RAD Amplify has expanded its collaboration across the Omnicom network for a third consecutive year, signaling continued demand for AI-powered creator marketing strategies built on live audience intelligence. The latest phase of the relationship includes work with Ketchum, where the company is helping integrate audience data into creator planning and campaign execution earlier in the process.

RAD Amplify is deepening its relationship with Omnicom agencies as holding companies increasingly seek data-driven ways to improve creator marketing performance.

The company, part of RAD Intel, announced an expanded collaboration across the Omnicom network for a third straight year. Most recently, that work has included Ketchum, where RAD Amplify is being used to bring audience intelligence into creator strategy before campaigns launch.

The move highlights a broader shift in influencer and creator marketing: brands are moving away from static audience personas and follower-count metrics toward real-time behavioral insight.

Why This Matters

Creator marketing has become one of the fastest-growing segments of digital media, but many enterprise campaigns still rely on outdated planning models. Brands often choose creators based on demographics, historical performance, or broad audience categories rather than current consumer sentiment and emerging cultural signals.

That creates risk.

Audience preferences can change quickly across platforms such as TikTok, Instagram, YouTube, Reddit, and search ecosystems. A creator who fit a campaign brief weeks ago may no longer be the best match by launch day.

RAD Amplify is positioning itself as a solution to that lag.

Its platform analyzes language and engagement behavior across social, search, and digital environments, then converts those signals into strategic recommendations. The company says its proprietary RAD Score helps identify how audiences think, respond, and engage in real time.

That insight can be used to guide creator selection, messaging, and creative direction.

Omnicom’s Interest in Integrated Creator Intelligence

For agency networks such as Omnicom, creator marketing is becoming a more strategic discipline rather than a niche social activation channel.

Large clients increasingly want creator campaigns connected to broader brand strategy, PR, commerce, paid media, and measurement systems. That means agencies need tools that bridge strategy and execution rather than operate as isolated influencer programs.

Ketchum Chief Innovation Officer Rob Bernstein said clients are asking for greater connectivity across strategy, data, and execution. That reflects a common enterprise challenge: marketing teams often run creators, media, analytics, and communications in separate silos.

Platforms like RAD Amplify aim to create a shared operating view of audience behavior across those teams.

Language as a Predictive Signal

One of the more interesting elements of RAD Amplify’s positioning is the idea that “language is the new behavior.”

That thesis suggests what people say online — comments, searches, reactions, and conversational trends — may reveal intent earlier than traditional campaign metrics such as clicks or conversions.

If accurate, that could be valuable for brands trying to respond faster to shifts in consumer mood, category demand, or cultural relevance.

For example, spikes in search phrasing or sentiment around wellness, sustainability, or pricing concerns may help marketers refine creator briefs before assets are produced.

This mirrors a wider movement across martech where conversational signals, first-party data, and social listening are increasingly used for predictive planning.

Why Holding Companies Are Investing

The world’s largest agency holding companies face pressure from multiple sides: clients want measurable ROI, creators expect faster workflows, and platforms keep changing their algorithms.

AI-driven audience intelligence offers a possible efficiency layer.

Rather than manually researching communities or relying on post-campaign reporting, agencies can use real-time signals to plan smarter upfront. That can improve creator fit, reduce wasted spend, and increase campaign relevance.

According to Statista, influencer marketing budgets continue to rise globally, while marketers are demanding stronger attribution and brand safety controls. Tools that combine strategy, intelligence, and execution are likely to benefit from that trend.

What It Means for Brands

For enterprise brands, the practical value lies in reducing guesswork.

Instead of relying only on broad personas such as “Gen Z beauty fans” or “millennial parents,” teams can understand how those audiences are talking now, what language resonates, and which creators align authentically with current sentiment.

That can lead to sharper briefs, stronger content resonance, and faster optimization.

For agencies, it may also help protect margins by reducing inefficient creator selection cycles and disconnected planning processes.

Bigger Industry Signal

RAD Amplify’s third-year expansion with Omnicom suggests creator marketing is maturing into a data infrastructure category.

The next phase of competition may not be about who has the largest creator roster. It may be about who best understands audience behavior before campaigns go live.

If that proves true, AI-powered audience intelligence could become as essential to creator strategy as programmatic data became to media buying.

Market Landscape

Creator marketing platforms are evolving beyond influencer marketplaces into intelligence-led martech systems. Competitors include CreatorIQ, Sprout Social, Captiv8, Aspire, and agency-owned platforms. At the same time, holding companies such as Omnicom, WPP, and Publicis are integrating creator programs into broader commerce, PR, and performance media operations.

Top Insights

• RAD Amplify expanded its Omnicom collaboration for a third year, reflecting sustained enterprise demand.
• New work with Ketchum focuses on using audience intelligence earlier in creator campaign planning.
• The company’s RAD Score uses live language and engagement signals to guide decisions.
• Agencies want tighter integration between creator strategy, analytics, and execution.
• Creator marketing is shifting from influencer lists to real-time audience behavior models.

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Microsoft, Postel, and Audiencerate have launched a new data and AI-powered platform aimed at helping Italian small and midsize businesses modernize customer engagement. The solution combines Microsoft cloud and AI tools, Postel’s omnichannel communications network, and Audiencerate’s data intelligence capabilities to give SMEs access to enterprise-grade marketing technology.

Microsoft is expanding its push into Europe’s small business digital transformation market through a new collaboration with Postel, a company within the Poste Italiane Group, and marketing technology provider Audiencerate.

The three companies announced an integrated platform designed to help Italian SMEs manage customer relationships using AI, automation, and data-driven marketing tools that have traditionally been available mainly to larger enterprises.

The launch reflects a broader market trend: AI adoption is moving beyond global corporations and into the mid-market, where smaller businesses often lack the budgets or internal teams required to deploy complex customer data and marketing systems.

Why Italian SMEs Matter

Italy’s economy is heavily driven by SMEs, many of which operate in manufacturing, retail, tourism, logistics, and family-owned service sectors. While these businesses form the backbone of the national economy, they have historically lagged larger enterprises in digital maturity.

That creates a major opportunity for technology vendors.

Cloud-based AI platforms can lower barriers by replacing expensive custom infrastructure with subscription tools that are easier to deploy and scale.

Microsoft and its partners appear to be targeting that opportunity directly.

What the Platform Does

The new solution combines three core capabilities:

• Postel’s omnichannel communications infrastructure, spanning physical and digital outreach
• Audiencerate’s customer data intelligence and activation tools
• Microsoft Azure cloud and AI services

Together, the platform is designed to help SMEs centralize and activate first-party data across the full customer lifecycle.

That includes segmenting customers, automating campaigns, orchestrating communication across channels, and generating market insights based on competitive and sector trends.

For smaller businesses, this can mean moving from fragmented spreadsheets and manual email tools to coordinated lifecycle marketing systems.

Bringing Enterprise Martech to the Mid-Market

One of the more significant aspects of the launch is democratization.

Large enterprises have long used customer data platforms, predictive analytics, and marketing automation tools from vendors such as Salesforce, Adobe, HubSpot, and Oracle. Many SMEs, however, have been priced out of these ecosystems or lacked implementation resources.

By embedding Azure AI into Audiencerate’s infrastructure, the partners say they can make advanced segmentation, market intelligence, and automation more accessible.

That matters because smaller companies face many of the same customer acquisition challenges as enterprises: rising ad costs, changing buyer expectations, and increasing pressure to personalize engagement.

The difference is scale and resources.

AI as a Competitive Equalizer

Microsoft Italy’s leadership framed the partnership around accessibility, arguing that cloud and AI can help smaller organizations operate more intelligently and regain competitiveness.

That aligns with wider market research. According to IDC, European SMEs are increasing investment in cloud services and automation to improve productivity and resilience. Meanwhile, McKinsey & Company has noted that AI adoption among mid-sized firms can generate outsized gains when tied to sales, service, and operational efficiency.

For Italian SMEs, practical use cases may include:

• Automated re-engagement campaigns for dormant customers
• Dynamic segmentation based on purchase behavior
• Real-time trend monitoring in local markets
• Multichannel communication across email, SMS, print, and digital touchpoints
• Better retention and loyalty programs

Why Postel’s Role Is Strategic

Postel brings an important local advantage: trusted communication infrastructure.

As part of the Poste Italiane ecosystem, it has deep roots in physical and digital communications. That may be particularly relevant in Italy, where many SMEs still rely on hybrid engagement models combining traditional direct outreach with newer digital channels.

This hybrid capability could differentiate the platform from purely digital SaaS competitors.

What Comes Next

The companies said the platform already includes customer segmentation, market intelligence, and connectors to Postel channels. Upcoming additions include a marketing automation module and new communication channels.

They also signaled continued innovation through Microsoft AI capabilities and Audiencerate’s broader AdTech and MarTech partnerships.

That suggests the platform could evolve into a full-stack SME growth engine rather than a narrow CRM tool.

Bigger Industry Implication

The launch points to a larger shift in B2B software markets: AI-enabled enterprise functionality is cascading downward into the SME segment.

That creates new competition not only among global cloud vendors, but also among regional operators that combine local trust, data services, and vertical expertise.

For Italian SMEs, the question is no longer whether advanced customer intelligence tools are available.

It is whether they can adopt them quickly enough to compete.

Market Landscape

The SME martech market is becoming a key battleground for Microsoft, Google, Salesforce, HubSpot, Zoho, and regional providers. Demand is rising for affordable platforms that combine CRM, automation, analytics, and AI. In Europe, local trust, regulatory compliance, and multilingual support remain important buying factors alongside product capability.

Top Insights

• Microsoft, Postel, and Audiencerate launched an AI marketing platform for Italian SMEs.
• The solution combines cloud AI, customer data intelligence, and omnichannel communications.
• Smaller businesses gain access to tools once reserved for large enterprises.
• Upcoming features include marketing automation and expanded communication channels.
• The move reflects growing SME demand for AI-driven competitiveness in Europe.

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BlueFocus is making a larger bet on artificial intelligence than many traditional agency groups. In its 2025 annual report, the company reported more than $10 billion in revenue, over $546 million in AI-driven revenue, and token usage exceeding one trillion. CEO Fei Pan says those figures reflect a deeper shift: AI is no longer a productivity layer, but the foundation for rebuilding how modern marketing businesses operate.

For years, marketing services firms have positioned AI as a way to automate repetitive work, improve campaign efficiency, or accelerate content production. BlueFocus is now presenting a more ambitious model. Rather than adding AI tools around an existing business structure, the company says it is redesigning operations, decision-making systems, and revenue models around AI-native workflows.

According to the company’s 2025 annual report, BlueFocus generated USD 10.07 billion in total revenue, with USD 546.05 million classified as AI-driven revenue. That means AI-led business still represents only 5.42% of total revenue, while the company’s core engine remains global outbound media buying, which generated USD 8.28 billion, or more than 82% of company revenue.

Those numbers matter because they show a company in transition rather than one claiming instant transformation.

Pan said BlueFocus has moved beyond using AI simply to reduce labor costs. Instead, the company is pursuing what it calls an “AI Native” operating model where intelligent systems participate in planning, execution, optimization, and performance feedback loops.

That approach mirrors a broader enterprise software trend. Major vendors such as Microsoft, Salesforce, Adobe, and Google are all repositioning products around autonomous AI agents that can complete workflows instead of responding to prompts. BlueFocus appears to be applying that same philosophy directly inside a services business.

The company says AI is already used across campaign-critical functions including:

• Social media insight generation
• Creator and influencer analysis
• Advertising risk control
• Winning creative extraction
• Intelligent budget optimization
• Video content production

BlueFocus reported that its Blue AI platform completed 146 million agent-to-agent collaborative tasks in 2025. It also claimed that across scenarios such as strategy creation, budget allocation, and delivery decisions, AI outperformed human teams without intervention in 85% of relevant use cases.

If accurate at scale, that would be significant for enterprise marketers. It suggests AI systems may soon manage performance media operations, creative testing, and budget shifts faster than traditional agency teams.

For CMOs and growth leaders, the practical takeaway is clear: the next stage of marketing automation may not be email workflows or CRM triggers, but autonomous campaign operations.

Gartner has forecast that generative AI will reshape multiple business functions, while McKinsey & Company estimates AI could add trillions of dollars in annual economic value across industries. Marketing remains one of the earliest adoption zones because media buying, personalization, and analytics generate large volumes of structured data.

BlueFocus also appears to be linking AI growth with international expansion. The company said more than 80% of revenue and more than half of profit now come from global outbound business. Its strategic media partnerships reportedly include Meta, Google, TikTok for Business, alongside expanding ties with AppLovin, Uber Ads, and Netflix.

That international footprint may be where AI delivers the fastest returns. Cross-border advertising requires localization, multilingual content, regional audience insights, and constant optimization across fragmented platforms. These are precisely the kinds of repetitive, data-heavy workflows AI systems are well suited to handle.

BlueFocus currently operates seven overseas offices and expects to exceed ten in 2026, with Southeast Asia markets including Singapore, Vietnam, Thailand, and Indonesia highlighted as growth centers.

The competitive question now is whether holding companies, consultancies, and enterprise MarTech vendors can move as quickly.

Traditional agency groups often rely on labor-based billing models, where automation can reduce billable hours. SaaS platforms monetize software subscriptions but may lack managed execution capabilities. BlueFocus sits in an interesting middle ground: it combines service delivery scale with platform economics if AI-driven automation expands margins.

That could become a model other large marketing organizations attempt to replicate.

Still, investors will likely focus on one core metric: whether AI revenue grows from a promising side business into a meaningful share of company earnings.

For now, BlueFocus has done something notable in the crowded AI market. It has offered measurable operating indicators—token usage, AI revenue, agent task volume, and automation performance—rather than relying only on branding language.

Whether that leads to a structurally different marketing company remains unproven. But the direction is becoming clearer: the future of marketing operations may belong to firms that build around AI from the inside out.

Market Landscape

BlueFocus reflects a wider shift across MarTech and AdTech markets where AI is moving from content generation into workflow orchestration. Competitors across agency services, customer data platforms, and marketing automation software are racing to launch AI copilots and autonomous agents. The next battleground will likely center on who can combine data access, execution scale, and measurable business outcomes fastest.

Top Insights

•  BlueFocus reported $10.07 billion revenue, showing AI transformation is happening inside a large-scale marketing enterprise rather than a startup environment.
• AI-driven revenue reached $546 million, signaling new monetization models built on automation and lower human dependency.
• Blue AI completed 146 million collaborative tasks, suggesting agent-based marketing operations are moving into production environments.
• Global outbound media buying still drives 82% of revenue, meaning legacy business scale remains essential during AI transition.
• Cross-border advertising may become an early winner for AI due to localization, multilingual execution, and platform complexity.

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Assemble is expanding its executive communities, summit events, AI-enabled content offerings, and leadership team as demand rises for peer-driven decision support. The company says senior leaders are facing a new challenge: not a shortage of data, but too much information and too little actionable insight

Executives today have access to more dashboards, market reports, analyst notes, software alerts, and AI-generated recommendations than ever before. Yet many leadership teams still struggle to make timely, confident decisions.

That tension is creating a new category of enterprise demand: decision intelligence grounded not only in analytics, but in trusted peer experience.

Assemble, a company focused on what it calls peer intelligence, is positioning itself to capture that opportunity. The business announced a broad expansion across member communities, executive events, content products, and senior leadership as it scales operations in 2026.

The company also reported 38% year-over-year revenue growth in Q1 2026, suggesting growing enterprise appetite for curated leadership networks and practical market insight.

The timing reflects a wider shift in B2B markets. Traditional research sources remain valuable, but many executives increasingly want faster answers tied to real-world implementation. In volatile markets shaped by AI disruption, economic pressure, and changing buyer behavior, decision-makers often seek to understand what peers are doing now—not what worked last year.

That trend has helped fuel demand for communities, advisory networks, private executive forums, and benchmarking platforms.

From Information Overload to Decision Support

Assemble’s thesis is straightforward: leaders do not primarily need more information. They need higher-confidence decisions.

That message lands at a moment when generative AI tools from Microsoft, Google, Salesforce, and Adobe are flooding enterprise workflows with summaries, forecasts, recommendations, and content outputs.

While those tools can accelerate productivity, they also create a new management challenge: separating signal from noise.

Assemble’s answer is peer intelligence—structured access to senior operators sharing market-tested lessons, buying insights, and execution strategies.

This model differs from traditional analyst research firms or software dashboards. Instead of top-down reports, peer intelligence relies on practitioner knowledge from executives actively managing similar challenges.

Community Expansion Targets New Leadership Functions

Assemble said it launched three new boards over the past year:

• AEO Board
• Manufacturing Board
• Learning & Development Board

The move suggests the company is broadening beyond classic HR and leadership circles into emerging growth categories.

The AEO Board is particularly notable. Answer Engine Optimization (AEO) has become an important topic as brands adapt content strategies for AI systems such as ChatGPT, Google Gemini, and Perplexity. Executive communities focused on AEO indicate how quickly AI-driven search behavior is entering boardroom planning.

Manufacturing and L&D communities point to another shift: digital transformation is no longer confined to marketing or IT teams. Operations leaders, workforce leaders, and supply chain executives increasingly need strategic peer networks as automation changes core business functions.

Executive Events Become a Growth Channel

Assemble is also expanding its summit portfolio with new events including:

• North American Procurement Executive Summit
• North American Finance Executive Summit
• North American Learning Executive Summit
• North American Marketing Leadership Summit
• Additional fall edition of the North American HR Executive Summit

That strategy mirrors a wider B2B media trend. In-person executive gatherings have become one of the fastest-growing monetization channels for enterprise communities and information businesses.

Gartner and Forrester have long used events as premium engagement channels. Newer platforms are now combining memberships, events, and digital communities into recurring revenue ecosystems.

For Assemble, summits likely serve three purposes: lead generation, member retention, and premium sponsorship revenue.

AI-Enabled Content Moves Beyond Reports

The company said it is investing in AI-enabled benchmarking, best practices, and buying guidance.

That matters because enterprise content is changing rapidly. Static whitepapers and annual trend reports are giving way to dynamic, continuously updated intelligence products. Buyers increasingly expect real-time peer benchmarks, vendor comparisons, and implementation guidance.

IDC has repeatedly noted that enterprise buyers want faster access to decision-ready intelligence rather than large research libraries. Assemble appears to be aligning with that demand.

Leadership Hires Signal Scale Ambitions

Assemble also announced senior leadership expansion across content, finance, and product strategy.

Pete Buer joins with deep experience from CEB, now part of Gartner. He will oversee content strategy and event production.

Joyce Liu brings experience from CEB and Politico, including acquisition and growth-stage finance expertise.

Katrina Tofflemire was promoted to lead platform strategy, operations, and member experience.

Together, the hires suggest Assemble is evolving from a niche executive network into a scaled information platform.

Why It Matters for Enterprise Leaders

For enterprise decision-makers, Assemble’s growth highlights a broader market reality: trusted peer context is becoming a competitive asset.

Analytics tools can show what happened. AI tools can predict what might happen. Peer intelligence can explain what is working in practice.

As companies navigate AI adoption, budget scrutiny, hiring changes, and vendor sprawl, that combination may become increasingly valuable.

Market Landscape

Peer intelligence sits at the intersection of executive communities, research subscriptions, B2B events, and AI-powered advisory tools. Competitors include analyst firms, membership networks, private communities, and enterprise media brands. The next wave may favor platforms that combine human expertise with AI searchability and real-time benchmarking.

Top Insights

•  Assemble reported 38% Q1 revenue growth, signaling strong enterprise demand for decision support built around executive peer networks.
• New boards in AEO, manufacturing, and learning show peer intelligence expanding into high-priority business functions.
• Executive summits create recurring revenue through memberships, sponsorships, and premium relationship-driven experiences.
• AI-enabled benchmarking suggests static research is being replaced by real-time decision intelligence products.
• Leadership hires from Gartner-era CEB talent indicate ambitions to scale into a larger enterprise insights platform.

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TeamViewer is expanding its enterprise IT automation strategy with new AI-driven scripting capabilities for Tia. Announced at the Gartner Digital Workplace Summit 2026 in London, the update allows Tia to turn previously resolved support incidents into reusable automations, a move that pushes TeamViewer closer to its vision of Autonomous Endpoint Management (AEM).

Enterprise IT teams have long struggled with a recurring problem: the same device issues appear repeatedly, technicians resolve them manually, and valuable remediation knowledge disappears once the ticket closes.

TeamViewer is attempting to break that cycle.

The company announced new AI scripting features for Tia, its TeamViewer Intelligent Agent, designed to learn from historical support sessions and convert successful fixes into ready-to-review automation scripts. The result is a system that can help IT departments standardize proven solutions, reduce repetitive help desk workloads, and respond faster to common endpoint problems.

The launch is significant because it moves TeamViewer beyond remote support software and deeper into autonomous IT operations—a fast-growing category that blends endpoint management, automation, observability, and AI assistance.

How Tia’s New AI Automation Works

According to TeamViewer, the new capability operates in two connected phases.

First, Tia analyzes historical support interactions and AI-generated session summaries to identify remediation steps that previously solved similar issues. Instead of relying solely on generic AI troubleshooting logic, the agent uses an organization’s own support history and environment context.

Second, once a support case is resolved, IT teams can instruct Tia to generate a script based on those remediation steps. Administrators can then review, refine, and deploy the automation across selected devices or groups.

That workflow turns tribal support knowledge into operational assets.

In practical terms, if a company repeatedly fixes printer driver conflicts, VPN failures, software crashes, or misconfigured system settings, Tia can help transform those repetitive manual fixes into repeatable automations.

Why It Matters for Enterprise IT Teams

For CIOs and IT operations leaders, repetitive endpoint support remains expensive and difficult to scale.

Gartner has consistently highlighted automation, employee digital experience, and endpoint resilience as top priorities for digital workplace leaders. Meanwhile, IDC has noted that support teams face growing device complexity as hybrid work expands across laptops, mobile devices, virtual desktops, and distributed endpoints.

That creates pressure to resolve more tickets without proportionally increasing headcount.

TeamViewer’s message is that every resolved ticket should improve future operations.

Instead of treating incidents as isolated events, Tia turns them into reusable playbooks that can reduce recurrence and shorten resolution times.

For enterprise IT teams, this could mean:

• Lower volume of repeat tickets
• Faster mean time to resolution (MTTR)
• More standardized remediation processes
• Reduced dependence on individual technician memory
• Greater scalability across global device fleets

TeamViewer ONE and the AEM Strategy

The announcement also reveals how TeamViewer is repositioning its broader platform.

Historically known for remote desktop connectivity, TeamViewer has increasingly expanded into digital workplace management through TeamViewer ONE, its unified platform combining remote support, endpoint visibility, AI guidance, and device management.

The company describes its roadmap as progressing through several stages:

1. Secure remote support
2. Real-time endpoint observability
3. AI expert assistance during support sessions
4. Knowledge capture from resolved incidents
5. AI-generated automations
6. Autonomous Endpoint Management

That mirrors a wider market shift where vendors are racing to unify previously separate categories such as Remote Monitoring and Management (RMM), Digital Employee Experience (DEX), endpoint management, and AI copilots.

Competitors in adjacent spaces include Microsoft with Intune and Copilot integrations, NinjaOne, ServiceNow, and VMware offerings.

TeamViewer’s differentiation appears to be grounding automation in real customer support history rather than purely synthetic AI recommendations.

Why Customer Data Matters in AI Support

Many enterprise buyers remain cautious about AI tools that produce generic or unverified actions. In IT environments, incorrect scripts can create outages, security gaps, or configuration drift.

By using previously successful internal fixes as source material, TeamViewer is positioning Tia as safer and more context-aware.

That could be important in regulated sectors such as finance, healthcare, manufacturing, and government where change control matters as much as speed.

It also aligns with a broader AI enterprise trend: domain-specific copilots trained on internal operational data often deliver stronger ROI than general-purpose assistants.

Market Outlook

Autonomous Endpoint Management is likely to become a major battleground in enterprise IT over the next several years.

As device fleets grow and skilled IT labor remains constrained, enterprises want platforms that can detect issues, recommend fixes, deploy remediations, and prevent repeat incidents automatically.

If TeamViewer can convert its remote support footprint into a broader automation platform, it could expand from a mature connectivity brand into a higher-value enterprise operations vendor.

The challenge will be execution. Buyers increasingly want open integrations, measurable ROI, and trustworthy AI controls—not just chatbot features.

Still, this release signals that TeamViewer sees the future of IT support less as screen sharing and more as self-healing digital workplaces.

Market Landscape

Endpoint management is converging with AI operations, observability, and employee experience software. Traditional RMM tools handled monitoring, while DEX platforms measured user friction. The next generation of platforms aims to unify detection, remediation, and automation into autonomous workflows.

Top Insights

•  TeamViewer added AI scripting to Tia, enabling support teams to convert successful fixes into reusable endpoint automations.
• The update advances TeamViewer’s Autonomous Endpoint Management roadmap beyond traditional remote support tools.
• Tia uses customer support history rather than generic AI advice, improving context and operational relevance.
• Enterprises could reduce repeat tickets, improve MTTR, and standardize IT remediation processes at scale.
• Autonomous endpoint operations may become a major growth category across hybrid workplace IT infrastructure.

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OneLayer is expanding its go-to-market strategy with the launch of the Sentry Partner Program, a new channel initiative designed to help systems integrators and service providers deliver Zero Trust security for private LTE and 5G networks. The move comes as enterprises accelerate adoption of private wireless infrastructure but face growing visibility, onboarding, and security gaps that traditional IT tools often fail to address.

Private cellular networks are moving from niche industrial pilots to mainstream enterprise infrastructure. Manufacturers, utilities, logistics operators, campuses, and public sector organizations are increasingly deploying private LTE and 5G networks to support connected devices, operational technology, robotics, and mission-critical communications.

But while connectivity adoption is accelerating, security models have lagged behind.

That gap is where OneLayer is placing its next growth bet.

The company announced the launch of its Sentry Partner Program, a formal channel ecosystem aimed at certifying integrators and managed service providers to deploy Zero Trust network access controls, automated device onboarding, and centralized visibility across private wireless environments.

Founding partners include Burns & McDonnell, Logicalis, World Wide Technology, MCA, STEP CG, and several specialist wireless infrastructure firms.

The announcement reflects a wider reality in enterprise networking: private 5G deployment is becoming easier, but securing thousands of devices across fragmented carrier and on-premise environments remains difficult.

Why Private Cellular Security Has Become a Priority

Unlike traditional corporate networks, private LTE and 5G environments often support mixed fleets of sensors, tablets, cameras, vehicles, handheld devices, and industrial equipment.

Many of those endpoints lack modern security controls or centralized identity management.

Enterprises also increasingly operate across multi-carrier APN environments, where devices connect through multiple public carriers alongside private wireless systems. That can create operational blind spots, inconsistent policy enforcement, and weak asset visibility.

OneLayer’s platform is designed to solve those challenges through:

• Zero Trust network access controls
• Automated SIM provisioning and onboarding
• Device discovery and inventory management
• Unified visibility across carriers and private networks
• Policy enforcement from a centralized console

For enterprises, the appeal is straightforward: secure every connected device, regardless of network origin.

Why the Channel Strategy Matters

Launching a partner program is a strategic move because private wireless buying cycles are heavily influenced by integrators, telecom consultants, managed service providers, and infrastructure specialists.

Unlike mainstream SaaS products, private 5G projects often involve hardware procurement, RF planning, carrier coordination, cybersecurity design, and long deployment timelines.

That means channel partners frequently control customer trust and implementation success.

By formalizing the Sentry Program, OneLayer is attempting to become embedded in that ecosystem rather than selling direct-only.

Partners receive benefits including:

• Sales and technical certifications
• Deal registration incentives
• Market development funds
• Performance bonuses (SPIFs)
• Access to OneLayer Scout for pre-deployment surveys and device inventories

That commercial structure mirrors mature channel programs from enterprise vendors such as Cisco, Palo Alto Networks, and Fortinet, suggesting OneLayer wants to scale through partners rather than build a large direct sales force.

Ecosystem Positioning in a Crowded Market

OneLayer also emphasized interoperability with a broad ecosystem including Ericsson, Nokia, Cisco, HPE Athonet, Druid, Celona, Digi, ServiceNow, and others.

That matters because the private cellular market remains fragmented. Enterprises often combine radio vendors, core software, security stacks, and device management platforms from multiple providers.

Vendors that integrate broadly rather than force rip-and-replace deployments may have an advantage.

Why Zero Trust Is Expanding Beyond IT Networks

Zero Trust security has largely been associated with corporate identity systems, cloud access, and remote workforce protection. But the next phase is expanding into operational environments where connected assets can create physical and financial risk.

Gartner and IDC have both identified industrial IoT and edge security as major enterprise priorities. Utilities, transportation firms, factories, and smart campuses increasingly need policy-based security for machine-connected networks.

That makes private cellular a natural next frontier.

If a compromised tablet, gateway, or field sensor can access critical systems, network segmentation alone may no longer be enough.

Market Outlook

OneLayer’s Sentry Program suggests the company sees partner-led expansion as the fastest route to market share.

As enterprises move from pilot deployments to large-scale production networks, demand will likely shift from connectivity-first buying toward security-first operating models.

That creates room for vendors that can answer three enterprise questions:

1. What devices are on the network?
2. Who should trust them?
3. How can policies be enforced at scale?

OneLayer is betting those questions will define the next stage of private LTE and 5G adoption.

Market Landscape

Private wireless infrastructure is converging with cybersecurity, asset management, and managed services. Network vendors provide connectivity, but enterprise buyers increasingly want full-stack solutions that combine coverage, onboarding, visibility, and Zero Trust controls.

Top Insights

•  OneLayer launched the Sentry Partner Program to scale Zero Trust security for private LTE and 5G enterprise deployments.
• Channel partners will help deliver onboarding, policy enforcement, and visibility across multi-carrier APN environments.
• Founding partners include WWT, Logicalis, Burns & McDonnell, and other enterprise infrastructure specialists.
• Private wireless adoption is shifting from connectivity-led pilots to security-driven production deployments.
• Zero Trust principles are expanding from IT networks into industrial and operational cellular environments.

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Hyland has appointed Tracy Roccasalva as Chief Marketing Officer, signaling a stronger go-to-market push as the enterprise content management (ECM) market shifts toward AI-driven content intelligence. The leadership move comes as software vendors race to reposition traditional content platforms for the next phase of enterprise automation.

The enterprise content management market is entering one of its most significant reset cycles in years.

Once centered on document storage, records compliance, and workflow digitization, ECM platforms are increasingly being recast as intelligence layers for AI systems. Enterprises now want platforms that can not only store content, but understand it, classify it, secure it, and activate it inside automated business processes.

Against that backdrop, Hyland has appointed Tracy Roccasalva as Chief Marketing Officer to lead its global marketing organization and sharpen its category positioning.

The company said Roccasalva will oversee worldwide go-to-market strategy as Hyland accelerates growth around its Content Innovation Cloud, a platform the company markets as AI-native.

Why the Appointment Matters

Executive marketing hires often reflect broader strategic priorities. In Hyland’s case, the move suggests the company sees market education and category creation as central to growth.

The ECM sector has become increasingly competitive as legacy content vendors face pressure from cloud-native challengers, workflow automation platforms, and hyperscale ecosystems from Microsoft, Google, and Adobe.

Meanwhile, enterprise buyers are reassessing how unstructured data—contracts, emails, PDFs, scanned forms, case files, invoices, media assets, and knowledge repositories—can fuel generative AI initiatives.

That creates an opportunity for vendors that can frame content not as archived data, but as strategic business infrastructure.

Hyland’s CEO Jitesh S. Ghai described the company’s ambition as leading the “content-powered Agentic Enterprise” category, language that reflects a broader industry trend toward AI agents executing workflows using enterprise data.

Roccasalva’s Enterprise Software Background

Roccasalva brings more than two decades of enterprise technology marketing experience across several major software and cybersecurity brands.

Her prior roles include leadership positions at:

• Informatica
• VMware
• RSA Security
• FireEye
• Cisco

Most recently, she served in senior marketing leadership at Ping Identity, where she helped guide the company through product transformation and pipeline growth.

That background is relevant because Hyland’s next growth phase likely depends on combining brand repositioning with measurable revenue execution. Modern B2B CMOs are expected to own both narrative and pipeline, especially in crowded enterprise categories.

ECM Is Becoming an AI Category

The bigger story may be what this appointment says about the ECM market itself.

Traditional enterprise content management focused on governance, retention, and process efficiency. The new AI era is changing buyer expectations.

Organizations increasingly want systems that can:

• Extract meaning from documents automatically
• Route content into workflows using AI agents
• Improve customer service with knowledge retrieval
• Automate compliance and classification
• Surface insights from decades of stored records
• Connect content to ERP, CRM, and HR systems

That is why many content vendors are repositioning around intelligent content services, automation, and AI orchestration.

Gartner has previously shifted market language from ECM toward content services platforms, reflecting how enterprise buyers prioritize modular, cloud-connected systems over monolithic archives.

Now, generative AI may accelerate another renaming cycle.

Why Marketing Will Be Critical

Hyland’s challenge is not only product innovation—it is category clarity.

Many enterprise buyers still associate ECM with back-office document management. But AI-era budgets may come from CIO modernization programs, customer experience teams, operations leaders, or line-of-business owners seeking automation gains.

That means marketing must translate technical capability into business outcomes such as faster onboarding, lower service costs, reduced compliance risk, and smarter decision-making.

Roccasalva highlighted that shift directly, saying enterprises are moving from AI experimentation to real execution.

That framing is important. Many software buyers in 2026 are no longer asking whether to use AI. They are asking where ROI can be proven first.

Competitive Landscape

Hyland competes in a broad field that includes legacy ECM vendors, intelligent automation providers, document cloud platforms, and adjacent enterprise suites.

Potential competitive pressure comes from:

• OpenText
• Microsoft SharePoint and Copilot ecosystem
• Box
• Adobe document workflows
• Salesforce workflow integrations

In this environment, differentiated messaging can be as important as feature parity.

Market Outlook

Hyland’s CMO appointment signals the company believes the next battle in enterprise content software will be won through AI positioning, ecosystem relevance, and demand generation discipline.

If enterprises increasingly treat content as fuel for AI agents and workflow automation, vendors with deep repositories of governed enterprise data may hold an advantage.

The challenge will be proving that old content systems can become modern AI infrastructure.

Market Landscape

The ECM market is converging with automation, search, knowledge management, and generative AI. Buyers want platforms that transform content from static storage into active intelligence embedded across enterprise workflows.

Top Insights

•  Hyland appointed Tracy Roccasalva as CMO during a major AI-driven transformation in the ECM market.
• The company is positioning content as the orchestration layer for AI-powered enterprise workflows.
• Roccasalva brings experience from Ping Identity, Informatica, VMware, and Cisco.
• Enterprise content platforms are evolving from archives into intelligence systems for automation.
• Marketing leadership will be key as vendors compete to define the AI-era ECM category.

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pharosIQ has introduced atlasIQ Intelligence at the Forrester B2B Summit North America 2026, positioning buyer intelligence as the next foundation for AI-driven go-to-market execution. The announcement reflects growing pressure on B2B revenue teams to replace broad intent signals with more precise, contact-level buying insights

For years, B2B marketers have relied on intent data to prioritize accounts, route leads, and guide demand generation campaigns. But as buying committees become larger, decision cycles more complex, and AI automation enters revenue operations, many organizations are discovering a core limitation: intent data often reveals interest, not actual buyers.

That challenge is creating demand for a new category of go-to-market intelligence.

pharosIQ announced atlasIQ Intelligence, a data intelligence offering designed to help enterprises identify real buying groups, understand decision formation at the contact level, and activate signals across sales and marketing systems in real time.

The company unveiled the platform during Forrester’s B2B Summit North America 2026 in Phoenix, one of the largest annual gatherings for B2B marketing, revenue, and product leaders.

Why Intent Data Is Losing Ground

Traditional intent data has become a staple of account-based marketing and pipeline acceleration strategies. Vendors typically infer demand using content consumption, keyword activity, ad engagement, or third-party browsing behavior.

That model helped fuel account-based marketing growth over the past decade.

But modern GTM teams increasingly need deeper answers:

• Who is actually involved in the purchase?
• Which contacts are influencing decisions?
• How advanced is the buying process?
• Which signals are meaningful versus noisy?
• When should sales engage?

Intent platforms can surface “in-market” accounts, but often struggle to identify real buying committees with enough precision for autonomous workflows or AI agents.

That gap is becoming more visible as revenue teams try to automate outreach, prioritization, and pipeline forecasting.

What atlasIQ Intelligence Does

pharosIQ says atlasIQ Intelligence is built to move from account-level intent toward decision-ready buyer intelligence.

According to the company, the platform combines:

• First-party engagement data
• Contact-level buyer activity signals
• AI-driven contextual modeling
• Continuous signal validation
• Real-time activation across GTM systems

The stated goal is to help companies identify active buying groups rather than anonymous account interest.

That distinction matters because B2B purchases often involve multiple stakeholders across finance, procurement, IT, security, and business units. Knowing an account is researching a category is useful. Knowing which five people are driving the decision is far more valuable.

Why It Matters in the AI Era

The timing of the launch reflects a broader market shift toward agentic GTM systems—AI-powered workflows that can score demand, personalize outreach, recommend next actions, and optimize pipeline programs with less manual intervention.

However, AI systems are only as strong as the data feeding them.

If models rely on weak or outdated intent signals, automation can amplify inefficiency rather than improve outcomes.

That is why many revenue leaders are refocusing on data quality, identity resolution, and first-party engagement sources.

Forrester and Gartner have both emphasized that B2B buying journeys are increasingly nonlinear, involving digital self-education, anonymous research, and consensus-driven decision making.

In that environment, static lead scoring and shallow account signals may no longer be enough.

Competitive Landscape

The buyer intelligence market overlaps with several established categories:

• Intent data platforms
• Account-based marketing software
• Revenue intelligence systems
• Sales engagement platforms
• Customer data platforms

Potential competitors or adjacent vendors include 6sense, Demandbase, ZoomInfo, Salesforce, and HubSpot.

pharosIQ appears to be differentiating by emphasizing first-party buyer intelligence and contact-level decision visibility rather than broad account scoring.

If successful, that could resonate with enterprise teams frustrated by inflated intent volumes that fail to convert into pipeline.

Growth Signals and Market Timing

The company also said it achieved double-digit organic year-over-year revenue growth in 2025, with continued momentum in 2026.

That claim is notable because many GTM technology vendors have relied on acquisitions for expansion. Organic growth may indicate stronger product-market fit if sustained.

The macro environment also favors measurable pipeline tools. CMOs and CROs are under pressure to prove ROI, shorten sales cycles, and align marketing spend directly with revenue outcomes.

Any platform that can improve buying group identification and reduce wasted targeting budgets could attract attention.

Market Outlook

The bigger story is not one product launch—it is the shift in how B2B demand generation is measured.

The next generation of GTM systems may care less about which company clicked and more about which humans are actually deciding.

That transition could redefine lead generation, ABM, sales prioritization, and pipeline forecasting over the next several years.

If that happens, buyer intelligence may become as important to revenue teams as CRM systems were in the previous era.

Market Landscape

B2B go-to-market technology is moving from account-level targeting toward identity-rich, AI-ready buyer intelligence. As automation expands, enterprises need data that explains not only where demand exists, but who is driving it and when to act.

Top Insights

•  pharosIQ launched atlasIQ Intelligence to help GTM teams identify real buyers rather than broad account intent signals.
• The platform uses first-party engagement data, AI modeling, and continuous validation for real-time execution.
• Intent data remains useful, but many teams now want contact-level buying committee visibility.
• Buyer intelligence is becoming critical for agentic sales and marketing automation systems.
• The shift could reshape ABM, lead generation, and pipeline forecasting categories.

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