measurement Unit for Navigational Aid (LUNA)—a precision system designed to operate in space and extreme environments.

With technology and supply chain support from Avnet and AMD, LUNA demonstrates how Australian companies can deliver mission-critical reliability while strengthening the country’s role in the global space supply chain.

Quantum Brilliance: Turning Quantum from Research to Revenue

For Quantum Brilliance, the challenge wasn’t theoretical physics—it was scaling hardware amid global supply constraints. By transitioning to the AVNET+ AMD–based ADRS1000 system-on-module, the company moved from prototypes toward commercial deployment.

Avnet’s ability to secure timely delivery despite shortages proved decisive, highlighting an often-overlooked reality of frontier technologies: innovation doesn’t scale without dependable supply chains. In quantum computing, that reliability can mean the difference between market leadership and missed opportunity.

Liquid Instruments: Agentic AI Comes to Test and Measurement

Liquid Instruments offered a glimpse into how AI is reshaping engineering workflows. Its Moku platform, powered by AMD FPGAs, is introducing Generative Instrumentation and agentic AI—tools that allow engineers to create and configure test instruments using natural language.

Set to launch with Moku:Delta in 2026, the approach promises faster experimentation and smarter workflows across research and manufacturing. With backing from Avnet and AMD, Liquid Instruments is showing how AI can compress development cycles without sacrificing precision.

Silentium Defence: Passive Radar at Production Scale

In the defense domain, Silentium Defence demonstrated how long-term collaboration accelerates complex technologies. Its SWaP-optimized passive radar systems, built on AMD technology, have progressed from early prototypes to production-ready platforms.

Avnet’s global supply chain and engineering support played a key role, enabling Silentium Defence to deliver advanced sensing capabilities for defense, space surveillance, and critical infrastructure customers worldwide.

A Blueprint, Not a One-Off Tour

Avnet and AMD are positioning “AMD on Wheels” as more than a marketing exercise. Instead, they describe it as a blueprint for Australia’s AI future—one that connects world-class research with commercial deployment through reliable infrastructure and partnerships.

By aligning advanced processors, secure supply chains, and ecosystem collaboration, the partners aim to help Australia build resilience in a global AI landscape that’s becoming increasingly competitive—and geopolitically complex.

If the roadshow proved anything, it’s that Australia’s AI opportunity won’t be unlocked by isolated breakthroughs. It will be driven by systems that work, scale, and endure—and by partnerships that know how to turn ambition into deployment.

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Cloud gaming’s long-promised mainstream moment may finally be edging closer—and Comcast and Amazon want the living room to be its proving ground.

The two companies announced today that Amazon Luna, Amazon’s cloud gaming service, is now available on millions of Xfinity TV and streaming devices across the U.S. Starting immediately, Xfinity customers with eligible X1 or Xfinity Xumo Stream Box devices can access Luna’s growing library of games directly from their TV interface, without a console, downloads, or lengthy setup.

The launch places Luna alongside live TV, on-demand programming, and streaming apps, reinforcing a broader industry push to blur the lines between gaming and traditional entertainment.

Gaming, Without the Console Commitment

For Xfinity customers, the pitch is simplicity. Users can say “Luna” into their voice remote, sign in with an Amazon Prime or Luna Premium subscription, and start playing. Games can be controlled with Amazon’s Luna controller or a compatible Bluetooth controller, keeping the barrier to entry low.

The content lineup spans high-profile titles such as Hogwarts Legacy and Indiana Jones and the Great Circle, alongside more casual, family-friendly options. Prime members also get access to a rotating selection of more than 50 games at no additional cost, including party-style GameNight experiences like The Jackbox Party Pack 9.

Some of those games are optimized for shared, in-person play and don’t require a controller at all. Players can simply scan a QR code on the TV and use their smartphones to join—a nod to how gaming increasingly overlaps with social and second-screen experiences.

A Strategic Win for Both Sides

For Amazon, the Xfinity deal significantly expands Luna’s reach. While cloud gaming services have struggled to break through as standalone platforms, embedding Luna directly into a widely used TV ecosystem gives Amazon access to millions of households that may never buy a console—or even consider themselves gamers.

“At Amazon, we’re focused on making gaming more accessible,” said Jeff Gattis, General Manager of Amazon Luna, pointing to Comcast’s scale as a key driver of the partnership. The move fits Amazon’s broader strategy of distributing services wherever customers already are, rather than forcing them into new hardware ecosystems.

For Comcast, Luna strengthens Xfinity’s positioning as more than just a cable or broadband provider. Gaming has become a critical battleground for ISPs, both as a driver of network usage and as a way to differentiate premium connectivity.

“Xfinity is redefining what it means to game on the big screen,” said Fraser Stirling, Global Chief Product Officer at Comcast. The subtext is clear: cloud gaming showcases the value of fast, low-latency broadband in ways streaming video alone cannot.

Entertainment OS: The Glue Behind the Experience

Under the hood, Luna’s integration is powered by Comcast’s Entertainment OS, the platform that unifies live TV, streaming apps, and now cloud gaming into a single interface. The OS supports features like voice search, personalization, and seamless content discovery across tens of millions of devices worldwide.

Entertainment OS already powers Xfinity and Xumo devices in the U.S., Sky platforms across the UK and Europe, and partner deployments with companies like Rogers and Foxtel. Notably, Rogers is also launching Amazon Luna on its Entertainment OS–powered Xfinity streaming devices today, signaling that this rollout is part of a broader global strategy.

Comcast says Luna will expand to additional Entertainment OS–powered devices over time, suggesting cloud gaming could become a standard feature of its entertainment stack rather than a niche add-on.

Why Cloud Gaming Needs the Network Advantage

Cloud gaming has always been constrained by physics. Streaming a game in real time requires far lower latency and greater consistency than video-on-demand, where buffering can mask network hiccups. Comcast is leaning hard into this reality, positioning its network as a competitive advantage for gamers.

The company says its Xfinity network delivers multi-gig speeds and ultra-low latency, engineered specifically to support demanding use cases like cloud gaming. Comcast also points to proprietary innovations designed to reduce lag and improve responsiveness—technologies it claims were industry firsts.

The emphasis isn’t just marketing. Gaming-related traffic on Comcast’s network grew 30% over the past year, and the company expects it to double roughly every three years. That growth mirrors a broader shift: streamed entertainment now accounts for more than 70% of total network traffic, with gaming joining video and music as a major contributor.

The Bigger Trend: Gaming as a Streaming Service

The Luna-Xfinity launch reflects a larger industry transition. Gaming is increasingly adopting the same distribution model as film and TV—subscription-based, device-agnostic, and always connected. Microsoft’s Xbox Cloud Gaming, NVIDIA GeForce NOW, and Sony’s evolving streaming strategy all point in the same direction.

What differentiates this move is context. By placing Luna directly inside a TV platform used daily for mainstream entertainment, Comcast and Amazon are testing whether cloud gaming can reach a broader, more casual audience—one that values convenience over performance specs.

It’s also a reminder that cloud gaming’s success may hinge less on killer exclusives and more on distribution, network quality, and frictionless access.

What It Means for the Living Room

For consumers, the immediate benefit is choice. Console-quality games are now just another app on the TV, accessible with a voice command. For Comcast, it’s a way to reinforce the value of premium broadband. For Amazon, it’s a chance to scale Luna without fighting the uphill battle of hardware adoption.

Whether this partnership moves cloud gaming from promise to permanence remains to be seen. But by embedding Luna into one of the country’s largest entertainment platforms, Comcast and Amazon are making a compelling case that the future of gaming may look a lot like streaming—just far more interactive.

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As customer experience becomes the primary battleground for competitive differentiation, Perficient is quietly—but decisively—moving up the ranks.

The global consultancy has been named a Major Player in three 2025 IDC MarketScape reports, covering Experience Design Services, Experience Build Services, and Customer Experience Strategy Consulting. The triple recognition underscores Perficient’s growing influence in a services market increasingly shaped by AI, personalization, and the need to scale digital experiences without losing human relevance.

For enterprises struggling to balance automation with authenticity, IDC’s assessment positions Perficient as a firm built for the next phase of customer experience transformation.

Why This Recognition Matters Now

Customer expectations are climbing faster than most organizations can adapt. AI-driven personalization is no longer a differentiator—it’s table stakes. What separates leaders from laggards is execution: how well companies translate strategy into real, scalable experiences across channels.

That’s the gap Perficient is aiming to fill. Its inclusion as a Major Player across design, build, and strategy signals breadth, not just depth. Few consultancies are recognized across the full CX lifecycle, from shaping experience vision to actually engineering and deploying it at scale.

IDC’s MarketScape reports evaluate vendors on capabilities, strategy, and future readiness. Being named a Major Player in all three suggests Perficient isn’t just reacting to market trends—it’s aligned with where enterprise CX is headed next.

AI-First, Not AI-Only

Perficient describes its approach as AI-first, not AI-exclusive. That distinction matters. Rather than positioning AI as a bolt-on toolset, the firm integrates it into experience design, personalization frameworks, and delivery models from the start.

“Our clients value Perficient’s AI-first approach because it transforms customer experiences and delivers measurable business results,” said Erin Rushman, general manager of digital marketing and experience design operations at Perficient. The emphasis on measurable outcomes reflects a shift in CX buying behavior, where executive stakeholders increasingly demand ROI, not just better-looking interfaces.

IDC’s evaluation appears to validate that positioning. In the Experience Design (XD) MarketScape, Perficient was cited for strong digital offering design, supported by a global innovation network—a critical factor as enterprises look for consistency across regions without sacrificing local relevance.

From Design Vision to Build Reality

One of the persistent challenges in digital transformation is the handoff between design and implementation. Strategy decks and prototypes often lose momentum when they hit engineering constraints or organizational silos.

Perficient’s recognition in the Experience Build (XB) MarketScape suggests it’s addressing that gap head-on. IDC notes that the firm combines business and technology transformation with a robust set of supporting assets and tools, with a particular strength in personalization.

That’s significant as personalization shifts from rules-based logic to AI-driven orchestration. Building those systems requires not only creative design, but also data engineering, platform integration, and governance—areas where many experience agencies fall short.

IDC analyst Douglas Hayward summed it up succinctly, describing Perficient as a strong option for organizations seeking a global services provider that can pair client intimacy with industrial-strength digital transformation capabilities. That balance is increasingly rare as consultancies either scale up and lose flexibility, or stay boutique and struggle with enterprise complexity.

CX Strategy in an Experience-Driven Economy

Beyond execution, Perficient was also named a Major Player in the IDC MarketScape for Worldwide Customer Experience Strategy Consulting Services. This category evaluates firms on their ability to define CX vision, align it with business goals, and adapt strategies as technologies and customer behaviors evolve.

The recognition highlights Perficient’s role as a long-term partner rather than a project-based vendor. As CX strategies become living systems—continuously optimized through data and AI—organizations are favoring consultancies that can evolve alongside them.

IDC’s assessment suggests Perficient’s approach resonates with that need, emphasizing scalability, flexibility, and transformation over one-off engagements.

A Broader Industry Signal

Perficient’s triple recognition also reflects a broader shift in the technology services market. Traditional separations between consulting, design, and implementation are breaking down. Enterprises want fewer partners who can do more—and do it cohesively.

At the same time, AI is compressing timelines and raising expectations. Experience design cycles are shrinking, personalization is becoming real time, and CX strategies must adapt continuously. Service providers that can’t integrate AI meaningfully risk being sidelined.

By earning Major Player status across multiple IDC MarketScapes, Perficient is positioning itself as one of the firms built for that convergence.

The Bottom Line

IDC’s 2025 MarketScape reports don’t crown Perficient as the undisputed market leader—but that’s not the point. Being named a Major Player across experience design, build, and CX strategy signals consistency, maturity, and forward momentum.

For enterprises navigating AI-driven CX transformation, that combination may matter more than flashy claims or narrow specializations. As customer experience continues to define brand loyalty and revenue growth, consultancies that can bridge strategy, technology, and execution will shape the next generation of digital leaders.

Perficient is clearly aiming to be one of them.

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At most tech conferences, AI is still discussed as a future promise. At TCL’s Global Technology Innovation Conference 2025 (TIC 2025) in Guangzhou, the message was different: AI is already operational, measurable, and profitable.

Under the banner “AI for Real,” TCL used its 12th annual TIC event to show how artificial intelligence has moved from pilot projects into the core of its business—powering factories, redefining display manufacturing, and reshaping everyday consumer electronics. The subtext was clear: while much of the industry debates AI strategy, TCL is focused on execution.

Founder and Chairman Li Dongsheng framed the moment bluntly. AI, he said, only matters when it produces tangible value. TCL expects its AI applications to generate more than $140 million in economic benefits in 2025, a figure that puts real weight behind the company’s claims.

This wasn’t an abstract vision. Across manufacturing, displays, home appliances, AR devices, and robotics, TCL laid out a blueprint for how large-scale hardware companies can embed AI deeply—without turning it into marketing theater.

From AI Talk to AI Economics

The theme “AI for Real” reflects a broader shift happening across global manufacturing and consumer tech. As enterprises consolidate data, automate workflows, and race toward AI readiness, the winners are increasingly those that can connect algorithms to physical outcomes.

TCL COO Kevin Wang captured this sentiment during the conference, noting that AI’s real value lies not in “stacking up concepts,” but in delivering measurable results across production, products, and services.

That positioning matters. Many global electronics brands are still experimenting with AI in isolated features—voice assistants here, image processing there. TCL’s approach is more systemic: AI is treated as infrastructure, not an add-on.

Intelligent Manufacturing as a Competitive Weapon

The most compelling evidence of TCL’s AI maturity came from its manufacturing arm, particularly TCL CSOT, the company’s advanced display subsidiary.

At TIC 2025, TCL CSOT unveiled X-Intelligence 3.0, a domain-specific large language model designed explicitly for the display industry. Unlike general-purpose AI models, X-Intelligence 3.0 is trained to reason across highly specialized manufacturing and materials workflows—spanning R&D, production, quality control, and supply chain operations.

The results are already visible:

• 20% improvement in product issue analysis efficiency

• 30% increase in materials development efficiency

For an industry where yield improvements of even a few percentage points can translate into millions of dollars, those numbers are significant.

According to Dr. Yan Xiaolin, CTO of TCL Technology and TCL CSOT, AI-driven automation now spans the entire defect lifecycle—from Auto Defect Classification (ADC) to Auto Defect Repair (ADR). That end-to-end system is already generating more than $7 million in annual revenue, underscoring how AI is becoming a profit center, not just a cost reducer.

Inkjet OLED: From Lab Curiosity to Industrial Scale

Perhaps the most strategically important announcement was TCL CSOT’s progress in Inkjet-Printed OLED (IJP OLED) technology.

Long viewed as promising but difficult to scale, IJP OLED has now crossed a critical threshold. TCL CSOT has moved the technology from lab research to mass production, backed by a $4 billion investment in the world’s first 8.6-generation IJP OLED production line.

This matters for the broader display market. Compared with traditional OLED manufacturing, inkjet printing offers better material efficiency, lower waste, and greater flexibility across screen sizes—advantages that align closely with both cost control and sustainability goals.

TCL CSOT showcased multiple first-of-their-kind products built on this platform, including:

• A 5.65-inch Real Stripe RGB OLED MB Display designed for high-clarity smartphones

• A 28-inch foldable and portable display that expands from laptop size to ultra-wide format

Together, these products signal that IJP OLED is no longer experimental. TCL is positioning it as a mainstream alternative capable of reshaping the economics of premium displays.

APEX: Designing Displays for Humans, Not Just Specs

TCL CSOT framed its display strategy around its APEX philosophy:

• Amazing Display Experience

• Protective of Eye Health

• Eco-friendly to Build and Use

• Unlimited Imaginative Potential

This human-centric framing reflects a broader industry trend. As display performance plateaus in raw resolution and brightness, differentiation increasingly comes from usability, sustainability, and form factor innovation.

By combining AI-driven manufacturing with APEX design principles, TCL is trying to future-proof its display business against commoditization—a challenge that has plagued panel makers for decades.

AI Moves Into the Home—Quietly and Practically

While manufacturing innovations grabbed the headlines, TCL also demonstrated how AI is being woven into everyday consumer products—often in ways users may not even notice.

In home climate control, the TCL FreshIN AI Healthy Fresh Air Series uses AI to optimize airflow and purification based on real-time conditions. The system cuts nighttime energy use by up to 40% while extending deep sleep by 25%, according to TCL.

In the kitchen, AI-powered refrigerators maintain food freshness with ±0.5°C precision cooling, while AI Super Drum washing machines use sensors and TCL’s Fuxi LLM to identify fabric types, load weight, and soil levels—automatically generating custom wash cycles.

Televisions, still TCL’s most visible consumer category, now rely on AI models that interpret complex voice commands and dynamically optimize picture and sound on a frame-by-frame basis. The goal is less about flashy features and more about invisible optimization—making premium performance feel effortless.

AR Glasses and the Push Toward Ambient AI

TCL’s ambitions extend beyond the living room. Through its RayNeo brand, the company is betting on AR glasses as a next-generation AI interface.

The RayNeo X3 Pro is positioned as one of the world’s first AR glasses to support visualized, live AI interaction. Users can ask questions, receive contextual answers, translate languages in real time, and parse visual information on the fly.

This aligns with a broader industry shift toward ambient AI—systems that understand context and respond naturally without forcing users into screens or menus. While competitors like Meta and Apple are pursuing similar goals, TCL’s focus on practical translation and real-world utility suggests a more grounded approach.

AI Companions, Not Just Smart Devices

One of the more unconventional reveals was TCL AiMe, described as the world’s first modular AI companion robot.

Rather than positioning AiMe as a functional appliance, TCL framed it as a family partner capable of emotional recognition and multimodal interaction. Whether consumers are ready for AI companionship at scale remains an open question, but the move signals TCL’s willingness to explore the emotional dimension of AI—an area gaining traction across robotics and consumer AI research.

R&D Scale as a Strategic Moat

None of this experimentation happens without scale. Over the past six years, TCL has invested more than $8.4 billion in R&D, supported by a global network of over 20,000 researchers. The company has filed more than 110,000 patents, spanning IJP OLED, EL-QD, and AI-driven manufacturing systems.

Programs like the $2.8 billion Rising Sun Project further reinforce TCL’s ecosystem strategy, combining academic collaboration, industrial partnerships, and long-term platform investment.

This level of sustained R&D spending places TCL in rare company among global hardware firms—especially as many competitors pull back amid economic uncertainty.

AI Meets Sustainability

A recurring theme throughout TIC 2025 was sustainability. TCL emphasized that its AI strategy is tightly coupled with environmental goals, from renewable materials to energy-efficient manufacturing.

Through its TCLGreen initiative, the company is embedding green principles across product design, supply chains, and factory operations. The argument is pragmatic: AI-driven efficiency is not just good for margins—it’s increasingly essential for meeting global regulatory and climate expectations.

The Bigger Picture

TCL’s “AI for Real” message lands at a critical moment for the tech industry. As AI hype collides with economic reality, companies are being forced to prove ROI, not just ambition.

By tying AI directly to manufacturing yield, product differentiation, energy efficiency, and revenue generation, TCL is making a case that large, hardware-centric companies can still lead in the AI era—provided they focus on integration over spectacle.

The takeaway from TIC 2025 is simple: AI doesn’t need to be louder. It needs to work.

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As AI-driven search engines increasingly bypass traditional blue links in favor of instant, synthesized answers, a quiet shift is underway in how brands are discovered—or ignored. NEWMEDIA.COM, a U.S.-based digital marketing agency with more than 25 years in performance marketing, believes most companies are unprepared for that shift. This week, the firm publicly unveiled RankOS™, a platform it says was built specifically for this new reality.

After years of behind-the-scenes development and deployment across client programs, RankOS™ is now officially out of stealth. NEWMEDIA.COM positions it not as another SEO tool, but as an operating system for brand visibility across both AI-driven and traditional search environments.

The timing is deliberate. As generative AI reshapes Google Search, Bing, and standalone AI assistants, ranking on page one is no longer the finish line. In many cases, it’s not even part of the journey.

When Ranking No Longer Equals Visibility

For more than two decades, search optimization followed a relatively clear logic: improve rankings, earn clicks, drive traffic. AI-powered search is breaking that model.

Large language models increasingly answer queries directly, citing sources selectively—or not at all. Brands can rank well organically and still remain invisible inside AI-generated responses.

According to a 2025 AI visibility audit conducted by NEWMEDIA.COM, the gap is already stark. The firm found that 87% of Colorado-based businesses fail to appear in AI-generated search answers, even when many of them perform strongly in traditional SEO.

That disconnect is the problem RankOS™ is designed to solve.

“AI systems don’t just index websites,” said Steve Morris, Founder and CEO of NEWMEDIA.COM. “They rank brands based on trust, citations, and authority. RankOS™ was built to help businesses understand how they’re being perceived by AI—and how to systematically improve those signals.”

SEO Alone Isn’t Enough Anymore

The rise of AI search has exposed a limitation in traditional digital marketing stacks. SEO tools are excellent at tracking rankings, keywords, and backlinks—but they offer little insight into whether a brand is being recognized, trusted, or cited by AI systems.

RankOS™ aims to fill that gap by unifying disciplines that are typically siloed:

• Search engine optimization

• Public relations and earned media

• Structured data and entity optimization

• AI visibility and citation measurement

Rather than treating these as separate tactics, RankOS™ brings them together under a single framework focused on brand-level authority, not just page-level performance.

The underlying premise is simple: AI answers don’t reward pages—they reward entities.

Built for AI Engine Optimization (AEO)

NEWMEDIA.COM describes RankOS™ as both a platform and an operating methodology, designed to support what the agency calls AI Engine Optimization (AEO).

At a functional level, the system is designed to:

• Measure how brands appear (or fail to appear) across AI engines and search platforms

• Track citations, entity authority, and trust signals

• Identify specific gaps preventing brands from being recognized by AI systems

• Coordinate SEO, PR, and structured entity optimization into a single visibility strategy

Unlike conventional tools that focus on traffic growth, RankOS™ is engineered to answer a more existential question for modern brands: Does AI know who you are—and does it trust you enough to recommend you?

That distinction is increasingly critical as AI-generated answers become the first—and sometimes only—touchpoint between brands and customers.

From Rankings to Recognition

One of RankOS™’s core differentiators is its focus on verification rather than visibility metrics alone.

AI systems rely heavily on corroboration. They look for consistent brand signals across reputable media, authoritative websites, structured datasets, and trusted citations. Inconsistent or weak signals can result in exclusion, regardless of how well a website ranks.

RankOS™ continuously monitors how a brand is represented across:

• Media coverage and citations

• Web content and entity references

• AI-generated answers and summaries

From there, it prescribes targeted actions designed to strengthen authority and improve the likelihood of being cited by AI models.

In practice, that can mean aligning PR strategies with SEO objectives, refining structured data to reinforce entity clarity, or addressing trust gaps caused by fragmented online presence.

A Response to a Structural Market Shift

The launch of RankOS™ reflects a broader trend unfolding across digital marketing. As generative AI becomes embedded in search experiences, the industry is being forced to rethink long-standing assumptions.

Traditional SEO is not disappearing—but it is being subordinated to a larger visibility challenge. Brands that fail to adapt risk becoming invisible, even if their websites remain technically optimized.

Competitors across the MarTech landscape are beginning to respond with AI-focused features, but most solutions remain incremental. RankOS™ takes a more foundational approach, treating AI visibility as a systemic problem rather than a reporting add-on.

That perspective is shaped by NEWMEDIA.COM’s long tenure in performance marketing, where attribution gaps and platform shifts are familiar territory.

From Stealth to Scale

NEWMEDIA.COM confirms that RankOS™ has already been deployed quietly across multiple client programs prior to its public release. Those early implementations helped refine both the platform and its methodology before formal launch.

Looking ahead, the company plans to expand RankOS™ with:

• Additional reporting and analytics modules

• AI visibility benchmarking releases

• Broader measurement across emerging AI answer engines

These updates are slated for late 2025 and throughout 2026, signaling that RankOS™ is intended to evolve alongside the rapidly changing AI search ecosystem.

Why This Matters for Marketers and Brands

For marketing leaders, the implications are significant. Visibility is no longer controlled solely by algorithms ranking pages—it’s increasingly mediated by AI systems synthesizing information from across the web.

That shift raises uncomfortable questions:

• Why does AI cite competitors instead of us?

• Why does our brand disappear in AI answers despite strong SEO performance?

• How do we measure authority in systems that don’t show rankings or traffic?

RankOS™ doesn’t claim to solve AI search overnight, but it does provide a structured way to engage with those questions—using data, measurement, and coordinated execution rather than guesswork.

The Bottom Line

RankOS™ enters the market at a moment when digital visibility is being fundamentally redefined. As AI-generated answers replace traditional search results, brands that rely solely on rankings risk fading into the background.

By reframing visibility around trust, citations, and entity authority, NEWMEDIA.COM is betting that the future of search belongs to brands that can be understood and verified by AI, not just indexed by crawlers.

In the AI era, being found is no longer enough. Being recognized is what counts.

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Incubeta is making a clear bet on continuity, AI-led growth, and internal leadership as it charts its next phase in the Americas. The global digital marketing firm has appointed Amy Crowther as President, Americas, formally kicking off a planned leadership transition that will see her step into the role of Americas CEO in 2026.

The move comes at a moment of momentum for Incubeta. The company is delivering strong regional performance while advancing the strategic acquisition of RocketSource, a deal that sharpens its focus on AI-powered marketing, data-driven decisioning, and scalable global delivery. Crowther’s appointment signals not just a change in title, but a broader shift toward operational scale and AI-enabled execution across the region.

A Structured Succession, Not a Sudden Shift

Unlike abrupt executive reshuffles that can rattle clients and teams, Incubeta’s transition is deliberately phased. Crowther, who previously served as Chief Client Officer, will begin assuming full operational responsibility for the Americas business in January 2026, overseeing strategy, execution, and client engagement across the company’s core growth areas.

Those areas include integrated media, creative, data and measurement, Marketing Intelligence, and AI-enabled operations designed to support multi-market delivery at scale. In other words, the parts of the business where complexity is rising fastest—and where clients increasingly need partners who can connect technology, data, and outcomes.

Current Americas CEO Alex Langshur isn’t exiting the picture entirely. As part of the succession plan, he will move into a newly created role in July 2026 as Executive Advisor and M&A Integration Leader, providing strategic guidance and ensuring continuity, particularly as Incubeta integrates acquisitions like RocketSource.

For a services firm operating in a volatile martech and agency landscape, that level of planning is notable.

Why Amy Crowther, Why Now?

Crowther’s elevation reflects her growing influence inside Incubeta over the past several years. As Chief Client Officer, she has been closely involved in strengthening client relationships, improving operational rigor, and aligning delivery teams around measurable business outcomes—an increasingly critical mandate as marketers demand accountability from agency partners.

“Amy has been a powerful force in shaping our success across the Americas,” said Jacques van Niekerk, Group CEO at Incubeta. “Her leadership and commitment to clients have influenced the way we operate, making her uniquely positioned to lead the US business forward.”

Her background supports that confidence. Before joining Incubeta, Crowther held senior leadership roles at Jellyfish, IPG (Reprise), and Dentsu, where she built and led multinational strategy and planning teams, managed global client delivery, and advised enterprise brands on modern marketing best practices.

That mix of media, strategy, consultancy, and performance marketing experience matters in today’s environment, where clients are less interested in channel silos and more focused on integrated growth.

AI Moves From Promise to Operating Reality

Crowther’s appointment also aligns with a broader shift in how Incubeta is positioning itself in the market. Like many agencies, the firm talks openly about AI—but its recent actions suggest a focus on operationalizing AI rather than treating it as a buzzword.

The RocketSource acquisition, for example, is designed to strengthen Incubeta’s capabilities in AI-driven marketing intelligence, automation, and advanced analytics. Combined with Crowther’s client-centric leadership style, the goal appears to be translating AI potential into practical, repeatable value for brands.

“As the promise of AI meets the reality of our clients' day-to-day business needs, we have an important role in helping them navigate that complexity and turn it into meaningful outcomes,” Crowther said.

That framing is telling. Many brands are struggling to reconcile AI experimentation with real-world constraints like data quality, regulatory pressure, and fragmented tech stacks. Agencies that can bridge that gap—without overselling—stand to gain trust in a crowded market.

Implications for the Americas Business

Under Crowther’s leadership, Incubeta’s Americas organization is expected to double down on scale and integration. That means tighter coordination across media, creative, data, and measurement, alongside increased investment in AI-enabled operations that support multi-market clients.

It also suggests a continued shift away from campaign-centric thinking toward always-on, intelligence-led marketing models. For enterprise clients operating across regions, that kind of consistency is becoming a baseline expectation rather than a differentiator.

From a talent perspective, the promotion reinforces Incubeta’s emphasis on internal development. In an industry where executive turnover is high and external hires often struggle to acclimate, promoting from within can provide stability—assuming execution keeps pace with ambition.

A Signal to the Market

Leadership announcements don’t usually move markets, but they do send signals. In this case, Incubeta is signaling that it sees the next phase of growth in the Americas as operationally complex, AI-intensive, and client-driven—and that it wants experienced hands steering the transition.

The phased CEO succession, continued involvement of the outgoing CEO, and emphasis on AI-enabled delivery all point to a company trying to balance innovation with reliability. For clients navigating their own transformations, that balance may be exactly what they’re looking for.

As 2026 approaches, Crowther’s challenge will be to convert that strategy into sustained performance. If she succeeds, Incubeta’s leadership transition could become a case study in how agencies evolve without losing momentum.

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As customer journeys grow more fragmented and expectations climb, CSG is staking a clear claim in the crowded customer engagement market. The company announced that its flagship platform, CSG Xponent, has earned multiple third-party honors for customer journey management, analytics, and personalization—recognition that reinforces its positioning as a full-service, real-time engagement platform rather than another static CX tool.

In just the past month, CSG Xponent was named a Leader in QKS Group’s 2025 SPARK Matrix for Customer Journey Management, won Best Personalisation and User Experience Solution at the 2025 FinTech Futures Banking Tech Awards, and was recognized as a Core Performing provider in CMP Research’s Prism for Customer Analytics. Taken together, the accolades highlight a growing consensus: brands are moving beyond dashboards and journey maps toward platforms that can actually act in the moment.

From Mapping Journeys to Managing Them

For years, customer journey management has been long on insight and short on execution. Many platforms excel at visualizing journeys but fall apart when it comes to real-time decisioning or tying actions to financial outcomes. That gap is exactly where CSG Xponent is aiming to differentiate.

According to Tanuj Paulose, Analyst at QKS Group, the platform goes beyond broad segmentation by identifying each customer’s precise journey state—whether stalled, at risk, or ready to convert—and quantifying the business impact of specific interventions. By unifying journey analytics, real-time orchestration, identity, and omnichannel communications, Xponent makes customer journey management operational rather than theoretical.

That distinction matters, especially in complex, high-volume industries like media, financial services, healthcare, and retail, where customer interactions unfold across channels, devices, and touchpoints in seconds—not days.

Why Real-Time CX Is Becoming Table Stakes

The recognition comes as brands face a widening gap between customer expectations and internal execution. Consumers now expect relevance, consistency, and immediacy across every interaction, while businesses struggle with siloed data, delayed insights, and disconnected teams.

CSG Xponent is designed to address that friction by integrating real-time data streams with in-the-moment personalization. Instead of flagging journey breaks after the fact, the platform enables brands to detect and correct issues as they occur—whether that’s a stalled onboarding flow, a billing-related frustration, or a missed upsell opportunity.

In practice, that means fewer static journey maps and more adaptive, always-on orchestration. The goal isn’t just better experiences, but clearer accountability: which actions worked, which didn’t, and how each decision affected revenue, retention, or lifetime value.

Recognition Across Analytics, Personalization, and Execution

The breadth of recent awards underscores Xponent’s positioning as a convergence platform rather than a point solution. CMP Research’s Prism recognition highlights its analytics depth, while the FinTech Futures award points to its strength in personalization and user experience—critical capabilities for banks and financial institutions under pressure to modernize digital engagement.

Meanwhile, QKS Group’s SPARK Matrix leadership places Xponent among top global players in customer journey management, a category that has grown increasingly competitive as vendors race to layer AI and automation onto legacy CX stacks.

What sets Xponent apart, according to analysts, is its ability to connect insight to action without introducing more complexity. In industries where regulatory constraints, legacy systems, and scale often slow innovation, that balance can be decisive.

Moving Beyond “Customer-Obsessed” as a Slogan

“Almost every brand strives to be customer-obsessed, but few can capture a complete, real-time picture of their customers and act on it,” said Katie Costanzo, President of Customer Experience at CSG. Her point reflects a broader industry reckoning: intent alone isn’t enough when customer interactions are shaped by milliseconds and machine-driven decisions.

Costanzo argues that brands need to move beyond static journey maps toward intelligent, autonomous systems that anticipate needs and respond proactively. That philosophy aligns with a broader shift in CX technology—from descriptive analytics to prescriptive and increasingly agentic systems.

The Agentic Future of Customer Engagement

CSG isn’t stopping with today’s recognition. The company is positioning Xponent as the foundation for its most significant AI push yet: Agentic Orchestration. This approach uses coordinated intelligent agents to balance control and adaptability, allowing brands to automate decision-making while maintaining governance and transparency.

Agentic systems are emerging as the next frontier in CX, especially as brands grapple with what CSG calls the “Age of Overwhelm”—a reality where customers are inundated with messages, choices, and friction across channels. In this environment, relevance isn’t just a nice-to-have; it’s a survival requirement.

CSG’s forthcoming 2026 State of the Customer Experience Report is expected to explore these dynamics in detail, offering insight into how customer expectations are evolving and what brands must do to keep pace.

What This Means for the MarTech Landscape

The momentum behind CSG Xponent reflects a broader trend in martech and CX platforms: consolidation around systems that combine analytics, orchestration, and execution in real time. As AI becomes embedded across the stack, vendors that can translate intelligence into measurable business outcomes will pull ahead.

For enterprise brands, especially those in regulated or high-volume sectors, the appeal lies in platforms that reduce operational complexity rather than add to it. Recognition from multiple analyst firms suggests that CSG Xponent is resonating with that need.

In a market crowded with promises of personalization and AI-driven engagement, third-party validation matters. For CSG, these recent honors are less about trophies and more about signaling that customer journey management is finally moving from theory to practice.

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