Propelis is expanding its integrated brand services model in Japan by bringing together the package design capabilities of Marks with SGX's packaging production expertise. The move reflects a broader shift in enterprise marketing toward connected creative, content and production workflows, as brands look to reduce fragmented processes while maintaining the precision required by Japan's demanding consumer market.

For global consumer brands, packaging is no longer just a physical product wrapper. It has become a critical brand asset that must remain consistent across retail shelves, e-commerce listings, digital campaigns and increasingly complex product portfolios.

Propelis, the global brand services group created through the merger of SGK and SGS & Co, is leaning into that shift in Japan by connecting Marks' package design capabilities with SGX's packaging production operations.

The model is designed to create a more continuous path from creative concept to physical production and, eventually, digital content. Instead of treating design, artwork management, prepress, production and content creation as disconnected stages, Propelis is attempting to bring those functions into a coordinated workflow.

For enterprise marketing teams managing hundreds or thousands of SKUs, that distinction can have practical consequences. Fragmented approvals and repeated handoffs between creative agencies, packaging suppliers and production teams can introduce errors, delay launches and create inconsistencies between markets.

Propelis says connecting Marks and SGX can reduce duplicated work and allow packaging and content assets to be developed in parallel. The broader objective is to maintain a consistent brand identity across physical packaging and digital channels while adapting creative assets to local requirements.

The strategy also builds on Propelis' broader content and workflow capabilities. Its network includes Collide and 5Flow, which add content production and workflow technology to the group's brand services portfolio.

Following the integration of Marks and SGK Global Creative Operations, Marks now has more than 2,100 creative specialists across 25 global hubs. That scale gives the company a larger operating base for multinational brand programs that require localized creative execution without abandoning centralized brand governance.

The Japanese market provides a particularly relevant test for that model. Retail food and beverage sales in Japan reached approximately $193 billion in 2024, according to the figures cited by Propelis, while packaging expectations continue to evolve around convenience, sustainability and waste reduction.

Localization adds another layer of complexity. Packaging for products sold in Japan must account for Japanese-language product information and labeling requirements, alongside color accuracy, artwork specifications, print production and other manufacturing considerations.

That makes the connection between creative and production more than an efficiency argument. Errors that occur late in the packaging workflow can affect physical products already scheduled for distribution, making quality control and approval management important components of brand operations.

"Execution is just as important as creative ideas," said Reiko Nakamura, Managing Director, Marks & SGX, Japan and Korea.

That distinction is becoming increasingly relevant as enterprise marketing organizations attempt to manage global brands across more channels. A packaging design may become the visual foundation for an e-commerce product page, social campaign, digital advertisement or promotional asset. Recreating those elements separately for every channel can introduce visual inconsistencies and increase production costs.

Propelis' strategy is to treat packaging as part of a broader content ecosystem rather than as an isolated production deliverable.

This also places the company within a wider MarTech trend: the convergence of creative operations, digital asset management, content production and workflow automation.

Companies such as Adobe have spent years connecting creative production with digital content workflows, while enterprise marketing platforms from Salesforce and other technology providers increasingly focus on coordinating customer-facing experiences across channels. Propelis approaches the problem from the brand production side, where physical packaging and creative execution remain central to the workflow.

The company's use of controlled AI for quality checks, approval tracking and content testing adds another technology layer. AI in this context is less about replacing creative teams and more about reducing operational friction around repetitive checks, workflow monitoring and asset validation.

That distinction could prove important for enterprise buyers. Generative AI can accelerate content creation, but multinational packaging programs require systems that can also preserve brand standards, regulatory information and production accuracy.

Propelis' expansion therefore represents a broader attempt to connect the front and back ends of brand execution. Marks provides strategy, design and content capabilities, while SGX contributes artwork management, prepress, print management and packaging production expertise.

The company's challenge will be proving that this integrated model can deliver measurable improvements without sacrificing the local knowledge and detailed execution that Japanese brands and consumers expect.

For multinational consumer companies, the potential value is straightforward: fewer disconnected handoffs, greater control over brand assets and a more consistent route from package design to e-commerce and digital marketing.

As marketing organizations increasingly manage physical and digital experiences as one connected brand system, providers that can bridge those environments may gain an advantage over agencies and production specialists operating in narrower silos.

Market Landscape

The packaging and creative services market is moving toward greater integration as consumer brands manage more SKUs, more digital touchpoints and increasingly localized customer experiences.

Traditional operating models often separate brand strategy, creative development, artwork, packaging production and digital content. While specialization can bring expertise, it can also create multiple approval points and increase the risk of inconsistencies.

Propelis' Marks and SGX model addresses that fragmentation by connecting creative development with physical execution. The approach is particularly relevant in FMCG, food and beverage, beauty and home care, where packaging is simultaneously a product requirement, retail asset and brand communication channel.

The rise of e-commerce makes the connection even more important. A consumer may encounter a product online before seeing it in a physical store, meaning inconsistencies between packaging, product imagery and digital content can weaken brand recognition.

The competitive landscape includes creative networks, packaging specialists, production companies and enterprise MarTech ecosystems. Adobe's creative and content technology represents one side of the market, while agencies and specialized packaging providers address other parts of the workflow.

Propelis is attempting to compete through integration across those traditionally separate functions.

Strategic Outlook

Propelis' Japan expansion illustrates how brand execution is becoming a technology and operations challenge as much as a creative one.

The next stage of competition will likely focus on how effectively providers connect creative assets, packaging workflows, content localization, approval processes and AI-assisted quality controls.

For enterprise marketing teams, the appeal is not simply having more services under one organization. The real opportunity is creating a controlled system in which one brand identity can move from packaging to e-commerce, advertising and digital content without unnecessary recreation or loss of consistency.

Japan could become an important market for testing that proposition because its combination of mature consumer categories, demanding packaging standards and detailed localization requirements places a premium on execution quality.

Top Insights

• Propelis is connecting Marks' package design with SGX production capabilities, reducing workflow fragmentation for brands managing complex packaging programs in Japan.
• The model extends packaging assets into e-commerce and digital content, helping enterprise marketers maintain visual consistency across physical and digital customer experiences.
• Japan's detailed labeling and production requirements make artwork management, prepress, color accuracy and approval controls critical components of multinational brand execution.
• Propelis' controlled AI strategy focuses on quality checks, approval tracking and content testing, positioning AI as an operational layer rather than creative replacement.
• The integration increases competition among creative agencies, packaging specialists and MarTech platforms seeking to control more of the enterprise brand lifecycle.

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Apollo is adding another layer to its push into AI-powered go-to-market software, announcing recognition from the Inc. 5000, the 2026 MarTech Breakthrough Awards and G2. The awards arrive as sales and marketing teams increasingly look beyond standalone prospecting and automation tools toward platforms that can combine data, intelligence and execution in a single workflow.

Apollo, the AI-powered go-to-market platform, has received a series of industry recognitions that highlight both its recent growth and its positioning in the increasingly crowded SalesTech market.

The company said it ranked No. 54 among AI companies on the 2026 Inc. 5000 list, No. 46 among companies in the San Francisco Bay Area and within the top quarter of the overall ranking of America's fastest-growing private companies.

Separately, Apollo was named a winner of the 2026 MarTech Breakthrough Awards in the SalesTech Innovation category for its Apollo AI Assistant. The program recognizes technology companies and products across marketing, sales and advertising technology.

The distinction is notable because Apollo is competing in a market that has shifted from traditional sales intelligence toward AI-assisted revenue operations. Rather than treating prospect discovery, lead scoring, engagement and workflow automation as separate functions, newer platforms are attempting to connect those activities through a unified data and AI layer.

Apollo describes its product as an AI go-to-market system rather than simply a contact database or sales engagement platform. Its technology combines sales intelligence, prospecting and engagement capabilities with AI-driven assistance designed to help revenue teams identify opportunities and execute go-to-market activities.

The company also pointed to recent recognition from G2, saying it ranked first in more than 100 of G2's 2026 Summer Reports. Those include categories covering lead-to-account matching and routing, lead capture and lead scoring across different customer segments.

For enterprise marketing and sales teams, that positioning reflects a broader technology shift. AI is increasingly being embedded directly into revenue workflows instead of operating as a separate productivity layer. In practice, that can mean using AI to interpret prospect and account data, prioritize potential buyers, generate outreach and recommend next actions.

McKinsey's research illustrates why vendors are pursuing this direction. Its B2B Pulse Survey found that 19% of respondents were already implementing generative AI use cases for B2B buying and selling, while another 23% were in the process of doing so.

The broader economic case is also substantial. McKinsey estimates that generative AI could increase sales productivity by roughly 3% to 5% of current global sales expenditures, although realizing that value depends on how effectively AI is integrated into business processes and data environments.

That caveat is important for evaluating Apollo's growth story. Awards and customer adoption can demonstrate market traction, but they do not automatically establish that an AI-powered GTM platform produces better revenue outcomes. Gartner has warned that productivity improvements from AI in sales and marketing do not necessarily translate into stronger business performance, underscoring the importance of measuring outcomes rather than AI usage alone.

Apollo says more than 600,000 companies use its platform, including more than 100 Fortune 500 teams. Those figures, if sustained, put the company in a different competitive conversation from narrowly focused sales automation tools.

The competitive landscape includes established CRM and marketing ecosystems from companies such as Salesforce and Microsoft, as well as specialized sales intelligence, engagement and revenue-operations platforms. Apollo's challenge is therefore not simply adding AI features. It must demonstrate that an integrated GTM system can deliver reliable data, useful recommendations and measurable improvements without creating another disconnected layer in an already complex enterprise MarTech stack.

The role of AI assistants could become particularly significant here. If an assistant can move from answering questions about prospects to executing approved actions across workflows, the distinction between sales intelligence software and autonomous revenue operations begins to blur.

That evolution mirrors the wider direction of enterprise AI. Gartner has projected that specialized generative AI models will account for more than half of enterprise GenAI models by 2027, reflecting a move toward systems optimized for specific business functions rather than generic AI capabilities.

For Apollo, the Inc. 5000 ranking provides a growth signal, while the MarTech Breakthrough and G2 recognition reinforce its product positioning. The more meaningful test will be whether the company can turn that momentum into durable differentiation as AI becomes a standard component of SalesTech, marketing automation and enterprise revenue infrastructure.

Market Landscape

The GTM software market is moving toward convergence. CRM, sales intelligence, marketing automation, customer data and AI assistants are increasingly overlapping, creating pressure on vendors to offer broader workflows rather than isolated capabilities.

This favors platforms that can connect data with action. A sales team may no longer want one application for identifying accounts, another for enriching contacts, another for generating outreach and a separate AI assistant for analysis.

At the same time, enterprise buyers remain cautious. Gartner reported that 27% of marketing leaders surveyed had limited or no GenAI adoption in marketing campaigns, while 47% of organizations using GenAI reported a large benefit from the technology for campaign evaluation and reporting.

Apollo's opportunity sits directly within this transition: turning AI from an experimental capability into an operational component of the revenue stack.

Strategic Outlook

Apollo's latest recognition strengthens its position in AI-powered SalesTech, but the next phase of competition will be measured less by awards and more by workflow depth, data quality, integration and measurable revenue impact.

For enterprise marketing teams, the important question is whether platforms such as Apollo can complement existing CRM, CDP and marketing automation infrastructure rather than becoming another silo.

The direction is clear: AI is moving closer to the point where marketing and sales decisions are made. Platforms capable of combining trusted customer data with AI-assisted execution are likely to become increasingly important components of modern enterprise MarTech stacks.

Top Insights

• Apollo's Inc. 5000 ranking signals rapid company growth as AI-powered go-to-market platforms gain traction among businesses seeking integrated revenue workflows.
• The 2026 MarTech Breakthrough Award recognizes Apollo AI Assistant, highlighting the growing convergence between artificial intelligence, SalesTech and marketing automation.
• G2 recognition across more than 100 reports strengthens Apollo's product credibility, particularly across lead capture, scoring, routing and account-matching workflows.
• Apollo's 600,000-company customer claim positions it beyond niche sales tools, increasing competition with broader CRM and revenue technology ecosystems.
• Enterprise buyers will increasingly evaluate GTM AI platforms on measurable revenue outcomes, data quality and workflow integration rather than feature counts alone.

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A virtual influencer can publish content without the production requirements associated with a traditional human creator, potentially allowing operators to create and distribute content at much greater frequency. But audience scale alone does not guarantee a viable business.

RM11's new framework argues that AI creators need multiple monetization channels rather than depending on a single subscription or advertising deal.

Its model includes six primary revenue categories. Subscriptions provide recurring income in exchange for access to exclusive content, while pay-per-view allows individual premium posts, videos or content bundles to be sold separately.

Brand partnerships and affiliate marketing create commercial revenue outside direct fan payments. Paid messaging and custom content add a personalized layer, while tips, livestreams and one-to-one calls are designed to monetize real-time engagement.

The underlying strategy is straightforward: build one digital persona and give its audience several ways to spend.

Subscriptions Are Only the Starting Point

Recurring subscriptions can provide predictable revenue, but they also expose creators to churn. Every subscriber who cancels reduces future revenue, making retention as important as acquisition.

That makes the other channels strategically important.

Pay-per-view content can monetize high-intent fans without requiring them to maintain a subscription. Affiliate marketing can turn existing social content into an ongoing source of commissions, while brand partnerships can provide larger individual transactions when an AI persona reaches sufficient audience scale.

Paid messaging and custom content represent another potentially valuable category because the revenue is tied to personalization rather than mass distribution.

For AI creators, this can be particularly interesting. Generative AI can reduce the marginal cost of producing customized digital content, although the economics still depend on the technology stack, moderation, platform fees, human oversight and the quality of the resulting experience.

RM11 says its platform allows creators to retain 90% of platform revenue and supports memberships, locked content, messaging, livestreaming and direct fan engagement. The company's earlier 2026 announcement also described the 90% creator payout model.

Real-Time Interaction Could Become the Higher-Value Layer

RM11's sixth category—tips, livestreams and calls—highlights an important distinction between content production and audience relationships.

AI can make content generation relatively inexpensive, but fan engagement is a different problem.

Livestreams, voice-based conversations and personalized interactions can create a stronger sense of continuity around a digital persona. RM11 says its platform supports one-to-one calls for AI personas using voice synthesis technology from ElevenLabs.

That could make interactive experiences an important component of AI creator economics. Instead of treating an AI influencer as an automated content feed, operators can build a persistent character with a recognizable personality and recurring interactions.

The business model begins to resemble a combination of subscription media, social commerce and digital entertainment.

The Market Is Growing, but Competition Is Increasing

The opportunity extends beyond individual creator platforms.

Straits Research estimates that the global virtual influencer market was worth $6.33 billion in 2024 and could reach $111.78 billion by 2033, representing a projected 38.4% compound annual growth rate. The research covers both non-human and human-avatar virtual influencers across industries including entertainment, fashion, finance and travel.

Meanwhile, AI is becoming increasingly common in the broader creator economy. Adobe's 2026 Creators' Toolkit report found that 87% of creators using creative AI said it had accelerated the growth of their business or audience, while 75% described AI as integrated or essential to their workflows.

That creates a paradox.

The cost of creating content is falling, which means supply can increase rapidly. As more AI personas compete for attention, simply producing more images or videos is unlikely to create a durable competitive advantage.

Distinctive characters, audience relationships, distribution and monetization infrastructure could matter more.

AI Creators Still Face a Trust Problem

The economics of AI influencers also come with a significant caveat: audiences may not treat synthetic creators the same way they treat human creators.

Sprout Social's 2026 influencer marketing research found that 44% of consumers were uncomfortable with brands using AI influencers and warned that a lack of transparency around synthetic partnerships can damage audience trust.

That makes disclosure and authenticity important considerations for AI creator businesses.

An AI persona may have no human biography in the conventional sense, but the audience still needs to understand who operates it, what is automated and what interactions are generated or supervised.

For brands, the issue becomes even more important. A company partnering with an AI influencer will need to evaluate not just audience size and engagement, but disclosure practices, brand safety, intellectual property, synthetic media policies and the potential for reputational risk.

The Competitive Landscape Is Shifting Toward Creator Infrastructure

RM11 is entering a market that includes subscription platforms, creator marketplaces, influencer marketing technology, social commerce tools and AI-generated persona platforms.

Its differentiator is the attempt to combine direct-to-fan monetization with infrastructure specifically designed for AI creators.

That strategy is consistent with the broader evolution of creator software. Instead of simply helping creators publish content, platforms are increasingly trying to manage the complete business lifecycle: audience acquisition, content production, payments, messaging, analytics and retention.

For AI creators, that infrastructure may become particularly important because the technical barrier to producing content is falling faster than the operational barrier to building a trusted business.

Market Landscape

Virtual influencers are entering a more mature phase of the creator economy. The market is growing rapidly, but so is the volume of synthetic content competing for audience attention.

Research from Straits Research projects a 38.4% CAGR for the global virtual influencer market through 2033, while Adobe's creator research shows that AI has already become part of mainstream creator workflows.

The next competitive battleground is therefore likely to be monetization rather than content generation alone.

AI creators can potentially operate across multiple revenue streams at once, but success will depend on audience retention, platform economics, trust, intellectual property and the distinctiveness of each digital persona.

The strongest businesses may ultimately resemble media companies more than traditional influencer accounts.

Strategic Outlook

The rise of AI influencers could push creator monetization toward a portfolio model.

Instead of relying on sponsorships or subscriptions, digital personas can combine recurring memberships, premium content, affiliate commerce, personalized interactions and live experiences. That diversification can reduce dependence on any single revenue source while increasing the number of ways an engaged audience can participate.

But automation does not eliminate the fundamentals of creator economics.

AI may reduce production costs, yet attention remains scarce. Digital personas still need recognizable identities, compelling narratives and consistent audience engagement. The creators that succeed at scale will likely be those that use AI to increase output while investing equally in differentiation, community and trust.

For marketing teams, the development also creates a new category of potential media partner—and a new set of questions around disclosure, authenticity and brand safety.

Top Insights

• RM11's six-stream framework shows how AI influencers can combine subscriptions, premium content, partnerships and direct fan engagement into diversified creator businesses.
• Falling AI content-production costs could increase margins, but audience attention remains scarce and differentiation will become increasingly important for synthetic creators.
• Virtual influencer market projections point to rapid growth, creating opportunities for platforms that provide monetization, payments, engagement and creator-business infrastructure.
• Brand partnerships with AI influencers introduce new considerations around disclosure, intellectual property, audience trust, synthetic media and long-term brand safety.
• Direct fan engagement through messaging, livestreams and calls could become a higher-value monetization layer as AI personas develop persistent digital identities.

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BTQ Technologies and ITCEN PNS are establishing a framework to evaluate, test and potentially commercialize quantum-resistant security technologies in Korea and international markets.

The companies said the collaboration will cover financial networks, digital identity, biometric authentication, blockchain and Web3 security, as well as broader enterprise and government infrastructure.

The timing is significant. Post-quantum cryptography has moved beyond a theoretical cybersecurity concern. The U.S. National Institute of Standards and Technology (NIST) finalized three principal PQC standards in 2024, including ML-KEM for key establishment and ML-DSA and SLH-DSA for digital signatures. NIST now recommends that organizations begin transitioning systems toward quantum-resistant cryptography.

PQC is designed to protect information against future quantum computers capable of undermining some of the mathematical assumptions behind widely used public-key cryptography. That creates a migration problem for enterprises: replacing cryptographic infrastructure can take years, particularly in heavily regulated environments where security products must be tested and validated before deployment.

The BTQ-ITCEN PNS relationship is therefore less about inventing another quantum algorithm and more about connecting quantum-safe technology with existing enterprise infrastructure.

ITCEN PNS Brings Regulatory and Deployment Experience

A key component of the agreement is ITCEN PNS's experience deploying security technologies in Korea.

According to BTQ, ITCEN PNS has developed products spanning biometric authentication, electronic signatures, mobile security, data protection and digital financial security, with deployments across Korean banks and insurance companies.

The company also obtained KCMVP validation for a hybrid cryptographic module in July 2026, according to the announcement. The module combines conventional public-key cryptography with post-quantum algorithms including ML-KEM.

KCMVP, Korea's Cryptographic Module Validation Program, is particularly relevant to government and public-sector security deployments. The validation provides an important bridge between laboratory-level cryptography and technology that can be considered for regulated environments.

That distinction could become increasingly important as organizations move from PQC pilots to production systems.

NIST's own migration guidance emphasizes that organizations need to plan the transition from quantum-vulnerable algorithms to quantum-resistant standards rather than waiting until quantum computers become capable of breaking existing systems.

Why Hybrid Cryptography Matters

The reference to a hybrid cryptographic module is significant because enterprise PQC migration is unlikely to happen as a single overnight replacement.

Organizations operate complex environments containing legacy applications, hardware, network infrastructure and third-party systems. Replacing every cryptographic dependency simultaneously would create substantial operational and compatibility risks.

Hybrid approaches can allow conventional and post-quantum mechanisms to operate together during migration.

ML-KEM, one of the standards finalized by NIST, is a key-encapsulation mechanism used to establish shared secret keys between communicating parties. NIST describes ML-KEM as a foundational standard for post-quantum key establishment.

For financial institutions and government systems, the practical challenge is therefore not simply selecting a PQC algorithm. It is integrating quantum-resistant cryptography into authentication, identity, communications and data-security infrastructure without disrupting existing operations.

That is where ITCEN PNS's implementation experience could provide BTQ with an important route into enterprise environments.

Korea's Security Market Is Becoming a PQC Testbed

South Korea has invested heavily in digital infrastructure, financial technology, cloud computing and cybersecurity, creating a large ecosystem in which quantum-safe technologies can be tested against real-world requirements.

The country's broader cybersecurity policy is also moving toward stronger security architectures. In February 2026, the Korea Internet & Security Agency (KISA) and South Korea's Ministry of Science and ICT announced a 2026 Zero Trust adoption pilot program aimed at expanding Zero Trust implementation in the private sector.

Zero Trust and post-quantum cryptography address different security problems, but they share an important enterprise objective: reducing assumptions about trust and strengthening security across increasingly distributed infrastructure.

For financial institutions, the convergence is particularly relevant. Digital banking environments depend on identity systems, encrypted communications, mobile authentication, APIs and cloud infrastructure. Quantum-safe security will eventually need to operate across all of those layers.

The Competitive Landscape

BTQ is entering a market that includes established cybersecurity vendors, cryptographic technology providers, cloud companies and specialist post-quantum security firms.

Major technology ecosystems including Microsoft, Google and IBM have been developing PQC migration capabilities, while cybersecurity vendors are incorporating quantum-resistant algorithms into network security, identity and encryption products.

The competitive question is therefore shifting.

It is no longer enough for a company to demonstrate that its cryptography is quantum-resistant. Enterprise customers need migration tooling, validated implementations, compatibility with existing infrastructure and deployment expertise.

That makes local partnerships potentially valuable. ITCEN PNS provides access to a Korean security market where regulatory requirements and established relationships can influence technology adoption.

From Quantum Research to Infrastructure

BTQ's strategy is built around what happens after the cryptographic standards are established.

NIST has already standardized ML-KEM, ML-DSA and SLH-DSA, and selected HQC for standardization as an additional key-establishment algorithm in 2025.

The industry is consequently entering a migration phase.

Enterprises must inventory cryptographic dependencies, identify systems that require replacement or upgrades, test new algorithms and develop transition strategies. Long-lived sensitive information also creates a concern often described as "harvest now, decrypt later," where encrypted information captured today could potentially be decrypted in the future if sufficiently capable quantum computers emerge.

The BTQ-ITCEN PNS agreement addresses this implementation layer. If the MOU progresses into commercial deployments, the partnership could provide a route for quantum-safe technologies to move into banking, public-sector and enterprise environments rather than remaining primarily in research and pilot projects.

Market Landscape

Post-quantum cybersecurity is moving into an enterprise migration cycle. NIST says organizations should begin applying its PQC standards now, reflecting the long lead times required to replace vulnerable cryptographic infrastructure.

The challenge is especially pronounced in financial services and government, where authentication, digital identity and encrypted communications are deeply embedded across legacy and modern systems.

Korea's combination of advanced digital infrastructure, regulated financial institutions and active cybersecurity programs makes it a strategically important market for PQC deployment.

For BTQ, the partnership with ITCEN PNS provides access to an established security channel. For ITCEN PNS, BTQ could add another layer of quantum-focused technology to its existing security portfolio.

The real test will be whether the relationship produces validated products, production deployments and measurable migration outcomes.

Strategic Outlook

The next stage of post-quantum cybersecurity will be defined less by algorithm announcements and more by integration.

Banks, government agencies and large enterprises will need to determine which systems are most exposed, where hybrid cryptography is appropriate and how quantum-safe authentication can be incorporated into existing identity infrastructure.

That creates opportunities for vendors that can combine cryptographic expertise with hardware security, identity management, cloud infrastructure and compliance.

BTQ and ITCEN PNS are positioning their MOU around precisely that intersection.

The agreement does not itself represent a commercial deployment, and the companies will first evaluate integration, testing and commercialization opportunities. Its importance lies in the potential pathway from post-quantum technology to regulated infrastructure.

If that pathway develops, Korea could become an important reference market for BTQ as organizations worldwide begin the long transition toward quantum-safe security.

Top Insights

• BTQ and ITCEN PNS will evaluate post-quantum security for financial, government and enterprise systems, connecting quantum technology with established Korean infrastructure.
• ITCEN PNS's reported KCMVP validation strengthens the partnership's regulatory positioning as organizations move PQC from research toward production environments.
• NIST's ML-KEM, ML-DSA and SLH-DSA standards are accelerating enterprise migration planning and increasing demand for quantum-resistant cryptographic infrastructure.
• Hybrid cryptography could help banks and government agencies transition gradually while maintaining compatibility with existing security systems and legacy infrastructure.
• The BTQ-ITCEN relationship could give quantum-security technology greater access to Korea's financial and public-sector markets if testing progresses into commercial deployments.

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Rival Technologies' July 2026 study found that 74% of surveyed Gen Z consumers reacted negatively after realizing that a brand's marketing had been created using AI. Half described their reaction as very negative, while only 8% responded positively.

The behavioral consequences are more significant for marketers.

Half of respondents said they had unfollowed a brand on social media after encountering AI-generated marketing. Another 49% said they had complained to friends, family or online, while 48% had unsubscribed from email or text communications. Most significantly from a revenue perspective, 43% said they had stopped buying from a brand because of its use of AI marketing.

The research was conducted among 901 Gen Z participants in the United States and Canada using Rival's mobile-first, conversational research platform. Because the research comes from Rival's proprietary panels, the findings should be viewed as a snapshot of attitudes among its surveyed audience rather than a universal measure of Gen Z sentiment.

Still, the results point to a potentially important issue for brands scaling generative AI across content operations.

The Problem Is Bigger Than AI-Generated Content

One of the study's more notable findings is that Gen Z's concerns are not primarily aesthetic.

Respondents associated AI-generated marketing with issues such as job losses and uncompensated creative work. That distinction matters because improving the quality of AI-generated imagery, copy or video may not resolve the underlying objection.

For marketing leaders, this creates a communications challenge. A campaign that emphasizes AI-powered efficiency could be interpreted differently depending on the surrounding corporate narrative.

If a company promotes AI as a way to reduce costs while simultaneously announcing workforce reductions, for example, consumers who already associate AI with job displacement may interpret the marketing as evidence of those concerns rather than as a technological innovation.

That puts AI adoption and brand reputation on the same strategic playing field.

Age and Geography Change the Picture

The research also challenges the idea that Gen Z represents a single, uniform audience.

Strong negative reactions increased from 44% among respondents aged 18 to 20 to 54% among those aged 25 to 29. The difference suggests that attitudes toward AI marketing may evolve as consumers move through different stages of education, employment and purchasing power.

There was also a notable difference between Canadian and U.S. respondents. Rival reported that 84% of Canadian participants reacted negatively to AI-generated marketing, compared with 65% in the United States.

The purchasing impact followed a similar pattern: 48% of Canadian respondents said they had stopped buying from a brand over AI marketing, compared with 38% of U.S. respondents.

For multinational marketers, that variation makes a one-size-fits-all AI disclosure or messaging strategy increasingly difficult to justify.

AI Transparency Is Becoming a Brand Question

The findings arrive as generative AI becomes embedded across the modern MarTech stack.

Platforms from Adobe, Salesforce, Google and Microsoft are increasingly integrating AI into content creation, customer engagement, analytics and campaign workflows. For enterprise marketing teams, the technology can reduce production bottlenecks and help personalize communications across thousands or millions of customers.

But automation creates a new layer of brand governance.

Marketing teams now have to consider not only whether AI-generated content is accurate and on-brand, but whether its creation aligns with audience expectations. The question is moving from "Can we automate this?" to "Should we automate this, and how should we explain it?"

That is particularly relevant for creative work. Consumers may tolerate AI for some functional applications while objecting to its use in areas they associate strongly with human creativity.

The Implications for Marketing Teams

The research does not mean brands should abandon AI-generated marketing. Instead, it suggests that AI adoption needs to be accompanied by stronger audience intelligence and clearer governance.

For CMOs, that could mean segmenting audiences by their attitudes toward AI rather than assuming that demographic labels alone predict acceptance.

It could also mean giving consumers greater visibility into where AI is used, maintaining meaningful human involvement in creative development and avoiding messaging that frames human labor as an unnecessary cost.

Rival's Emerging Consumer Index, which tracks Gen Z and millennial attitudes in the U.S. and Canada every two weeks, reflects another emerging requirement: continuous listening.

Consumer sentiment toward AI is still developing rapidly. What audiences reject today may become normalized tomorrow, while new concerns could emerge as AI becomes more deeply embedded in everyday marketing.

Market Landscape

The AI marketing market is moving quickly from experimentation to infrastructure. Generative AI now supports copywriting, image creation, campaign optimization, customer segmentation, personalization, analytics and conversational customer engagement.

That expansion is creating a second challenge alongside implementation: trust.

The Rival study suggests that consumers may judge AI marketing not only on output quality but also on the perceived social consequences of automation. For brands, this introduces reputational considerations into technology decisions that were previously evaluated primarily through efficiency, scale and performance.

The market is therefore moving toward a more nuanced model of AI adoption. Enterprise marketers will need to balance automation with human creativity, cost efficiency with brand values, and personalization with transparency.

The companies best positioned for this transition may not be those that automate the most content, but those that understand where automation adds value without weakening the relationship between brands and consumers.

Strategic Outlook

The Gen Z response to AI marketing is an early warning for marketers rather than a verdict on generative AI itself.

As AI becomes a standard component of enterprise MarTech stacks, brands will need to develop clearer policies around disclosure, human oversight, creative attribution and audience testing. AI-generated content may become commonplace, but that does not guarantee that every audience will accept it equally.

The more important competitive advantage could therefore shift toward AI governance and audience intelligence.

Marketing organizations that continuously test consumer sentiment, understand regional differences and distinguish between acceptable and unacceptable AI use cases will be better positioned to scale automation without turning efficiency gains into brand risk.

For Gen Z in particular, the message from Rival's research is straightforward: how a company uses AI can influence how the company itself is perceived.

Top Insights

• Rival Technologies found 72% of surveyed Gen Z consumers have acted against brands over AI marketing, making AI adoption a growing reputation issue.
• Gen Z concerns center on jobs and creative labor, suggesting brands cannot address AI skepticism solely by improving synthetic content quality.
• Canadian respondents showed stronger resistance than U.S. participants, highlighting the need for localized AI marketing and brand communication strategies.
• Enterprise MarTech platforms increasingly automate content and engagement, increasing the importance of human oversight, transparency and audience sentiment monitoring.
• Continuous consumer research could help marketers identify changing AI attitudes before automation decisions translate into customer churn or brand damage.

Get in touch with our MarTech Experts

The launch reflects a broader shift in financial technology: the boundary between public-market intelligence and private-market research is becoming less distinct.

For decades, private companies were difficult for retail investors and many smaller financial institutions to track systematically. Information about venture funding, secondary transactions and pre-IPO developments could be spread across company announcements, regulatory filings, private databases and specialist research providers.

That is changing as brokerages expand beyond traditional equities and add alternative investments and private-market products to their offerings.

Benzinga's Private Markets Newsfeed API is designed to provide an additional layer of infrastructure. Rather than delivering only structured transaction data, the API turns private-market events into written stories that can be integrated into financial products.

That distinction is important for companies that want to provide news alongside market data without building an editorial operation or data-processing pipeline from scratch.

From Raw Private-Market Signals to News

The API covers several categories of private-market activity.

These include venture capital and growth-stage funding rounds, secondary-market transactions and corporate developments involving companies that remain privately held. Together, those signals can provide a picture of how companies are progressing toward potential public listings and how investors are valuing businesses before an IPO.

The REST-based architecture allows customers to integrate the content into existing applications, alerts and internal systems.

For a brokerage, that could mean adding private-company news to an investment research interface alongside public equity prices and news. A venture capital firm could use the feed to monitor financing activity and potential competitors. Private equity teams could use it as an input for deal sourcing and diligence, while analysts could track companies before they become public.

The underlying value proposition is therefore less about another newsfeed and more about reducing the infrastructure required to make private-market intelligence usable.

Why Pre-IPO Intelligence Is Becoming More Important

The growth of private-market activity has created a data problem.

Companies are often staying private for longer, while large funding rounds can create significant valuations before shares become available on public exchanges. That means an investor interested in a company's trajectory may need to understand its private financing history well before an IPO.

For financial platforms, this creates an opportunity to broaden the definition of market intelligence.

Public-market feeds already provide real-time prices, earnings announcements, analyst research and corporate news. Private-market coverage adds another layer: funding events, investor participation, secondary transactions and strategic developments that can signal how a company is evolving before it reaches the public market.

This is especially relevant to fintech platforms trying to give users a more complete picture of companies across their entire lifecycle.

The API Economy Is Reshaping Financial Data Distribution

Benzinga's approach also fits into a larger movement toward API-driven financial infrastructure.

Instead of requiring financial companies to purchase a complete software platform, APIs allow individual data and content capabilities to be embedded into existing products. Brokerages, wealth platforms, research terminals and internal investment systems can select the feeds they need and incorporate them into their own user experiences.

Companies such as Bloomberg, LSEG and FactSet have historically built extensive financial information ecosystems around data, research and analytics. Newer API-focused providers are increasingly competing on easier integration and specialized datasets.

Benzinga's private-market newsfeed sits within that broader shift.

The differentiation is the combination of private-market signals and editorialized content. Customers receive stories rather than having to transform raw events into readable market intelligence themselves.

The Challenge: Private-Market Data Is Not Public-Market Data

The opportunity also comes with a significant data-quality challenge.

Public markets operate within established disclosure frameworks, creating relatively standardized streams of information. Private companies have considerably more flexibility around what they disclose and when they disclose it.

That means private-market data providers must deal with incomplete information, inconsistent terminology and varying levels of transparency.

For AI-powered and automated financial products, provenance becomes particularly important. Financial institutions need to understand where information originated, when an event occurred and how it was verified before incorporating it into investment research or customer-facing products.

Benzinga's editorial approach could help address part of this problem by turning fragmented signals into structured, readable coverage, but financial institutions will still need their own governance and verification processes for investment decisions.

Market Landscape

Private markets are becoming a larger part of the financial technology ecosystem as investors seek access to companies and assets beyond publicly traded equities.

The expansion is also occurring alongside the growth of alternative investment platforms, private-market exchanges and fintech brokerages. Platforms such as Nasdaq Private Market and Forge Global have helped build infrastructure around private-company transactions, while financial data providers continue expanding their private-company datasets.

The market is increasingly moving toward a model in which investors expect information about a company throughout its lifecycle—not only after an IPO.

For brokerages, this creates a competitive opportunity. A platform that can provide public-market data alongside credible private-company intelligence can potentially offer a more complete research experience.

Strategic Outlook

Benzinga's Private Markets Newsfeed API points toward a broader evolution in financial data infrastructure: private-company intelligence is increasingly becoming a mainstream component of market information.

The next stage could involve combining private-market news with structured transaction data, company financials, alternative data and AI-powered analytics. Financial institutions could use those combined signals to monitor companies from early funding rounds through late-stage financing and eventually an IPO.

For enterprise financial platforms, the value will ultimately depend on data quality, speed, integration and trust.

As more investors look beyond public equities, APIs that make private-market information easier to consume could become an important layer of fintech infrastructure. Benzinga's launch is an indication that private-market intelligence is moving from a specialist research category toward a more integrated part of digital financial products.

Top Insights

• Benzinga's Private Markets Newsfeed API brings funding, secondary transactions and pre-IPO developments into financial platforms through publish-ready news content.
• Brokerages can use private-company intelligence to expand research coverage beyond public equities as investors increasingly seek alternative investment opportunities.
• REST API delivery allows private-market news to integrate directly into brokerage platforms, alerts, research tools and internal investment workflows.
• Private-market data presents greater transparency and verification challenges than public markets, making provenance and editorial validation increasingly important for financial platforms.
• The API launch reflects growing demand for lifecycle-based company intelligence covering businesses from venture funding through potential public-market listings.

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The launch reflects a broader shift in enterprise marketing software: AI is moving from generating individual pieces of content toward handling multi-step workflows.

Kineto's Kinetik For Teams is designed to operate inside tools teams already use, particularly Slack and WhatsApp. According to the company, it can connect with social platforms and marketing systems, allowing marketers to work with campaign and audience data rather than repeatedly copying information into a general-purpose AI assistant.

That distinction matters for influencer marketing, where the work extends well beyond writing a social post. Teams have to identify relevant creators, verify audience quality, negotiate partnerships, prepare briefs, review content and determine whether campaigns generated meaningful business outcomes.

Kinetik attempts to bring those activities into one agent-driven workflow.

Its creator discovery capability can identify potential partners based on audience relevance, reach and brand fit while flagging potentially suspicious engagement. The system can then help prepare personalized outreach and keep track of negotiations.

On the content side, Kinetik can generate briefs and adapt content to a company's brand voice. Its stated use cases extend from SEO-oriented blog content and LinkedIn or X posts to visual content. The platform also analyzes creator and social content to identify topics and formats that appear to be performing well.

The company says Kinetik can connect with analytics platforms including Google Analytics 4, Amplitude and Meta Ads, providing campaign reporting and alerts around performance. It also monitors competitors, social conversations and emerging topics across platforms including X, Instagram and TikTok.

That combination is important because creator marketing increasingly sits between several traditionally separate disciplines: social media management, content marketing, paid media, SEO, audience research and marketing analytics.

From Content Generation to Marketing Execution

Kinetik's positioning also highlights a growing divide between generic generative AI and specialized AI agents.

A general-purpose model such as those offered by OpenAI, Google or Anthropic can produce campaign ideas or outreach copy, but enterprise teams still have to supply context, connect data sources and coordinate the resulting tasks. Marketing platforms from Salesforce and Adobe have taken a different route by embedding AI into broader customer and campaign infrastructure.

Kineto is pursuing a narrower approach. Instead of attempting to become an entire marketing cloud, Kinetik is focused on acting as an operational marketing teammate with access to the systems and social channels a team already uses.

The company says its agent can retain brand context and operate across connected services without requiring teams to repeatedly write prompts or provide background information.

That could be particularly relevant for smaller marketing organizations. Enterprise brands can dedicate specialists to influencer relations, social analytics, content operations and campaign management. Smaller teams often cannot.

The challenge, however, will be proving that automation can maintain the human judgment required in creator partnerships. Brand suitability, audience authenticity, contractual terms, disclosure requirements and creator relationships cannot always be reduced to engagement scores.

Creator Marketing Is Becoming Enterprise Infrastructure

The market opportunity is substantial. IAB projected U.S. creator advertising spend would reach $37 billion in 2025, representing 26% year-over-year growth. The organization also found that 48% of creator ad buyers considered creators a "must buy," while identifying the right creators and measuring outcomes remained major challenges.

IAB's 2026 outlook shows the broader advertising market moving in the same direction. U.S. social media advertising is forecast to grow 14.6% in 2026, while marketers increasingly prioritize AI and agentic AI for campaign planning and optimization.

For marketing leaders, this creates a paradox. Spending is increasing, but scaling creator programs can introduce more operational complexity rather than less.

An AI agent that handles discovery, outreach, content development and measurement could therefore serve as an automation layer between marketing strategy and execution.

Kinetik's approach also reflects a larger trend toward conversational interfaces for enterprise software. Instead of opening another dashboard, marketers can issue a task within Slack or WhatsApp and receive research, recommendations or campaign outputs through the same workflow.

The Competitive Question

Kinetik enters a market that already includes influencer marketing platforms, social listening tools, creator marketplaces and increasingly AI-enabled marketing suites.

Its differentiation is less about offering another creator database and more about combining creator intelligence with execution. The company is effectively betting that marketers want an agent capable of moving from "find creators" to "contact them," "develop the campaign," and eventually "measure what happened."

That is a more ambitious proposition than AI-assisted copywriting, but it also creates higher expectations around accuracy, data access and governance.

For larger organizations, integration with existing MarTech infrastructure will be critical. Marketing teams already operating Salesforce, Adobe, Google Analytics, Meta and other systems are unlikely to replace established platforms simply for an AI agent. The more realistic opportunity is for Kinetik to function as an orchestration layer across them.

Market Landscape

Creator marketing is evolving from an experimental social tactic into a measurable media channel. IAB's research says U.S. creator ad spending has more than doubled from $13.9 billion in 2021 to $29.5 billion in 2024, with 2026 spending expected to reach $44 billion.

Yet measurement remains an industry weakness. IAB's 2026 creator measurement research points to fragmented metrics, siloed platforms and inconsistent attribution as barriers to treating creator activity like established media channels.

That makes the infrastructure surrounding influencer marketing increasingly important. The next generation of platforms will likely compete not only on creator discovery, but also on identity resolution, fraud detection, campaign attribution, workflow automation and AI-powered optimization.

Kinetik is entering that transition with an agent-first model. Its success will depend on whether it can turn fragmented social and marketing data into reliable actions without removing the human oversight that creator relationships require.

Strategic Outlook

The more significant implication of Kinetik For Teams may be the direction of marketing software itself. AI agents are increasingly being designed to execute sequences of tasks rather than simply answer questions.

For marketing organizations, that could mean fewer isolated tools and more software that operates across existing systems. A future campaign workflow might begin with a natural-language brief, identify appropriate creators, generate outreach, monitor responses, prepare content and continuously analyze performance.

That does not eliminate marketers. It changes where their time is spent—from coordinating repetitive campaign operations toward strategy, creative judgment, compliance and relationship management.

For smaller teams in particular, that could make sophisticated influencer marketing programs more accessible without requiring a dedicated creator-marketing department.

Top Insights

• Kinetik For Teams brings creator discovery, outreach, content and analytics into Slack and WhatsApp, reducing operational complexity for lean marketing teams.
• IAB forecasts U.S. creator advertising will reach $44 billion in 2026, increasing demand for scalable measurement, verification and campaign infrastructure.
• Kinetik's agent model differs from generic AI by connecting marketing tasks with real social, analytics and campaign data across platforms.
• Enterprise marketers could use specialized AI agents as orchestration layers across existing MarTech systems rather than replacing platforms from Salesforce or Adobe.
• Creator marketing automation will increasingly depend on reliable attribution, brand safety and human oversight as campaigns become larger and more performance-focused.

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Samsonite Group is acquiring digitally native travel and lifestyle brand BÉIS for approximately $210 million, expanding its portfolio while adding a social-first consumer business with a strong e-commerce and creator-marketing presence.

Samsonite Group is betting that its next phase of growth will come from more than traditional luggage. The company has agreed to acquire BÉIS, the travel and lifestyle brand founded by actress and entrepreneur Shay Mitchell, in a deal that would add a digitally native business to Samsonite's global portfolio.

The transaction values BÉIS at approximately $210 million on a cash-free, debt-free basis. Samsonite Group will acquire 85% of the company's equity for $178.5 million, using cash on hand and available borrowing capacity under its revolving credit facility.

The deal is expected to close in the fourth quarter of 2026, subject to regulatory approvals and customary closing conditions.

Founded in 2018 and incubated by Beach House Group, BÉIS has built its business around luggage, lifestyle bags and travel products while leaning heavily on social media, creator partnerships, brand collaborations and direct-to-consumer e-commerce.

That digital-first model is a significant part of the strategic rationale for Samsonite.

BÉIS has more than 1.4 million Instagram followers and over 619,000 followers on TikTok. The brand generated approximately $210 million in revenue in 2025 and is described as profitable, giving Samsonite access to a younger consumer audience and a business model that has developed largely outside traditional luggage retail.

About half of BÉIS' sales come from lifestyle bags, a category that broadens Samsonite Group's exposure beyond its established travel luggage business.

The acquisition therefore represents more than a portfolio expansion. It gives Samsonite an opportunity to bring the infrastructure of a global luggage company together with the customer engagement model of a digitally native lifestyle brand.

For BÉIS, the transaction provides access to Samsonite's international distribution network, sourcing capabilities, logistics infrastructure and product-development resources.

The challenge will be preserving the characteristics that made BÉIS successful while introducing the operational scale of a much larger parent company.

Samsonite says BÉIS will continue operating as a standalone brand after the acquisition, with Adeela Hussain Johnson remaining CEO and the existing management team continuing to lead the business.

Mitchell will retain a 15% ownership stake in BÉIS after closing. She is also expected to continue guiding the brand's creative and product direction as Founder and Head of Creative and Design.

That structure is notable because founder involvement can be important for consumer brands whose identity is closely tied to storytelling, personality and community.

The transaction also reflects a broader shift in consumer marketing. Digitally native brands have increasingly used social platforms, creators and community-driven content to build awareness without relying exclusively on traditional retail distribution.

BÉIS' model illustrates how those channels can become part of the commercial infrastructure rather than simply serving as promotional outlets. Its Instagram and TikTok audiences provide owned brand communities, while creator collaborations can extend product discovery to highly targeted consumer groups.

For Samsonite, the acquisition creates an opportunity to apply its global operating capabilities to that digital ecosystem.

The company can potentially introduce BÉIS products to new geographic markets, expand distribution and use its sourcing and logistics scale to support continued growth. At the same time, BÉIS could give Samsonite additional insight into younger consumers and lifestyle-oriented purchasing behavior.

This type of portfolio strategy has become increasingly common across consumer industries as established companies seek digitally native brands with strong communities and differentiated positioning.

The transaction also comes as the distinction between travel products, fashion accessories and lifestyle brands continues to blur. Consumers increasingly buy luggage and bags not only for utility but also as expressions of personal style, particularly through social commerce and creator-led discovery.

BÉIS is positioned directly within that intersection.

Kyle Gendreau, CEO of Samsonite Group, said the acquisition aligns with the company's priorities around consumer-centric brands, digital capabilities, multichannel growth and lifestyle bags.

For BÉIS, the deal changes the company's scale without immediately changing its operating identity.

Adeela Hussain Johnson said the brand's combination of product design and community provides a foundation for its next phase, while Samsonite's global platform could help it reach additional consumers.

From a marketing technology perspective, the acquisition also highlights the increasing value of the digital infrastructure behind consumer brands. Social media audiences, e-commerce operations, creator relationships and customer engagement systems can become strategic assets when established companies evaluate digitally native acquisitions.

The key question for Samsonite will be whether it can scale BÉIS without diluting the digital-native characteristics that helped create its growth.

If the integration succeeds, the acquisition could give Samsonite a stronger position in lifestyle bags while adding a more sophisticated social and e-commerce playbook to its global consumer portfolio.

Market Landscape

The acquisition sits within a broader consumer-brand market where established companies are seeking digitally native businesses with strong communities, direct-to-consumer capabilities and younger customer bases.

Social platforms such as Instagram and TikTok have changed how consumer products are discovered, while creator marketing has become an important bridge between brand awareness and purchase consideration.

For traditional companies, acquiring a digitally native brand can provide faster access to these capabilities than building them internally. The risk is that operational integration can weaken the brand's authenticity or slow the experimentation that made the business successful.

Samsonite's decision to maintain BÉIS as a standalone brand suggests the company intends to preserve that independence while using its global infrastructure to support expansion.

Strategic Outlook

Samsonite's BÉIS acquisition points toward a consumer-brand strategy increasingly built around complementary capabilities rather than simple product overlap.

Samsonite brings international distribution, sourcing, logistics and established travel expertise. BÉIS brings a younger audience, lifestyle positioning, social reach and a digital-first customer acquisition model.

The success of the transaction will depend on how effectively those capabilities reinforce each other. If Samsonite can expand BÉIS internationally without compromising its identity, the deal could become a blueprint for using global scale to accelerate digitally native consumer brands.

Top Insights

• Samsonite Group will acquire 85% of BÉIS for $178.5 million, expanding its lifestyle portfolio and strengthening exposure to digitally native travel consumers.

• BÉIS generated approximately $210 million in 2025 revenue, giving Samsonite a profitable digital-first brand with substantial social and e-commerce capabilities.

• More than half of BÉIS' sales come from travel-related products, while lifestyle bags represent about 50%, broadening Samsonite's category exposure.

• Shay Mitchell will retain a 15% stake and continue creative leadership, helping preserve the founder-driven identity behind BÉIS' social-first growth strategy.

• Samsonite plans to combine BÉIS' digital marketing model with global distribution, sourcing and logistics capabilities to accelerate international consumer growth.

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