Chromaway AB has introduced Atbash, a new agentic governance layer built on the Chromia blockchain to help developers build verifiable and policy-controlled AI systems. Designed as a plugin for the OpenClaw framework, Atbash allows organizations to define, enforce, and audit how autonomous AI agents interact with data, tools, and external systems.

The platform introduces a transparent control layer aimed at solving one of the most pressing challenges in enterprise AI adoption: ensuring that increasingly autonomous systems operate within traceable, governed, and auditable environments.

Artificial intelligence systems are becoming increasingly autonomous. Modern AI agents can execute tasks, interact with APIs, make decisions, and coordinate workflows across enterprise software environments.

But as these systems become more capable, organizations are confronting a new challenge: how to govern AI-driven decision-making processes.

Without clear oversight, it can be difficult to determine how an AI system arrived at a particular outcome or whether its actions complied with internal policies and regulatory requirements.

This is the problem that Chromaway is targeting with the launch of Atbash.

Built on the Chromia blockchain platform, Atbash introduces what the company calls an Agentic State & Policy Management (SPM) layer. The system allows developers to define policies governing how AI agents operate, while also providing mechanisms to verify that those policies were followed.

Atbash works alongside OpenClaw, a framework used for developing agentic AI applications. Within this environment, the new plugin allows developers to control how AI agents interact with external systems, validate decisions, and record actions for auditing purposes.

According to Henrik Hjelte, co-founder and CEO of Chromaway, the challenge facing AI developers is shifting.

“AI capability is no longer the bottleneck—control, accountability, and trust are,” he said. The Atbash framework, he added, is designed to ensure AI applications operate within transparent governance structures.

Governance for Autonomous AI

Traditional AI systems typically operate within centralized environments where decisions and outputs may be logged but are not always independently verifiable.

Atbash introduces a different approach by recording decision events and rule validations on-chain.

Each interaction—whether it involves a policy check, a decision point, or an action executed by an AI agent—can be logged as an immutable event on the blockchain.

This mechanism creates a tamper-resistant audit trail that developers, organizations, and external auditors can verify independently.

For enterprises deploying AI in regulated industries such as finance, healthcare, and telecommunications, that transparency could play a crucial role in meeting compliance requirements.

The approach aligns with emerging regulatory expectations that require organizations to maintain detailed documentation of automated decision-making processes.

The Role of Clawchain

The system is coordinated through Clawchain, which manages how interactions between AI agents, governance policies, and application infrastructure are recorded.

By linking policy enforcement with blockchain-based verification, the architecture ensures that actions taken by AI systems are both traceable and auditable.

This capability supports structured AI governance, where organizations can define rules governing agent behavior and ensure those rules are enforced consistently.

Instead of operating as opaque algorithms, AI agents become part of a monitored and verifiable system.

Blockchain and AI Infrastructure

The launch of Atbash reflects a broader trend in the technology industry: the convergence of blockchain infrastructure and AI governance frameworks.

As AI agents begin to coordinate complex workflows across digital systems, the need for secure, verifiable control mechanisms is increasing.

Large technology providers including Microsoft, Google, and Amazon are already investing heavily in tools that help enterprises monitor and govern AI systems.

However, most current governance solutions rely on centralized monitoring systems.

Chromia’s blockchain-based architecture takes a decentralized approach, ensuring that governance records are immutable and independently verifiable.

AI Governance Becomes a Priority

The introduction of Atbash also reflects growing awareness that AI governance is becoming a foundational layer of enterprise technology infrastructure.

Research from Gartner suggests that organizations adopting AI at scale must implement governance frameworks that provide transparency into automated decision-making processes.

Meanwhile, IDC projects that enterprise investment in AI governance, compliance, and risk management platforms will increase significantly as regulatory frameworks evolve.

These frameworks are particularly relevant for organizations deploying agentic AI systems, where autonomous software agents can initiate actions without direct human supervision.

In these environments, governance systems must not only monitor outputs but also validate the policies governing AI behavior.

Turning AI Activity Into Verifiable Infrastructure

Beyond governance, Atbash also contributes to the broader Chromia ecosystem.

Because AI interactions are recorded on-chain, application usage generates measurable transactional activity on the network. This effectively turns AI-driven workflows into verifiable infrastructure activity within the blockchain environment.

For Chromia, the strategy positions the platform as an infrastructure layer for real-world AI applications that require both scalability and governance transparency.

The first version of Atbash Agentic SPM is scheduled to become available to developers building on Chromia through OpenClaw by the end of April 2026.

As enterprises continue exploring AI-driven automation, tools that combine policy enforcement, verifiable decision-making, and decentralized audit trails may become essential components of the next generation of AI development platforms.

Market Landscape

The rise of agentic AI systems—autonomous software agents capable of executing tasks independently—is creating new governance challenges for enterprises.

Analysts at Forrester report that organizations deploying AI at scale are increasingly prioritizing auditability, explainability, and policy control frameworks.

At the same time, blockchain technologies are being explored as infrastructure for verifiable AI governance, enabling organizations to create transparent and immutable records of automated decision-making processes.

Atbash positions Chromia at the intersection of these two emerging technology trends.

Top Insights

• Chromia introduced Atbash, a governance layer that allows developers to define and enforce policies for autonomous AI agents within enterprise applications.
• The system records AI decisions, validations, and rule enforcement events on-chain, creating a transparent and independently verifiable audit trail.
• Integrated with OpenClaw and coordinated through Clawchain, Atbash enables developers to control how AI systems interact with data, tools, and external services.
• The platform addresses growing enterprise concerns around AI accountability, traceability, and compliance as agentic systems become more autonomous.
• By transforming AI interactions into blockchain-recorded events, Chromia aims to position its network as infrastructure for verifiable AI applications.

Vonage, part of Ericsson, has partnered with India-based AI platform Broot.ai to integrate real-time voice capabilities into its CRM environment. By leveraging the Vonage Voice API and global number provisioning, Broot.ai is enabling sales and marketing teams to place calls directly within the CRM workflow, accelerating how enterprises engage prospects and event leads.

The integration reflects a broader shift toward embedding programmable communications into enterprise software platforms, allowing businesses to connect with customers instantly without leaving their operational systems.

As sales and marketing teams manage increasingly complex customer journeys, speed of engagement has become a competitive advantage. The ability to contact prospects at the right moment—particularly after a lead registers for an event or expresses interest in a product—can significantly influence conversion outcomes.

That challenge is driving software platforms to integrate communications tools directly into customer relationship management systems.

Broot.ai, an AI-powered contact management and enrichment platform designed for B2B marketing and sales teams, is taking that approach by embedding real-time calling capabilities powered by Vonage APIs into its CRM platform.

The integration enables users to place calls with a single click immediately after identifying a potential prospect within the platform. Rather than switching between applications or manually dialing contacts, sales and marketing teams can engage leads directly from the CRM interface.

For organizations running event-driven marketing campaigns or high-volume prospecting initiatives, that workflow optimization can shorten response times and improve engagement rates.

According to Mithun Waghela, Founder and Chief Product Officer at Broot.ai, the platform’s objective is to eliminate friction that slows down relationship-building.

“Sales and marketing teams should be able to focus on building real connections rather than navigating complex systems,” Waghela said, noting that the integration enables seamless in-app calling and automated number provisioning.

Communications Built Into CRM Workflows

The integration leverages the Vonage Voice API, part of the company’s programmable communications platform, which allows developers to embed voice, messaging, and video capabilities into applications.

Through this capability, Broot.ai users can initiate calls directly from the CRM interface without leaving the application environment.

The platform also provides local phone number provisioning across major markets, including the United States, Europe, and the Asia-Pacific region. This allows businesses to establish a local presence when contacting prospects—an important factor in improving response rates and trust among customers.

For global sales teams, the ability to operate with localized numbers while managing communications centrally can streamline international engagement strategies.

The integration also centralizes call data and analytics inside the CRM platform, giving organizations visibility into team activity and campaign performance. These metrics can help marketing and sales leaders understand which outreach strategies generate the most engagement and refine targeting accordingly.

AI and Communications Converge

The partnership highlights a growing convergence between AI-powered CRM systems and programmable communications platforms.

Modern sales and marketing technology stacks increasingly combine AI-driven lead intelligence, automated data enrichment, and real-time communication capabilities within a single environment.

Broot.ai focuses on contact enrichment and AI-driven prospect insights, helping users identify relevant business contacts and contextual information about potential customers.

When combined with embedded calling capabilities, that intelligence can enable teams to move quickly from prospect discovery to live conversation.

According to Christophe Van de Weyer, President and Head of Business Unit API at Vonage, the company’s platform is designed to help software providers embed communication features directly into enterprise applications.

By integrating real-time voice functionality into CRM workflows, Vonage aims to support organizations pursuing digital transformation initiatives that prioritize faster customer engagement.

Growing Demand for Embedded Communications

The integration also reflects a broader shift in enterprise software toward communications-enabled applications.

Traditionally, sales teams relied on separate telephony systems or call center platforms to interact with customers. Today, businesses increasingly expect those capabilities to exist directly within their CRM and marketing automation systems.

Major enterprise platforms such as Salesforce, Microsoft, and Adobe have been embedding communications features and AI assistants into their customer engagement tools to streamline interactions.

Programmable communications providers like Vonage enable smaller software platforms to deliver similar capabilities through APIs.

For CRM developers, the approach allows them to focus on core product innovation while integrating voice, messaging, and verification features through external services.

A Shift Toward Real-Time Engagement

Real-time engagement has become particularly important in B2B sales environments, where timing can influence deal outcomes.

When a prospect downloads a report, registers for an event, or responds to a marketing campaign, the ability to reach out immediately can significantly increase the likelihood of a meaningful conversation.

Embedding voice capabilities directly inside CRM workflows removes operational delays that might otherwise occur when switching between multiple tools.

Industry analysts say this shift reflects a broader transformation in how enterprises approach customer engagement.

Research from Gartner indicates that organizations are increasingly investing in AI-driven customer engagement technologies that unify data, analytics, and communication capabilities.

Meanwhile, forecasts from IDC suggest that global spending on digital transformation technologies—including cloud communications platforms—will continue to grow rapidly as enterprises modernize customer interaction systems.

By combining AI-driven contact intelligence with programmable voice capabilities, the Broot.ai and Vonage partnership illustrates how CRM platforms are evolving into comprehensive engagement environments for modern marketing and sales teams.

Market Landscape

The rise of communications platform-as-a-service (CPaaS) providers is transforming how enterprise applications handle voice, messaging, and customer engagement.

Analysts at Forrester report that programmable communications platforms are becoming a foundational layer for SaaS applications, enabling developers to embed real-time interactions directly within software products.

This trend is particularly significant in CRM and marketing automation platforms, where faster engagement with prospects can directly influence revenue generation and pipeline growth.

Top Insights

• Broot.ai integrated Vonage Voice APIs to enable real-time calling directly within its AI-powered CRM platform, allowing sales teams to contact prospects instantly.
• The platform provides local phone number provisioning across global markets, helping enterprises establish localized communication presence and improve customer response rates.
• Embedded voice capabilities enable teams to engage leads immediately after identifying prospects, improving conversion potential in fast-paced campaigns.
• Centralized call analytics within the CRM platform provide greater visibility into outreach performance and team activity.
• The partnership highlights the growing role of programmable communications APIs in modern enterprise CRM and marketing technology stacks.

Data Axle has introduced SignalFuse™, a new intelligence layer within the company’s data platform designed to help go-to-market teams access real-time insights directly inside their workflows. The launch aims to address a persistent problem facing enterprise marketing and sales teams: vast amounts of data exist, but actionable intelligence often arrives too late to influence decisions.

SignalFuse integrates AI-driven analytics and contextual data relationships to help business teams identify opportunities, risks, and revenue signals faster—reducing the lag between data collection and strategic execution.

Across enterprise organizations, marketing and sales teams have access to more analytics data than ever before. Yet many organizations struggle to translate that data into timely decisions that influence campaigns, targeting strategies, and pipeline development.

The challenge is rarely data availability. Instead, the issue lies in how intelligence is delivered to the people responsible for acting on it.

That gap is what Data Axle is attempting to address with SignalFuse.

The newly launched platform capability acts as an intelligence layer embedded within the Data Axle Platform, enabling users to explore relationships across datasets, detect patterns, and generate insights without waiting for traditional analytics reports.

SignalFuse also integrates an AI Copilot interface that helps users move from exploration to execution quickly, allowing marketing and sales teams to interact with complex data environments through natural workflows rather than relying on static dashboards.

According to Data Axle CEO Andy Frawley, organizations frequently encounter bottlenecks not because data is unavailable but because insights reach decision-makers too late to influence outcomes.

“Too often the bottleneck isn't data; it’s the gap between data and the people who need to act,” Frawley said. SignalFuse, he noted, aims to deliver governed, explainable intelligence directly into operational workflows so teams can act with confidence.

Intelligence Embedded in the Workflow

Traditional business intelligence tools often focus on retrospective reporting. Dashboards summarize historical performance metrics but rarely highlight emerging opportunities or risks in real time.

SignalFuse attempts to shift analytics toward forward-looking intelligence.

The system enables users to explore connections across business, customer, and market data in a unified environment. Marketing teams can identify more precise target audiences, while sales organizations can surface new prospect opportunities earlier in the pipeline development cycle.

Key capabilities highlighted by the company include:

• Reducing analysis cycles from days to minutes
• Improving targeting precision for marketing campaigns
• Surfacing revenue opportunities and risk signals earlier
• Reducing reliance on centralized analytics teams
• Providing explainable insights with traceable governance

For go-to-market teams operating in fast-moving markets, those capabilities could significantly influence operational efficiency.

The Data Foundation Behind SignalFuse

The platform is built on Data Axle’s proprietary B2B and B2C datasets, which connect multiple types of information—including business entities, employers, households, individuals, and service providers.

The company describes the system as a living data environment, continuously updated through AI-assisted monitoring, multi-source validation, and human verification processes.

By linking these data domains together, SignalFuse aims to provide a more complete view of business relationships and customer ecosystems.

The platform also allows organizations to integrate first-party customer data, enabling companies to enrich internal datasets with external intelligence.

This unified data architecture enables advanced use cases that fragmented data systems often struggle to support—particularly when teams attempt to combine customer data, market intelligence, and revenue analytics across different departments.

AI-Driven Intelligence for Go-to-Market Teams

The introduction of SignalFuse reflects a broader shift in enterprise technology toward AI-enabled decision intelligence platforms.

Rather than simply aggregating data, modern systems increasingly analyze patterns, interpret signals, and recommend actions.

Large enterprise software vendors including Salesforce, Adobe, Microsoft, and Amazon have introduced AI copilots and intelligent analytics layers aimed at automating business insights.

These technologies are designed to support data-driven go-to-market strategies, helping marketing and sales teams better understand audiences, prioritize prospects, and improve revenue forecasting.

SignalFuse extends that trend by combining AI-assisted analysis with Data Axle’s unified data infrastructure.

Industry Recognition

The launch also builds on Data Axle’s recent recognition in The Forrester Wave™: Marketing and Sales Data Providers for B2B, Q1 2026.

Forrester identified Data Axle as a leader in the category, highlighting the company’s work in AI-ready data architecture and data unification services.

According to the report, the development of a semantic data layer for agentic business intelligence is becoming a critical foundation for next-generation marketing and sales analytics platforms.

That same data architecture now powers SignalFuse.

The Future of Intelligence-Driven Go-to-Market

As organizations continue to invest in marketing automation, revenue intelligence, and customer data platforms, the demand for real-time decision intelligence is expected to grow.

Research from Gartner suggests that organizations are increasingly prioritizing analytics tools capable of delivering insights directly within operational workflows.

Similarly, IDC projects continued growth in AI-driven enterprise analytics platforms as businesses seek to transform data into actionable intelligence.

SignalFuse positions Data Axle within that evolving market, where success increasingly depends on reducing the distance between data signals and business decisions.

For enterprise go-to-market teams, the difference between discovering insight early and discovering it too late can determine whether opportunities are captured—or missed entirely.

Market Landscape

The market for AI-driven marketing and sales intelligence platforms is expanding rapidly as organizations attempt to unify fragmented data environments.

Analysts at McKinsey & Company estimate that companies leveraging advanced analytics and AI-driven decision intelligence can significantly improve marketing efficiency and revenue growth.

Meanwhile, enterprise platforms are shifting from traditional reporting systems to embedded intelligence architectures that provide contextual insights directly inside operational workflows.

SignalFuse reflects this industry movement toward real-time, AI-powered go-to-market intelligence.

Top Insights

• Data Axle launched SignalFuse, an AI-driven intelligence layer that connects fragmented data sources and delivers real-time insights directly to marketing and sales teams.
• The platform enables users to explore relationships across B2B and B2C datasets, detect patterns, and generate explainable insights without relying on traditional analytics dashboards.
• SignalFuse includes an integrated AI Copilot designed to accelerate the transition from data analysis to revenue-generating actions.
• The solution builds on Data Axle’s proprietary unified data environment linking business, employer, household, and individual datasets.
• The launch follows Data Axle’s recognition as a Leader in The Forrester Wave™: Marketing and Sales Data Providers for B2B, Q1 2026.

GVTC Communications has promoted Jonathan Babbitt to Vice President of Sales & Marketing, expanding his leadership role as the broadband cooperative responds to intensifying competition and evolving customer expectations in the telecommunications and connectivity market.

The appointment signals GVTC’s focus on aligning its go-to-market strategy with customer engagement and long-term member value as broadband providers compete for market share across residential, enterprise, and digital service offerings.

Broadband providers across the United States are facing a new phase of competition. As high-speed connectivity becomes a core piece of digital infrastructure, providers must balance network investment with stronger customer acquisition, retention, and service experiences.

Against that backdrop, GVTC Communications has elevated Jonathan Babbitt to oversee the cooperative’s sales, marketing, and communications functions, consolidating key commercial operations under a single leadership role.

In his new position as Vice President of Sales & Marketing, Babbitt will guide the cooperative’s overall market strategy, focusing on customer lifecycle engagement, brand positioning, and revenue growth.

The move reflects a broader shift among telecommunications providers toward integrated marketing and sales strategies that connect network infrastructure investment with customer experience and digital service delivery.

GVTC President and CEO Josh Pettiette said the promotion recognizes Babbitt’s ability to translate strategic priorities into operational results.

According to Pettiette, success in the broadband market increasingly depends on building long-term customer relationships rather than focusing solely on subscriber acquisition.

“Growth isn't just about adding customers—it's about earning the right to keep them,” Pettiette said, emphasizing the importance of customer trust and service quality in the cooperative’s long-term strategy.

Aligning Go-to-Market Strategy

Babbitt previously served as Director of Sales & Marketing at GVTC, where he led initiatives aimed at improving market access, increasing customer adoption, and strengthening long-term retention.

During that period, he helped develop a coordinated commercial strategy designed to align GVTC’s marketing efforts with evolving customer expectations around broadband reliability, digital services, and community engagement.

His new leadership role expands those responsibilities across the organization’s broader communications and customer engagement strategy.

The goal, according to the company, is to simplify how customers interact with GVTC while ensuring that growth initiatives reinforce the cooperative’s reputation for reliability and service.

For regional telecommunications providers, maintaining that balance is increasingly important as the broadband industry evolves.

Traditional network expansion strategies are now complemented by digital customer engagement, data-driven marketing, and lifecycle service management.

Telecom operators are also investing in new marketing technologies and analytics platforms to better understand how customers discover, evaluate, and adopt broadband services.

Experience in Broadband Transformation

Before joining GVTC, Babbitt served as Vice President of Product Strategy & Communications at Matanuska Telecom Association, a telecommunications cooperative based in Alaska.

In that role, he led a multi-department transformation initiative spanning product development, sales operations, marketing strategy, and customer experience programs.

The initiative resulted in significant business outcomes for the organization, including doubling broadband revenue and increasing market share by 30 percent, while also strengthening member engagement and retention.

That experience reflects a growing trend among telecommunications providers: integrating product strategy, marketing operations, and customer analytics to drive sustainable growth.

Rather than operating as separate functions, these disciplines increasingly work together to optimize the entire customer journey—from initial service discovery to long-term subscription loyalty.

Broadband Market Pressures

The broader telecommunications landscape continues to shift as fiber deployment expands, wireless broadband services mature, and government infrastructure programs accelerate connectivity initiatives.

According to Gartner, telecommunications providers are increasingly investing in data-driven marketing platforms and customer experience technologies to compete in a crowded broadband marketplace.

Meanwhile, research from IDC suggests global spending on digital transformation across telecom industries will continue to rise as providers modernize network infrastructure and customer engagement systems.

For organizations like GVTC, which operate as member-owned cooperatives, the challenge is particularly nuanced.

Unlike national telecom operators, cooperatives often compete through community trust, localized service, and long-term relationships, rather than scale alone.

Babbitt’s expanded leadership role is expected to help strengthen those relationships while ensuring GVTC’s growth strategy remains aligned with evolving digital connectivity demands.

Building Long-Term Customer Relationships

As Vice President of Sales & Marketing, Babbitt will focus on simplifying customer engagement and strengthening lifecycle relationships across GVTC’s service offerings.

That includes ensuring marketing initiatives, communications strategies, and sales operations operate as a cohesive system designed to support sustainable growth.

The approach reflects a broader shift in telecommunications strategy: focusing on customer lifetime value rather than short-term subscriber growth.

For broadband providers, that means investing not only in infrastructure but also in marketing technologies, customer analytics platforms, and service experiences that encourage long-term loyalty.

By aligning sales, marketing, and communications under a unified leadership structure, GVTC is positioning itself to compete more effectively in a market where customer trust and service quality increasingly determine success.

Market Landscape

The broadband industry is undergoing rapid transformation as providers expand fiber networks and introduce new digital services. Analysts at Forrester note that telecommunications companies are increasingly investing in customer experience platforms, marketing analytics, and digital engagement tools to differentiate their services.

At the same time, competition from national telecom providers and emerging wireless broadband services is pushing regional operators to refine their go-to-market strategies.

Leadership roles that combine sales strategy, marketing operations, and communications management are becoming more common as companies seek integrated approaches to growth and customer retention.

Top Insights

• GVTC Communications promoted Jonathan Babbitt to Vice President of Sales & Marketing, consolidating leadership across sales, marketing, and communications as broadband competition intensifies.
• Babbitt previously served as GVTC’s Director of Sales & Marketing, where he helped develop coordinated strategies focused on market expansion, customer acquisition, and long-term retention.
• His earlier leadership role at Matanuska Telecom Association included enterprise-wide transformation initiatives that doubled broadband revenue and increased market share by 30 percent.
• The promotion reflects broader telecom industry trends emphasizing customer lifecycle management, digital engagement, and integrated marketing operations.
• GVTC aims to strengthen long-term customer relationships while aligning its commercial strategy with evolving digital connectivity demands.

Bitly is expanding its push into AI-driven marketing intelligence with the launch of Bitly Assist and Weekly Insights, two new features designed to help marketing teams quickly analyze link and QR code performance. The updates aim to reduce the manual effort required to interpret campaign data and allow marketers to move faster from analytics to action.

The new capabilities arrive as enterprise marketing teams face an expanding volume of performance data across channels, from social media campaigns to email marketing and digital advertising. Bitly’s latest AI integrations attempt to simplify that process by embedding conversational analytics and automated reporting directly inside its link management platform.

For years, marketers have relied on shortened links and QR codes not only for distribution but also as measurement tools for campaign engagement. Platforms like Bitly provide granular performance data — including clicks, geographic engagement, and traffic sources — but extracting meaningful insights often requires time spent navigating dashboards and exporting reports.

Bitly’s newest AI features are designed to address that bottleneck.

Bitly Assist, an AI-powered conversational interface integrated directly into the Bitly platform, allows users to ask natural-language questions about link and QR code performance. Instead of manually searching analytics dashboards, marketing teams can ask questions such as which campaign links generated the most engagement during a specific period or which traffic sources are driving conversions.

The assistant then surfaces the relevant analytics in seconds.

Beyond answering questions, the tool also supports conversational creation of links and QR codes, reducing the number of steps required to launch new marketing assets. According to Bitly, the goal is to streamline the entire workflow — from campaign setup to performance analysis — within a single AI-driven interface.

“Customers don’t have time to dig through dashboards for answers,” said Kelsey Stevenson, Chief Product Officer at Bitly. The company built Bitly Assist and Weekly Insights to remove friction between accessing analytics data and acting on it.

The second feature, Weekly Insights, focuses on automated analytics interpretation. Integrated within Bitly Analytics, the system identifies notable changes in link performance across dimensions such as geographic regions, referral sources, and device types.

Rather than requiring marketers to manually run reports, Weekly Insights highlights patterns and anomalies automatically. For example, the system might surface spikes in engagement from a specific region or identify a campaign link that is outperforming others across multiple channels.

The feature effectively acts as a weekly intelligence report for marketing teams managing multiple campaigns simultaneously.

Early users say the combination of conversational analytics and automated insights can significantly reduce the time required for performance analysis. According to Ania Cotton, SEO and Data Analytics Manager at Americas’ SAP Users’ Group, tasks that once required navigating dashboards for several minutes can now be completed almost instantly using the assistant.

The launch reflects a broader shift toward AI-assisted marketing analytics, where platforms increasingly interpret data rather than simply displaying it.

Major technology vendors — including Salesforce, Adobe, Google, and Microsoft — have all introduced AI copilots or analytics assistants designed to automate data interpretation for marketing teams. These tools attempt to solve a growing problem in enterprise marketing operations: the gap between data collection and actionable insight.

Bitly’s approach focuses specifically on link-based engagement data, an often-overlooked layer of marketing analytics that spans multiple channels.

Links and QR codes serve as connective infrastructure across marketing ecosystems, bridging platforms such as social networks, email campaigns, mobile apps, and websites. As a result, they can provide a unified signal for cross-channel engagement.

By embedding AI interpretation into this layer, Bitly is attempting to turn link analytics into a more strategic marketing intelligence tool.

The company has also been expanding integrations with generative AI ecosystems. Recent updates include integrations with large language models such as ChatGPT, Claude, Perplexity AI, and Microsoft Copilot.

Through its Model Context Protocol (MCP) server, Bitly allows its link management capabilities to operate directly inside external AI tools and enterprise workflows.

The integration strategy reflects a broader trend in SaaS platforms embedding functionality into AI assistants rather than forcing users to work inside standalone dashboards.

From an industry perspective, the timing aligns with growing demand for AI-driven marketing intelligence platforms.

According to Gartner, marketing organizations are expected to increasingly rely on AI-enabled analytics tools to interpret complex datasets and automate campaign optimization. Meanwhile, research from IDC indicates that global spending on AI-powered enterprise software is expected to surpass $300 billion by the end of the decade.

For enterprise marketing teams, tools that reduce analytical friction could have significant operational value. Marketing departments often manage campaigns across dozens of platforms — social media, search advertising, influencer marketing, and CRM systems — each generating its own stream of performance metrics.

Consolidating insights from those systems typically requires multiple analytics tools and manual data interpretation.

Bitly’s AI-driven approach attempts to reduce that complexity by turning link engagement data into a central layer of campaign intelligence.

The company’s scale gives it a large dataset to train and refine such insights. Bitly reports more than 5.7 million monthly active users, more than 600,000 paying customers, and usage across 190 countries.

If the company’s AI features gain adoption, link management platforms could evolve from simple utilities into broader marketing analytics infrastructure.

Market Landscape

AI-powered marketing analytics is rapidly becoming a core capability across enterprise marketing platforms. Analysts at Forrester report that marketing teams increasingly expect software to interpret data, generate insights, and recommend actions automatically, rather than simply visualizing performance metrics.

Platforms such as Salesforce Marketing Cloud, Adobe Experience Platform, and Google Analytics are embedding AI copilots to assist with analytics interpretation.

Bitly’s new features position the company within this emerging category of AI-assisted marketing intelligence tools, with a specific focus on cross-channel engagement data generated through links and QR codes.

Top Insights

• Bitly launched Bitly Assist and Weekly Insights, two AI-driven features that automate link analytics and surface actionable marketing insights directly inside the platform.
• The conversational assistant allows marketers to query campaign performance and create links using natural language, significantly reducing manual analysis and operational friction.
• Weekly Insights automatically identifies trends across channels, geographies, and referral sources, helping marketing teams quickly understand what is driving engagement.
• The launch reflects a broader shift toward AI-powered marketing analytics platforms competing with tools from Salesforce, Adobe, and Google.
• With over 5.7 million monthly users and 600,000 paying customers, Bitly is expanding beyond link management toward AI-driven marketing intelligence infrastructure.

Global video and television revenues are projected to exceed $1 trillion by 2030, according to new research from Omdia. The forecast highlights a major transformation in the media and entertainment industry, with social video advertising emerging as the primary growth driver, accelerating the shift from traditional TV to digital video platforms.

New insights from Omdia reveal that global revenues from traditional television and online video services are expected to grow from $775 billion in 2025 to approximately $1.03 trillion by 2030, signaling a significant structural shift in how content is produced, distributed, and monetized.

The projections were presented by Maria Rua Aguete during the FED Show in Madrid, where she outlined how digital platforms—particularly those driven by social video—are rapidly reshaping the economics of the global media landscape.

Social Video Advertising Driving Industry Growth

According to the report, online video advertising will become the primary engine of industry expansion over the next five years.

Advertising revenues in this segment are expected to increase from $309 billion in 2025 to $540 billion by 2030, boosting its share of total video industry revenue from 40% to 53%.

Social video platforms will play a central role in this growth. Major platforms such as Meta, TikTok, and YouTube are projected to generate around $400 billion in streaming advertising revenues by 2030.

The shift reflects broader changes in audience behavior, including increased consumption of mobile-first, short-form video content powered by sophisticated discovery algorithms and creator-driven ecosystems.

These platforms are enabling advertisers to reach highly targeted audiences while delivering scalable monetization opportunities through algorithmic content distribution.

Subscription Video Growth Slows as Market Matures

While subscription-based video services will continue expanding, the pace of growth is expected to slow compared with advertising-led models.

Online video subscription and transaction revenues are forecast to rise from $174 billion in 2025 to $216 billion by 2030.

This growth signals continued demand for premium streaming services, but analysts note the segment is entering a more mature phase, where competition among streaming platforms and rising subscription costs are influencing consumer spending patterns.

Traditional TV Segments Continue to Decline

In contrast, traditional broadcast and cable television models are projected to lose market share over the next decade.

Linear TV advertising revenues are expected to decline from $123 billion in 2025 to $113 billion by 2030, reducing its share of total video industry revenues from 16% to 11%.

Similarly, pay-TV revenues, including subscriptions and transactional services, are forecast to decrease from $169 billion to $159 billion over the same period.

These declines are largely attributed to the continued trend of cord-cutting, as audiences migrate toward digital streaming services and social video platforms.

A Structural Shift in Media Monetization

According to Maria Rua Aguete, the evolving media landscape reflects a deeper transformation in how video content is monetized.

Social video advertising is increasingly becoming the dominant force in the industry, enabling platforms to combine creator-driven content with highly targeted advertising models.

This approach contrasts with traditional television’s reliance on fixed programming schedules and broad audience targeting.

Digital platforms, by comparison, leverage algorithmic content discovery, user-generated content ecosystems, and advanced advertising technology to drive engagement and revenue at scale.

The Road to a $1 Trillion Video Economy

As the global media industry approaches the $1 trillion revenue milestone, analysts believe the balance of power will increasingly favor digital platforms.

Advertising—particularly social video advertising—is expected to remain the central driver of growth, while traditional TV business models continue to shrink in relevance.

The transformation reflects broader shifts in consumer behavior, technology innovation, and advertiser priorities as the industry moves deeper into the AI-driven, creator-led digital media era.

Key Insights

• Omdia forecasts global video and TV revenues will reach $1.03 trillion by 2030.

• Online video advertising is projected to grow from $309B in 2025 to $540B by 2030.

• Platforms including Meta, TikTok, and YouTube are expected to generate around $400B in streaming ad revenue.

• Subscription-based video revenues will grow moderately to $216B by 2030.

• Traditional linear TV advertising and pay-TV revenues are projected to decline due to cord-cutting and digital migration.

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Global consumer intelligence company NielsenIQ has introduced Ask Arthur Chat, an AI-powered conversational interface designed to simplify how businesses access retail and consumer insights. The new tool allows users to ask natural-language questions about product performance, market trends, and category dynamics using data from NIQ’s extensive datasets.

As organizations across the retail and consumer goods industries seek faster access to actionable insights, NielsenIQ (NIQ) has launched Ask Arthur Chat, an AI-powered conversational interface that enables clients to retrieve market intelligence through natural-language queries.

The new tool expands the capabilities of NIQ’s analytics ecosystem by enabling businesses to interact with consumer data through a conversational AI experience rather than traditional dashboards or complex analytics platforms.

Ask Arthur Chat reflects NIQ’s broader strategy to embed artificial intelligence into its data services, making insights more accessible to a wider range of users, including small and medium-sized businesses.

Simplifying Access to Consumer Intelligence

Retailers and consumer goods companies increasingly rely on large datasets to understand product performance, market dynamics, and shopper behavior. However, accessing and interpreting these insights often requires advanced analytics tools and specialized expertise.

Ask Arthur Chat aims to reduce those barriers.

The AI interface allows users to ask questions in natural language—for example, about category growth trends, product performance, or regional market changes—and receive immediate answers grounded in NIQ’s verified datasets.

By eliminating the need to navigate complex analytics systems, the platform allows business users to quickly access insights that support faster decision-making.

AI Built on Verified Retail Data

Unlike general-purpose AI systems that rely on publicly available data sources, Ask Arthur Chat draws directly from NIQ’s proprietary consumer and retail datasets.

This approach ensures that responses are based on trusted, validated market intelligence rather than unverified information from the open web.

According to Troy Treangen, the goal is to combine AI’s conversational capabilities with the reliability of NIQ’s long-established consumer data platform.

By doing so, the company aims to make sophisticated analytics insights accessible to a broader audience without compromising data accuracy.

Supporting SMBs and Enterprise Clients

Ask Arthur Chat is designed to support a wide range of users across NIQ’s client base.

For large enterprises, the tool provides a faster way to access insights without navigating multiple analytics dashboards.

For small and medium-sized businesses (SMBs), it introduces a lower-friction entry point into NIQ’s data ecosystem.

SMBs often lack dedicated analytics teams, making it more difficult to extract value from complex data platforms. By enabling conversational access to insights, NIQ aims to democratize access to market intelligence.

Strengthening Client Engagement

The launch of Ask Arthur Chat also reflects a broader trend across the data analytics industry toward AI-driven insight delivery.

Organizations increasingly expect analytics platforms to provide answers rather than just dashboards.

Through conversational interfaces powered by AI, companies can ask questions and receive actionable insights in real time, improving both accessibility and engagement.

NIQ expects Ask Arthur Chat to support several key objectives:

• Expanding access to insights among diversified clients
• Increasing engagement across its analytics platforms
• Accelerating adoption of AI-powered analytics tools

Expanding the Ask Arthur Ecosystem

Ask Arthur Chat will initially serve as a conversational gateway into NIQ’s data platform, but the company plans to expand its capabilities further.

Future updates are expected to integrate the feature more deeply into NIQ’s Ask Arthur and Discover platforms, enabling additional workflows and use cases.

Planned enhancements include:

• Integration with existing client analytics workflows
• Expanded data insights and business intelligence capabilities
• Availability across additional global markets
• Multilingual support for international clients

These improvements aim to extend the value of the conversational interface while making NIQ’s insights accessible across a wider geographic footprint.

The Rise of AI-Powered Analytics Platforms

The launch highlights a broader shift within the analytics industry as companies integrate artificial intelligence into data discovery and decision-making processes.

Research firms such as Gartner and IDC have noted growing demand for augmented analytics platforms that combine machine learning, natural language processing, and automated insight generation.

These platforms help organizations move from traditional analytics dashboards toward systems that proactively deliver insights through conversational interfaces.

For companies operating in fast-moving sectors such as retail and consumer packaged goods, the ability to access insights quickly can provide a significant competitive advantage.

Positioning for the Future of Data Access

By introducing Ask Arthur Chat, NIQ is positioning itself to meet the evolving expectations of modern data users.

As organizations increasingly rely on AI-powered tools to navigate large datasets, platforms that combine trusted data with intuitive interfaces may become essential components of the analytics ecosystem.

Through its continued investment in AI-driven innovation, NIQ aims to strengthen its role as a leading provider of consumer intelligence in a rapidly changing data landscape.

Key Insights

• NielsenIQ launched Ask Arthur Chat, an AI-powered conversational interface for accessing consumer insights.

• The tool allows users to ask natural-language questions about product performance, market trends, and category dynamics.

• Ask Arthur Chat draws on NIQ’s verified consumer and retail datasets, ensuring reliable analytics insights.

• The platform aims to expand access to market intelligence for SMBs and enterprise clients.

• NIQ plans to integrate the tool across its Ask Arthur and Discover analytics platforms and expand it globally.

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Enterprise procurement platform Zip has appointed Michael Denari as General Manager of AI, bringing in a seasoned technology executive who previously led global IT and enterprise AI strategy at Canva. In his new role, Denari will oversee Zip’s AI business, including go-to-market strategy, revenue growth, product development collaboration, and internal AI transformation initiatives.

AI-powered procurement platform Zip has announced the appointment of Michael Denari as General Manager of AI, strengthening the company’s leadership team as enterprises accelerate investments in artificial intelligence.

Denari joins the company from Canva, where he served as Global Head of IT and played a central role in building and scaling the company’s enterprise AI initiatives across a global workforce of more than 5,000 employees.

At Zip, Denari will lead the company’s AI business strategy end-to-end, including go-to-market execution, customer success, revenue growth, and internal AI adoption across departments. He will also collaborate closely with Zip’s product and engineering teams to shape the development of AI-powered procurement solutions.

Strengthening AI Leadership at Zip

The appointment comes as enterprises face increasing pressure to demonstrate measurable returns on artificial intelligence investments.

According to Rujul Zaparde, organizations are moving beyond AI experimentation and now expect tangible operational impact.

Zaparde noted that Denari brings unique experience from building AI systems within large organizations—an expertise that aligns with Zip’s goal of delivering enterprise-grade AI solutions that improve how businesses operate.

Enterprise AI Experience at Canva

During his tenure at Canva, Denari led the company’s global IT organization, overseeing a team responsible for enterprise technology infrastructure, governance, and AI-driven transformation.

Over the past several years, he implemented multiple AI initiatives that restructured internal business operations, including:

• Automated internal support systems
• AI-powered sales enablement tools
• AI-assisted employee performance reviews
• Procurement compliance automation agents

These initiatives helped integrate AI into core business workflows across the organization.

Denari’s experience spans both procurement leadership and enterprise IT strategy—an uncommon combination that aligns closely with Zip’s platform focus on procurement orchestration and AI-powered enterprise operations.

From Customer to Leadership Role

Denari also played an early role in adopting Zip’s technology during his time at Canva.

When Zip launched its procurement orchestration platform in 2021, Canva became one of the company’s earliest enterprise customers under Denari’s leadership.

This firsthand experience implementing the platform at scale gave him direct insight into how procurement technologies can transform financial operations and internal workflows.

Driving AI in Procurement

Procurement is increasingly viewed as a high-impact area for enterprise AI adoption.

Large organizations often manage complex supplier networks, approval processes, and compliance requirements, creating opportunities for automation and intelligent decision-making.

Zip’s platform aims to address these challenges by integrating AI into procurement workflows, helping companies manage purchasing, vendor management, and financial controls more efficiently.

Denari believes procurement represents one of the most underutilized opportunities for AI-driven business value.

He noted that organizations often underestimate the operational and financial impact that AI-powered procurement systems can deliver.

Leading Zip’s AI Strategy

In his new role, Denari will oversee several critical areas of Zip’s AI operations, including:

• Developing the company’s AI go-to-market strategy
• Expanding enterprise adoption of Zip’s AI capabilities
• Driving customer success and measurable ROI from AI deployments
• Leading internal AI transformation initiatives
• Collaborating with product and engineering teams on AI innovation

The role also includes scaling the use of AI agents across business functions, reflecting a broader shift toward agentic systems that automate enterprise workflows.

A Career at the Intersection of Procurement and Technology

Before joining Canva, Denari built and led the procurement function at Procore Technologies, where he helped scale operations prior to the company’s public listing.

His experience across procurement leadership, enterprise IT management, and AI strategy positions him to guide Zip’s expansion as companies look to integrate artificial intelligence into core financial and operational processes.

Growing Demand for AI in Enterprise Procurement

The appointment reflects growing interest in AI-powered procurement tools as enterprises seek ways to improve operational efficiency and reduce costs.

Research from Gartner suggests that procurement automation and intelligent sourcing technologies are becoming key priorities for CFOs and operations leaders looking to optimize enterprise spending.

As AI adoption expands across enterprise systems, procurement platforms that integrate automation, analytics, and workflow orchestration are gaining traction within the broader enterprise technology ecosystem.

Zip’s leadership move signals its intention to position AI at the center of procurement transformation.

Key Insights

• Zip has appointed Michael Denari as General Manager of AI.

• Denari previously served as Global Head of IT at Canva, where he built enterprise AI programs across the organization.

• In his new role, he will lead Zip’s AI strategy, go-to-market operations, and enterprise adoption initiatives.

• Denari previously helped build procurement operations at Procore Technologies prior to its IPO.

• The appointment highlights growing enterprise demand for AI-powered procurement platforms and operational automation.

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