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8×8 Brings Agentic AI Natively to the 8×8 Platform for CX

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Business Wire
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8x8 Brings Agentic AI Natively to the 8x8 Platform for CX

8x8, Inc. Logo

8×8 AI Studio, now in early availability, lets any team build and deploy next-gen AI agents on the 8×8 Platform for CX through natural language conversation

8×8, Inc. , a leading global business communications platform provider, introduces 8×8 AI Studio, a native AI development environment that lets any team build, test, and deploy AI agents directly on the 8×8 Platform for CX using natural language instructions. 8×8 AI Studio is now in early availability for 8×8 customers.

Most organizations trying to deploy AI run into the same set of obstacles: specialist developer requirements, expensive professional services, long implementation projects, and tools that sit outside the platforms they already operate. The result is a persistent gap between AI ambition and AI execution. 8×8 AI Studio is built to close it.

Nearly three in four CX leaders prefer to build their own AI agents rather than buy off-the-shelf solutions, according to the Metrigy Customer Experience Optimization 2025-26 report, citing trust and domain expertise as the primary reasons. 8×8 AI Studio is designed for exactly that preference. Because it is native to the 8×8 platform, customers build on infrastructure they already trust, with voice channels, digital routing, interaction data, and telephony pre-integrated from day one. No new vendor. No new contract. No additional infrastructure layer to stand up or configure before the first agent goes live.

“Many companies — especially mid-sized ones — have held back deploying AI agents because of the cost of specialized developers and months of integration work. 8×8 built AI Studio natively on infrastructure its customers already operate so no intricate integration is required,” said Sheila McGee-Smith, President & Principal Analyst at McGee-Smith Analytics. “A business user can describe what they want an agent to do in natural language, and the native Builder creates it, including the ability to take real action such as scheduling appointments or filing tickets. This combination of accessibility for non-technical teams and the flexibility to expand into agentic workflows on a single platform is what will allow companies to transform AI from a concept to repeatable outcomes.”

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AI that ships with the infrastructure

Unlike legacy conversational AI solutions, 8×8 AI Studio comes with a Builder that lets any user describe what they need in plain language and get from concept to a live AI agent across voice and digital channels in minutes rather than months, without professional services or specialist developers.

Dozens of customers across more than 15 verticals are already running hundreds of agents in early availability, putting agents into production across inbound routing, outbound follow-up, sales qualification, scheduling, internal helpdesk triage, and individual employee productivity workflows.

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“8×8 AI Studio is not an AI layer sitting on top of a communications platform, it’s AI embedded in the infrastructure itself,” said Hunter Middleton, Chief Product Officer at 8×8, Inc. “The LLM has direct access to real-time voice data, network telemetry, and the full interaction context that external tools typically cannot access. That direct access also eliminates the transcription intermediaries responsible for the latency and drop-offs that destroy the natural conversation experience on older architectures. That is what separates AI that demos well from AI that holds up at production scale.”

What teams are building

Organizations in early availability are deploying 8×8 AI Studio agents across a range of operational use cases:

  • Always-on inbound coverage. AI agents handle intake, identity verification, call routing, and multi-location reception around the clock – with business-hours awareness built in.
  • Proactive outbound engagement. Outbound agents confirm appointments, follow up on open service requests, and collect structured data from customers without adding headcount.
  • Sales qualification and CRM handoff. AI agents capture inbound leads, run qualification workflows, and hand off to CRM with live Salesforce integration, enabling sales teams to pick up conversations that are already qualified.
  • Internal support resolution. Helpdesk agents triage employee requests, create tickets in connected systems, and resolve common issues before they reach a support team.
  • Employee productivity. Any 8×8 user can configure a personal AI agent through the AI Studio Builder to handle calls, screen requests, and manage after-hours interactions, without IT involvement.

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Qlik Extends Analytics from Answers to Agentic Action

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Business Wire
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Qlik Extends Analytics from Answers to Agentic Action

Qlik

New capabilities across Qlik Answers, Discovery Agent, MCP Server, and new agents for prediction, automation, and analytics development help teams move from inquiry to action, with Discovery Agent surfacing more than 100,000 discoveries for customers since its February GA.

Key takeaways:

  • Agentic analytics is already gaining traction: Since the February GA of Qlik’s agentic experience, the majority of Qlik Cloud accounts with agentic tools are actively using their agents.
  • Qlik Answers becomes an on-demand analyst for decisions: New capabilities for discovery, analysis, prediction, and automation help teams move from signal to action in one governed flow.
  • Prediction becomes part of the agentic flow: Qlik brings predictive signals, explainable reasoning, and workflow action together so users can understand what is likely to happen, why it matters, and how best to respond.

Qlik® announced a major expansion of its agentic analytics capabilities, bringing together Qlik Answers, Discovery Agent, and MCP Server with new agents for prediction, automation, and analytics development to support a more complete path from question to action.

The pressure on enterprise AI initiatives has changed. Teams are being asked to move faster, prove value sooner, and make outputs usable inside real operating workflows. A simple question-answer bot does not solve that problem. Enterprises need AI systems that can surface what matters, reason in context, and drive action with traceability, control, and trust.

Qlik’s latest agentic analytics release is designed around that reality. Qlik Answers remains the entry point, combining structured analytics and unstructured content to deliver richer, more contextual answers. Discovery Agent monitors key data areas and helps surface important changes and anomalies early so users can act faster. Automate Agent executes actions and workflows in downstream systems based on insight and agentic reasoning. Predict Agent builds machine learning models, generates predictions, and helps answer forward-looking questions. Analytics Agent helps teams accelerate analytics development tasks and creation workflows more efficiently.

“The bar for enterprise AI is getting much higher,” said Mike Capone, CEO, Qlik. “It is not enough to produce a fluent answer. AI has to understand the business in context, run on a trusted foundation, and connect insight to action in the systems teams already use. That is how organizations create value without adding more fragility, lock-in, or spend.”

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Key advances in agentic analytics

  • Qlik Answers as the entry point for agentic analytics: Qlik Answers brings together structured analytics and unstructured content in one governed experience, designed to support richer responses and follow-up reasoning rather than isolated prompts.
  • Semantic Layer for governed business context: Qlik is extending data products with shared, reusable business definitions — including measures, dimensions, and relationships — so Qlik Answers, analytics apps, and third-party assistants can work from more consistent business meaning across analytics and AI workflows.
  • Discovery Agent for early signal detection: Discovery Agent monitors key data areas, detects anomalies and important changes, and delivers prioritized signals so users can investigate earlier and act faster.
  • Analytics Agent for analytics development: Analytics Agent can now support analytics development tasks in addition to generating insights, helping teams move through creation workflows more efficiently.
  • Automate Agent to take action: Qlik extends the path from analysis into execution by enabling teams to trigger workflows directly using natural language.
  • Predict Agent for forward-looking insight: Users can ask forward-looking questions, and Predict Agent will build machine learning models, generate predictions, and interpret results to help teams act earlier and with more confidence.
  • MCP Server for broader AI access: MCP Server allows third-party AI assistants to use Qlik analytics to support decisions, bringing Qlik’s context-rich calculations into the assistants teams already use while helping preserve value from existing Qlik investments.

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Together, these capabilities create a more complete agentic experience: detect, investigate, predict, and act. They also reflect a broader Qlik view that analytics becomes materially more useful when answers are grounded in context, supported by explainable reasoning, and connected to execution.

“What stands out here is the focus on the part that usually gets harder after the demo, helping teams understand what matters, work through why it matters, and move into action without losing trust,” said Charles (Cal) Link, Sr. Director – Data and Analytics, Reworld. “For organizations trying to make AI useful in day-to-day operations, that combination of reasoning, prediction, and workflow follow-through is exactly where the conversation needs to go.”

This announcement is part of a broader set of releases at Qlik Connect® 2026, Qlik’s annual customer and partner event, focused on agentic analytics, open and reusable data foundations, operational trust, and sovereignty-ready deployment.

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Backpack Media and Kargo Launch Exclusive Partnership Powered by Predictive Life-Stage Intelligence

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Backpack Media and Kargo Launch Exclusive Partnership Powered by Predictive Life-Stage Intelligence

Sallie Logo

Predictive Audience Insights From Backpack Media, Paired With Kargo’s High-Impact Creative, Help Brands Reach Students and Families at the Right Moment

Backpack Media, a first-to-market education media network which connects brands to high-intent moments across the college student journey, announced its strategic partnership with Kargo, the leading creative optimization platform. Together, the companies will give brands and agencies an exclusive opportunity to reach college students, recent graduates, and their families during their higher education journey. Key benefits of the partnership include:

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  • A powerful combination of data, inventory, and creative: Backpack Media’s trusted, intent-rich first-party data insights through Sallie, combined with Kargo’s engaging creative formats and brand-safe premium environments, work together to capture attention, drive engagement, and deliver measurable performance.
  • Meaningful reach that builds lasting loyalty: This partnership offers the reach, relevance, and efficiency needed to build impact and brand loyalty with students and families at scale and before key purchasing moments. Unlike broad Gen Z proxies or modeled segments, it’s built on life stage intelligence, including who’s heading off to college, about to graduate, or moving into their first apartment, so brands can show up at the moments that actually shape what students need next.
  • Multi-format, full-funnel reach: Brands gain access to onsite placements across Backpack Media, part of the Sallie’s owned properties, and offsite digital and CTV distribution powered by trusted first-party audiences. Kargo’s CTV creative has been shown to capture attention 76% longer than the 30-second CTV ad benchmark and deliver impressions 78% more effective at keeping eyes on screens.

“Backpack Media’s deep education industry expertise, rich first-party audience intelligence, and growing partner ecosystem gives brands a precise, trusted channel to reach students and families. Our active campaigns show we can reach this audience at scale and efficiently across CTV and other channels where we operate. This is a highly engaged audience, and the results we’re delivering reflect that,” said Marco Steinsieck, Managing Vice President and Head of Advertising at Backpack Media. “Pairing Backpack Media’s predictive insights with Kargo’s high-impact offsite formats will enable brands to reach coveted Gen Z audiences with precision, utilizing first-party data to ensure accuracy and real-world relevance.”

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“College students and their parents are making some of the biggest financial decisions of their lives during this time, and they’ll remember the brands that show up in an impactful way,” said Libby Dondero, Senior Manager, Retail Media Solutions at Kargo. “Kargo’s high-impact creative formats are built to stop the scroll, tell a story, and drive action. Paired with Backpack Media’s verified educational audiences, we’re not just putting a brand in front of the right person, we’re putting the right experience in front of them at the right moment.”

The partnership comes as commerce media expands well beyond retail into new categories like education. Backpack Media gives brands direct access to students and early-career adults. Gen Z’s spending power is projected to hit $12 trillion by 2030, and with $86 billion flowing through the college back-to-school market annually, there are immediate opportunities for advertisers.

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Parsnipp Launches New Behavior-Driven AI Search and GEO Platform That Models Real Buyer Interactions

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Parsnipp Launches New Behavior-Driven AI Search and GEO Platform That Models Real Buyer Interactions

Parsnipp Logo GEO Platform

Seattle-based company helps marketers better understand and improve AI search visibility, and prepare for agentic commerce and LLM-based advertising

  • The Parsnipp platform uses and builds persona-based agents that model more realistic user interactions through multi-turn LLM conversations, moving beyond early GEO best practices that rely on contextless single prompt responses.
  • Parsnipp makes AI Search and GEO accessible to small and large brands through a free trial and low cost licensing options.
  • While the platform offers better visibility data and a more simplified approach to GEO, the company is building the agentic commerce and LLM-native advertising capabilities marketers’ will need later this year.
  • Parsnipp was founded by Andrew Higgins, a former executive at Pixlee, Emplifii, and StartX, and Awad Sayeed, the former CTO and co-founder of Pixlee.

Parsnipp has announced the launch of the Parsnipp AI Search and GEO (Generative Engine Optimization) platform. Built for marketers at small to large organizations that want to get started with GEO, the Parsnipp platform moves beyond traditional tools, modelling real user and buyer behavior through persona-based agents and simulations. This not only provides a more realistic view of a brand’s AI-driven discoverability, but enables the platform to curate and prioritize GEO recommendations with the highest impact for marketers.

As consumers increasingly rely on AI systems like ChatGPT, Gemini, Claude, and Grok to research products and make decisions, marketers need a more realistic view of how their brands, products, and content appear across AI search . Parsnipp gives marketers free and low-cost subscription options to start prioritizing GEO now, and is building the agentic commerce and LLM-native advertising tools marketers will need in the future.

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Most AI visibility and GEO tools currently analyze isolated prompts from large language models (LLMs), similar to how early SEO tools tracked keyword rankings. These tools mirror earlier approaches to search and social, testing large volumes of single prompts and analyzing outputs at scale. Parsnipp takes a different approach by simulating full research journeys instead of isolated prompts, capturing more realistic insight into how AI systems evaluate brands and speak to real people. This produces more accurate visibility data and deeper insights into how AI recommendations are actually formed.

“The majority of data in this category looks comprehensive, but it’s not grounded in realistic behavior. People typically don’t interact with AI through isolated prompts. They have conversations. They bring context. They change direction,” said Andrew Higgins, co-founder of Parsnipp. “If you’re not using an AI Search tool that simulates customer personas and behavior, the data may look useful, but it’s not based on how real users interact with AI search. Marketers need to accurately measure how customers are interacting with them via AI, and use it to build tactical and simplified plans that are prioritized, easy to measure, and that help ensure they are visible to today’s shopper.”

The Parsnipp platform helps brands understand at a foundational level how they show up inside AI-driven discovery and search by identifying specific signals, misconfigurations, and content gaps. It prioritizes and gives practical steps to improve visibility today, while helping brands uplevel internally and stay on top of all the changes AI is having on consumer behavior. Some of the key features include:

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  • Brand Analytics – Measure brand visibility across LLMs including ChatGPT, Gemini, Claude, and Perplexity, and receive clear recommendations on the most important changes to improve how a brand appears in AI-generated searches.
  • Competitor Tracking – Benchmark competitors, track Share of Voice, and identify specific opportunities where a brand can improve visibility relative to competitors.
  • Prompt and Citation Tracking – Analyze topics and prompts in detail to understand which sources influence AI responses and receive guidance on how to strengthen a brand’s presence in those conversations.
  • GEO Content Optimization – Identify content gaps and get prioritized recommendations to improve readability, create new content, and optimize existing pages using the built-in content editor.
  • Search Personas – Model different user personas and research journeys to understand how real buyers interact with AI to uncover the most impactful actions to improve visibility across those interactions.
  • AI Readiness Recommendations – Parsnipp analyzes a brand’s full digital footprint, including website structure, product feeds, social media, reviews, ratings, and earned media to identify signals that influence how LLMs interpret and cite a brand. The platform then delivers prioritized, practical recommendations brands can implement immediately to improve AI readability, visibility, and discoverability.
  • Agentic Commerce (coming soon) – Optimize your product catalog for AI-powered shopping experiences by tracking visibility, customizing your catalog, and enabling direct commerce through LLM platforms. This includes analyzing shopping topics, commerce integrations, and catalogue performance across various AI platforms,
  • LLM Ads (coming soon) – Directly advertise within AI search experiences to test and optimize ad placements in LLMs with an AI-native ads manager. Use AI visibility personas to quickly expand your organic and targeted paid programs. Prepare for OpenAI’s ChatGPT ads testing program.

While many AI visibility tools are priced for enterprise customers, Parsnipp offers comparable insights through a free trial and low-cost licensing model (starting at $39.99 USD per month). The platform not only measures AI visibility but provides curated, prioritized recommendations by scanning a brand’s marketing signals across websites, content, social media, reviews, and other digital sources to identify the highest-impact actions brands can take to improve AI visibility now.

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B2B Cold Email Reply Rates Jump 2-3x When AI Personalization Replaces Templates, New Industry Data Reveals

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MTS Staff Writer
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B2B Cold Email Reply Rates Jump 2-3x When AI Personalization Replaces Templates, New Industry Data Reveals

LeadHaste

LeadHaste data from 10M+ cold emails shows AI-personalized outreach hits 3.2% reply rates, 2-3x the industry average.

New performance data from managed outbound firm LeadHaste, drawn from more than 10 million B2B cold emails sent across multiple industries, shows that AI-personalized cold email campaigns consistently achieve positive reply rates of 3.2% – two to three times the 1-1.5% industry average for template-based outreach.

Cold email is not a one-tool problem. It’s a systems problem. The companies using AI to personalize at scale are seeing 2x to 3x the industry average.”

— Dimitar Petkov, Co-Founder, LeadHaste

The findings, based on aggregate campaign data from LeadHaste’s client base spanning healthcare, SaaS, manufacturing, staffing, professional services, and financial services, point to a widening gap between companies that have adopted AI-driven personalization and those still relying on traditional cold email methods.

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“The industry average for cold email reply rates has barely moved in five years – it’s still stuck around 1 to 1.5 percent,” said Dimitar Petkov, Co-Founder of LeadHaste. “Meanwhile, the companies using AI to personalize at scale are seeing 2x to 3x those numbers. The gap is only getting wider, and it’s becoming a real competitive disadvantage to still be sending batch-and-blast templates.”
Key findings from the 10 million email dataset:

According to LeadHaste’s analysis, AI-personalized sequences outperform templates by 2-3x on positive reply rate. Multi-channel campaigns that combine cold email with LinkedIn touchpoints generate 2-3x more positive replies than single-channel email. A multi-provider email verification waterfall (using four or more verification providers in sequence) significantly improves deliverability versus single-provider approaches. The compound effect is real – campaigns in their third month outperform first-month campaigns by a measurable margin as domain reputation strengthens and targeting refines based on actual reply data. Companies that own their sending infrastructure (domains and mailboxes registered in the company’s name) see more consistent long-term deliverability than those using shared or rented infrastructure.

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The data also revealed that the number of tools in a B2B outbound stack matters. LeadHaste orchestrates 35+ specialized tools per client – covering data sourcing, enrichment, verification, personalization, multi-channel sending, and CRM integration – compared to the 3-5 tools used by most agencies or in-house teams. The performance difference, Petkov argues, is not incremental.

“Cold email is not a one-tool problem. It’s a systems problem,” Petkov said. “When you connect the right data sources, enrich through multiple providers, verify at every step, and personalize with AI that actually has context on the prospect – the output is fundamentally different from what a template and a purchased list produces.”

Industry shift toward owned infrastructure
The data highlights another emerging trend: B2B companies are increasingly demanding ownership of their outbound infrastructure rather than renting access through agencies. LeadHaste’s model – where every domain, mailbox, sending platform subscription, and contact list is registered in the client’s name – reflects this shift.

“Historically, agencies held the infrastructure hostage,” Petkov noted. “You’d pay $5,000 a month, and when you left, you started from zero. The market is moving away from that model. Companies want to own what they’ve built, and they should.”

LeadHaste reports that its owned-infrastructure approach has been a key driver of client retention, with clients citing transparency and data ownership as primary differentiators.

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Enhancing Asset Manager Distribution Intelligence with AI

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Enhancing Asset Manager Distribution Intelligence with AI

No complex queries. No manual report building. Just answers. Ask. Discover. Execute.

SalesFocus Solutions (SFS), a fintech leader servicing the asset management industry, announced its comprehensive MARS Distribution Intelligence and Master Data Management (MDM) solution which has been instrumental in providing a single, trusted source of data(“Golden Copy”) for its clients, empowering quicker, smarter sales and marketing decisions will include the new MARS-AI™ feature with MARS v11.

Currently, MARS v10 includes an automated insights feature that provides asset management firms with business insights, such as identifying Advisors who may have an interest in particular products based on user-defined factors, identifying cross-selling opportunities, identifying Advisor trends, and alerting when Advisors break trends, and more. MARS v10 also includes business-critical Distribution Intelligence features such as Advisor Team information, segmentation, lead scoring, cross-sell identification, and automated insights, which leverage behavioral and transaction data that typically fall outside the scope of a traditional MDM platform.

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MARS v11, targeted for release later this year, will provide AI-powered analytics to help distribution teams quickly uncover actionable insights and trends and make faster strategic decisions. Powered by secure AI agents, MARS v11 understands the context, runs the analysis, validates the output, and delivers clear narrative insights, structured data, visualizations, and grounded, explainable results without complex queries and manual report building.

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MARS provides multi-product reporting and automated distribution insights across all product types, including model portfolios, mutual funds, ETFs, Managed Accounts, UCITs, UMAs, SICAVs, CITS, interval funds, DCIO/retirement, and alternative investment products. MARS v11 enhances current capabilities by helping sales and marketing teams shift from administrative work to high-value selling and proactive risk management, thereby growing AUM.

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Harmonic Introduces Breakthrough AI Orchestration Service for Live Video Workflows

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PRNewswire
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Harmonic Introduces Breakthrough AI Orchestration Service for Live Video Workflows

New Service Simplifies Integration of AI Applications with Exceptional Reliability and Security

Harmonic announced a breakthrough new AI orchestration service that enables broadcasters, streamers and service providers to seamlessly integrate AI applications into live video workflows with broadcast-grade reliability and security. The service empowers media companies to efficiently and securely enhance their workflows with best-of-breed AI applications developed by Harmonic and its trusted partners. As a result, service providers can lower AI-related investments and accelerate time to market for more personalized, cost-efficient live streaming and broadcast services.

“As video workflows increasingly become more complex and distributed, media companies face growing challenges with fragmented AI tools, complex integrations and inconsistent reliability,” said Yaniv Sibony, vice president of growth product management at Harmonic. “Our new AI orchestration service changes the game by enabling multiple AI applications to operate from a unified control plane, with built-in reliability and security, helping media companies innovate faster, reduce complexity and confidently bring AI-powered video experiences to market.”

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Boosting Video Workflow Efficiency with a Unified AI Control Plane
Harmonic’s AI orchestration service aggregates, orchestrates, maintains and updates AI applications implemented by Harmonic and best-in-class partners. Through a unified interface, service providers can easily configure, schedule and activate AI applications dynamically for simpler, more cost-effective operations. The service coordinates AI-based processing for live content, synchronizes outputs across multiple AI engines and ensures seamless failover through built-in redundancy mechanisms.

Available as a stand-alone SaaS offering, the orchestration service supports a suite of AI-driven applications, including real-time audio translation and transcription, dubbing and localization, automated live sports highlight generation, scene-level metadata generation, ad-break detection and in-stream ad triggering. Built for the broader ecosystem, the service works natively with Harmonic’s full suite of media processing solutions including VOS®360 Media SaaS, VOS Media Software, XOS media processor and Spectrum™ X Plus.

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Delivering Broadcast-Grade Reliability
Harmonic’s AI orchestration service offers media companies a host of benefits, including:

  • Unified Governance: Service providers can manage multiple AI vendors from a single, secure control plane.
  • Synchronized Processing: Precise alignment of AI outputs across multiple engines enables media companies to deliver frame-accurate broadcast and streaming services.
  • Built-in Redundancy: Seamless failover mechanisms, combined with security and health monitoring for AI tasks, help service providers prevent on-air disruptions.
  • Dynamic Scheduling: Service providers can effortlessly schedule and activate AI applications on a per live event basis.

Simplifying AI Adoption
By unifying multiple AI applications into a single platform, the AI orchestration service enables media companies to avoid costly integration cycles and rip-and-replace upgrades as AI technologies evolve. Ultimately, the service accelerates time to market for new AI-powered offerings by eliminating the need for complex integrations and repeated platform migrations.

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GRAX to Debut Zero-Code AI for Salesforce at TDX

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GRAX to Debut Zero-Code AI for Salesforce at TDX

GRAX, Inc. Logo

GRAX unveils a new solution for turning verified, governed Salesforce historical data into business-ready answers — inviting TDX attendees to see it live!

GRAX, Inc., a leading data platform built for Salesforce data protection and AI, announced it will be showcasing its latest platform innovation for governing, querying, and activating Salesforce data at TDX. GRAX will be offering an early look at GRAX AI: a zero-code AI product that leverages verified and governed data to accelerate answers to real-life data-driven business questions.

Your AI is only as good as the data behind it. GRAX AI debuts at #TDX2026 — zero code, full Salesforce history, 100% yours. Booth #9. Come see it.

With GRAX, users can obtain full context and history to fuel AI, and now, the intelligence layer has been added on top — unlike other tools in the market relying on simple snapshots of CRM data. GRAX AI is designed to accelerate answers to business questions without a single line of code. Key features include:

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  • Clicks, Not Code™: Anyone from Salesforce admins to business users can generate reports and deploy AI assistants. GRAX provides deep historical context for Agentforce agents, ensuring they act on the full history.
  • Business-Ready Reporting: Create beautifully branded and executive-ready departmental reports with precise insights and prescriptive actions
  • Streamlined Time-to-Value: Out-of-the-box knowledge packs and agentic jobs for Salesforce and IT admins, sales, service and marketing to drive faster ROI on Salesforce investments
  • 100% Data Ownership and Control: Complete control with verified, comprehensive historical context

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“When you own 100% of your history, your agents and AI models are powered by deeper knowledge and comprehensive context that empowers you to trust the answers,” said Joe Gaska, GRAX CPO, “In the age of AI, trust and data ownership isn’t optional — it’s everything.” As regulators increasingly require enterprises to prove integrity of data powering AI, accountability flows back to the data owner. GRAX AI is built on governed, customer-owned data foundation with full Digital Chain of Custody data provenance, and immutable history that satisfies audit requirements in the age of AI.

This builds upon GRAX’s existing AgentExchange solution, GRAX for SFDC Backup & Recovery, Archive, Data Seeding, Pipelines & Reuse.

GRAX Exhibiting at TDX 2026

GRAX will be exhibiting at booth #9 on Level 2 of Moscone West, showcasing GRAX AI and the entire suite of products, ranging from data backup and recovery to archive to seeding and more. Stop by the booth to see what’s possible.

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FreeWheel Launches First-of-its-Kind Context Engine to Deliver Scaled, AI-Driven Contextual Targeting Globally Across Premium Video

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FreeWheel Launches First-of-its-Kind Context Engine to Deliver Scaled, AI-Driven Contextual Targeting Globally Across Premium Video

FreeWheel Logo

New features enable smarter ad alignment and enhanced brand safety for advertisers, improved monetization for publishers, and a better viewer experience for consumers

FreeWheel, the leading global technology platform for the streaming advertising ecosystem, announced the launch of Context Engine, a new AI-driven feature within FreeWheel’s Streaming Hub that helps advertisers align ads to relevant premium video content with greater ease, precision, and scale. At the same time, publishers can unlock incremental value from programming based on more granular attributes in content that have high relevancy to the viewer such as emotion, location and objects.

Contextual alignment drives up to +40% more brand recall and delivers brand outcomes across a range of content, allowing publishers to monetize entire catalogs, not only the most “obvious” environments for a given brand*. However, adoption of contextual tools has been slow.

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“Contextual advertising is an increasingly important lever for performance and monetization in premium video. Yet the high cost of implementation has limited adoption at scale for many publishers,” said Larry Allen, Vice President of Global Strategy Addressable, Data, and Measurement, FreeWheel. “Context Engine solves these challenges, providing smarter ad alignment and stronger brand safety to drive higher engagement for advertisers, and enabling publishers to activate premium contextual signals in weeks versus months.”

Context Engine, which is integrated into FreeWheel Streaming Hub and powered by Comcast Technology Solutions’ VideoAI, combines computer vision, machine learning, and generative AI to analyze millions of hours of premium video content and assign contextual segments and keywords from closed captions and visual signals. These classifications make inventory more discoverable and brand-safe for buyers, enabling them to deliver ads at scale alongside content that resonates with audiences, expanding reach and enhancing the viewer experience.

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This is especially important in markets such as the UK and France that have limited access to audience data for targeting.

“As the advertising sales house of the public service broadcaster, brand trust and suitability are essential,” said Marianne Siproudhis, CEO of FranceTV Publicité. “Through this pilot of Context Engine, where we’re proud to be the first in France to test the technology, we’re advancing the way we classify video more consistently at scale, so advertisers can align messages to the right programming while we strengthen monetization across our premium inventory.”

Context Engine is designed to help publishers monetize their programming more effectively such as differentiating content and unlocking previously blocked budgets, while maintaining full control over their inventory classification.

“A+E Global Media (A&E, HISTORY, and Lifetime) is built on premium storytelling and innovation in brand-safe environments,” said Stacie Danzis, SVP, Digital Ad Sales, A+E Global Media. “Advertisers want confidence their messages align with that experience and appear at the right moments. In our pilot with FreeWheel, Context Engine translates our programming into scalable contextual signals—making it easier for buyers to align campaigns without adding complexity for our teams.”

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Wizz App, Trusted by 16 Million Users, Partners with Cinder to Power AI-Driven Content Moderation At Scale

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MTS Staff Writer
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Wizz App, Trusted by 16 Million Users, Partners with Cinder to Power AI-Driven Content Moderation At Scale

Wizz – Make New Friends & Build Real Connections

Committed to building a platform where every user feels safe and valued, Wizz App is consolidating its Trust & Safety infrastructure into Cinder.

Every month, more than 20 million videos and images move through Wizz App, a social discovery platform for Gen Z who want real connections and shared experiences. Behind every one of those uploads is a young adult looking for their people. And behind every one of those uploads is a Trust & Safety team responsible for making sure they find them safely.

Committed to building a platform where every user feels safe and valued, Wizz App is taking a decisive step forward by consolidating its Trust & Safety infrastructure into Cinder, which provides mission-critical infrastructure that protects the world’s most important platforms from junk, abuse, manipulation, and harm at scale.

From different providers to one unified system
Until now, the tools that power Trust & Safety at most social platforms tended to live in separate systems, managed by separate teams. This is why Wizz App selected Cinder as its unified digital safety operating system. The partnership brings together Wizz App’s human review teams and automated moderation workflows under one unified platform, giving the company the speed, consistency, and control needed to keep its community safe.

Marketing Technology News: MarTech Interview with Nicholas Kontopoulous, Vice President of Marketing, Asia Pacific & Japan @ Twilio

How it works
At the core of the integration are AI agents trained specifically on Wizz App’s content policies. The platform enforces 11 community policy areas covering everything from identity and age verification to child sexual abuse and exploitation (CSAM), harassment and bullying, hate speech, and personal privacy, and holds itself to a standard that reflects its primary user base: Gen Z users aged 16 to 24 who deserve a platform that takes their safety seriously.

Cinder’s agents evaluate every image and video uploaded or shared on the platform, distinguishing between violating and non-violating content with precision, helping human moderators make better and faster decisions with high confidence. Cinder’s AI understands the nuances of Wizz App’s community standards, reducing both over-enforcement and harmful content slipping through. Cinder agents help human moderators work faster and smarter, while also supporting fully automated decision-making that bypasses the review queue entirely.

Marketing Technology News: The ‘Demand Gen’ Delusion (And What To Do About It)

“Wizz App has always put community safety first. Partnering with Cinder is the natural next step, bringing even greater speed, consistency, and visibility to a Trust & Safety program we’re proud of,” says Alexandra Ryabova, Head of Operations. “Cinder amplifies our safety measures, giving our teams and AI systems a unified platform to operate at their best.”

Cinder also manages Wizz App’s user reports and content appeals, processing reports per month through Cinder Managed Moderation, creating a seamless workflow from initial flagging through final resolution. Human reviewers and AI systems work in concert inside the same environment, ensuring nothing falls through the cracks. Every decision is traceable. Every outcome is auditable.

By consolidating moderation, reporting, and appeals into Cinder’s platform, Wizz App gains full operational visibility into its Trust & Safety program. Based on results with similar platforms, teams can expect to reduce operational time by 50% or more, with room to improve further as workflows mature. Cinder’s infrastructure also delivers sub-second latency for synchronous workflow processing, ensuring that speed never becomes a bottleneck as case volume grows. Teams can respond more consistently and scale their operations without sacrificing quality, all critical capabilities as the platform continues to grow.

“Wizz App is exactly the kind of company we built Cinder for: a fast-growing platform that understands safety challenges are core to every product,” says Glen Wise, Cinder CEO. “By bringing together their human review teams, AI workflows, and appeals process into a single place, we’re giving Wizz App mission-critical infrastructure so the team can move fast without compromising on safety. We’re proud to be their partner.”

Trust & Safety has always been at the heart of the Wizz App experience as a priority. Cinder is the next evolution of that commitment—expanding their capabilities while staying true to the community they’ve built.

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Springbig Launches AI Audience Builder, Giving Regulated Retailers a Smarter Way to Target, Engage, and Grow

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Globe Newswire
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Springbig Launches AI Audience Builder, Giving Regulated Retailers a Smarter Way to Target, Engage, and Grow

New natural language segmentation capability accelerates campaign execution, reduces marketer effort, and drives measurable revenue impact for regulated retail operators

Springbig (OTCQX: SBIG), the AI-powered marketing and customer engagement platform serving regulated retailers and brands, announced the launch of AI Audience Builder, a breakthrough capability that enables retailers to create precisely targeted customer segments using plain, natural language powered by artificial intelligence. No filters. No manual logic. No data expertise required.

The launch positions Springbig at the forefront of AI-driven retail marketing, delivering a tangible productivity and revenue advantage to dispensary operators competing in an increasingly data-intensive market.

Instead of navigating complex segmentation workflows, marketers can now describe an audience in their own words and watch Springbig’s AI instantly build it, dramatically compressing the time from insight to campaign execution.

Marketing Technology News: MarTech Interview with Nicholas Kontopoulous, Vice President of Marketing, Asia Pacific & Japan @ Twilio

Transforming How Marketers Work With Data

Audience segmentation has long been one of the most powerful, yet consistently underutilized, levers in retail marketing. The barrier has never been data availability. It has been accessibility.

Traditional segmentation requires marketing teams to build logic manually, configure multiple filters, and maintain a working knowledge of underlying data structures. For operators running lean teams across multiple locations, that friction translates directly into missed revenue opportunities.

AI Audience Builder removes that barrier entirely. Key capabilities include:

  • Natural language audience creation based on intent, purchase behavior, or campaign goals
  • Instant segmentation without manual filter configuration or technical training
  • Faster campaign execution that compresses setup time from hours to seconds
  • Higher targeting precision grounded in real, real-time customer data
  • Broader team access, empowering any marketer, not just data specialists, to run sophisticated campaigns

Marketing Technology News: The ‘Demand Gen’ Delusion (And What To Do About It)

“For too long, the most powerful tools in retail marketing required technical expertise to unlock,” said Jaret Christopher, Chief Executive Officer of Springbig. “AI Audience Builder changes that equation. When a marketer can describe who they want to reach in plain English and have that audience built instantly, it is not just a better workflow. It is a direct driver of revenue. We built this because speed and precision at the campaign level are where wins are made, and we are giving every one of our customers that edge.”

Speed and Precision Where It Matters Most

In high-velocity retail environments, the window between consumer intent and purchase decision is narrow. AI Audience Builder allows operators to react in real time, building and launching hyper-relevant campaigns without the delays historically caused by manual segmentation.

This capability delivers outsized impact during peak promotional periods, product launches, and high-traffic events, where message relevance directly determines conversion and revenue outcomes.

Operators leveraging AI Audience Builder can expect to:

  • Launch campaigns faster with dramatically reduced setup time
  • Reduce segmentation errors that dilute message relevance and waste spend
  • Increase customer lifetime value through smarter, behavior-driven targeting
  • Unlock deeper intelligence from existing customer data without additional infrastructure
  • Scale marketing output without scaling headcount

The result is a more agile, more profitable marketing operation, one that keeps pace with consumer behavior and operational demands simultaneously.

A Platform Built for AI-Native Marketing

AI Audience Builder is the latest addition to Springbig’s expanding suite of AI-powered capabilities, which span campaign automation, personalized messaging, loyalty optimization, and performance analytics. Each capability is designed with the same goal: reduce friction for the marketer and increase the return on every customer interaction.

For investors, AI Audience Builder represents a meaningful advancement in platform stickiness, operator efficiency, and the revenue impact Springbig delivers to its client base. Features that measurably improve operator outcomes strengthen retention, expand usage, and accelerate the platform’s competitive differentiation in the regulated retail technology sector.

“Springbig has made a deliberate and committed transition to being an AI-first company,” said Christopher. “We are embedding artificial intelligence at the core of our MarTech platform and across our entire organization. The goal is straightforward: automate what is manual, simplify what is complex, and use AI to drive operational efficiencies both inside Springbig and for every customer we serve. AI Audience Builder is one example of that commitment in action, but it reflects a much larger transformation underway across our business.”

“The opportunity in AI is not abstract,” Christopher added. “Every campaign that gets built faster, every audience that gets targeted more precisely, every message that lands at the right moment drives measurable revenue for our customers. That is what we are building toward: an AI layer that makes the entire marketing operation smarter, faster, and more effective at every touchpoint.”

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Webflow Launches Webflow AEO, A Closed-Loop Agentic Answer Engine Optimization Solution for Modern Marketing Teams

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Globe Newswire
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DigitalMYnd Launches with New Intelligence Platform, Reuniting Former Phoenix Marketing International Team

Full_Logo_Blue_Black.png

The end-to-end agentic solution enables enterprise marketing teams to measure AI search visibility, get brand-aware recommendations, and ship improvements at scale — all natively in Webflow

Webflow, the agentic web marketing platform, today announced Webflow AEO, a closed-loop answer engine optimization (AEO) solution that helps enterprise marketing teams get discovered, understood, and cited by AI answer engines. Webflow AEO, now in private beta, uses AI agents to bring measurement, recommendations, and execution directly into Webflow, so teams can go from insight to shipped improvements quickly and seamlessly.

“Most teams know AEO matters, but the problem is they can’t execute on it fast enough because their tools weren’t built for it and the context isn’t there. We’re helping close that execution gap with agents,” said Rachel Wolan, Chief Product Officer at Webflow. “Webflow allows customers to work inside a system that already knows their brand, their voice, and what they’re trying to say. We’ve automated closing the loop with Answer Engines because of this, so Webflow agents can continuously analyze your AEO presence, surface what to fix, and ship user-approved improvements all without ever leaving the platform where their site lives.”

Marketing Technology News: MarTech Interview with Nicholas Kontopoulous, Vice President of Marketing, Asia Pacific & Japan @ Twilio

Webflow AEO is built around a closed loop designed to make AEO operational for teams at scale:

  • Measure AI visibility: Webflow Analyze will be expanded with dedicated AEO analytics, so enterprise teams can easily understand how often their brand is cited in answer engines, which prompts they appear in, and how AI visibility connects to on-site engagement and conversions. No data expertise or instrumentation required.
  • Recommend discoverability improvements: AEO agents surface prioritized, brand-specific recommendations across technical and content optimization — from broken links and outdated metadata to new content opportunities that are likely to boost citations for the prompts you’re tracking.
  • Act in a closed loop: AEO agents help teams turn recommendations into shipped changes across their site at scale, with review-before-publish safeguards that allow teams to move fast while staying in control.

This launch builds on a year of investment in AEO education and foundational tools: our widely-adopted maturity model and assessment, support for llms.txt and Markdown for agents, LLM-referred traffic insights, and our first AI-assisted technical SEO auditing tool that drove 75% more monthly organic traffic for customers who adopted it. Webflow AEO is the culmination of that work: purpose-built for marketing teams to measure, execute, and scale their AEO strategy.

Marketing Technology News: The ‘Demand Gen’ Delusion (And What To Do About It)

“Search continues to evolve from static results pages to more intelligent, answer-driven experiences, and at Walker & Dunlop, we’ve been investing in structured data, answer-ready content, and a more integrated web and content approach,” said Allison Facciani, Sr. Digital Marketing Manager, Walker & Dunlop. “What’s exciting about Webflow AEO is the potential to bring greater visibility into how our brand is showing up in answer engines, and a more streamlined way to act on those insights. We see it as a natural next step in scaling our AEO efforts.”

”Our decision to migrate to Webflow was in large part due to their continued investment in AI tools, and Webflow AEO is a perfect example of how we plan to use their platform to drive business growth,” said Dylan Zaitsoff, Director of Product Management, Daily OM (an Everyday Health Group company). “Despite having a strong SEO foundations, AEO is new to everyone on our team, so having a tool that gives us visibility into how we show up in answer engines — along with optimization recommendations that a non-technical editor can easily publish — is exactly what we need to keep up and stay ahead of what ‘organic search’ is becoming.”

Webflow AEO is currently in private beta, and will be available soon to all Enterprise customers. To book a demo or learn more about what Webflow AEO can unlock for your team, contact sales here or reach out to your account team.

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ProGEO.ai Survey Finds 75.9% of Marketing Professionals Use GenAI for Work Daily

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Globe Newswire
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ProGEO.ai Survey Finds 75.9% of Marketing Professionals Use GenAI for Work Daily

ProGEO.ai - Generative Engine Optimization (GEO)

Three-quarters (76.8%) of survey respondents report a corporate usage policy, but only 43.8% report technical controls

ProGEO.ai, a data-driven generative engine optimization (GEO) agency, today published the March 2026 “AI Marketing Maturity (AIMM) Index,” a survey of 112 marketing professionals conducted at RSAC, the world’s largest cybersecurity conference.

Maturity models are common in cybersecurity. The Cybersecurity Maturity Model Certification is a Department of Defense (DoD) framework required for its contractors. MITRE, a cybersecurity non-profit, published the MITRE AI Maturity Model.

Marketing Technology News: MarTech Interview with Nicholas Kontopoulous, Vice President of Marketing, Asia Pacific & Japan @ Twilio

The AI Marketing Maturity (AIMM) Index is intended to benchmark enterprise adoption rates and marketing use cases to establish a baseline for marketing maturity. The AIMM Index reveals that 91.1% of respondents have a corporate-paid subscription to GenAI and 75.9% are using GenAI for work on a daily basis.

Key findings from the “AI Marketing Maturity (AIMM) Index” include:

  • A gap between policy and enforcement – 76.8% of marketing professionals report their company has a corporate usage policy for GenAI, but only 43.8% report their company enforces this policy with technical controls.
  • Content creation is the top use case – 83% of marketing professionals are using GenAI to brainstorm content at least once a week; 82.1% are creating content, and 75% are repurposing content.
  • Vibe coding is on the rise – 23.2% of marketing professionals are using GenAI for vibe coding at least once a week.

Marketing Technology News: The ‘Demand Gen’ Delusion (And What To Do About It)

“Most marketing professionals are using AI every day, but less than half of their organizations are enforcing corporate usage with technical controls,” said Clinton Karr, CMO, ProGEO.ai. “Adoption without governance shows a lack of maturity, which calls into question whether marketing teams are using AI strategically.”

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Ecer.com: Redefining the Future of Cross-Border B2B with a Mobile-First Ecosystem

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MTS Staff Writer
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Ecer.com: Redefining the Future of Cross-Border B2B with a Mobile-First Ecosystem

Ecer.com: search for China Manufacturers, wholesalers, Suppliers, Exporters & Factories from the leading B2B marketplace

In the traditional foreign trade model, cross-timezone communication and physical factory inspections often resulted in grueling decision cycles and high costs. That landscape is being radically transformed by the rise of the mobile internet.

The Mobile Efficiency Leap
Recent data reveals that over 70% of international buyers now utilize mobile devices as their primary tool for sourcing suppliers, sending inquiries, and conducting remote factory audits. In response, Ecer.com, a global leader in mobile B2B marketplace, is pushing the boundaries of technical innovation to usher in an era of “anytime, anywhere” high-efficiency collaboration.
“Business opportunities are now reachable at a moment’s notice,” a spokesperson for Ecer.com noted. Through the Ecer.com mobile platform, buyers can initiate instant video inspections and discuss product specifications in real-time. Furthermore, an AI-powered inquiry system facilitates multi-language interaction, effectively eliminating communication barriers and converting time-zone delays into 24/7 business connectivity.

Marketing Technology News: MarTech Interview with Nicholas Kontopoulous, Vice President of Marketing, Asia Pacific & Japan @ Twilio

Building Trust Through Immersive Technology
Trust remains the most critical variable in cross-border B2B transactions. To address the high costs of traditional on-site audits, Ecer.com has introduced a mobile-based Panoramic Factory Inspection solution.
By leveraging VR technology and 360° real-time mobile views, buyers can conduct immersive observations of production lines and product details. This innovation shrinks a process that once took days into a matter of hours.
 Case Study: Hunan CTS Technology Co,.ltd recently used ECER’s mobile tools to secure a deal with a skeptical German buyer.
 The Result: By providing a live video tour of the workshop, testing procedures, and warehouse management—supplemented by VR structural analysis—the enterprise turned a “preliminary inquiry” into “deep trust” in under two hours. The initial order was confirmed within the same week.

A Full-Link Digital Trade Loop
Moving beyond simple information matching, Ecer.com is evolving into an integrated digital trade powerhouse. The platform seamlessly connects every stage of the trade journey—from inquiry acquisition and remote inspection to logistics tracking—all within a mobile interface.
The fusion of AI, VR, and live interaction reduces the complexity of global collaboration, allowing supply chains to respond more with greater agility to market fluctuations.

Marketing Technology News: The ‘Demand Gen’ Delusion (And What To Do About It)

The “Always-On” Era of Foreign Trade
As “Mobile First” becomes the industry standard, the workplace for foreign trade has shifted from the confines of the office to any space with an internet connection. By merging mobile technology with intelligent capabilities, Ecer.com is helping enterprises achieve instant response and precision docking. In an increasingly competitive global market, being “Always-On” is no longer an advantage—it is the new core competency for growth.

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zMaticoo SDK 2.0 Officially Released: Full Technical Breakthroughs for Global Ad Monetization

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PRNewswire
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zMaticoo SDK 2.0 Officially Released: Full Technical Breakthroughs for Global Ad Monetization

Fresh off its successful offline event recently, zMaticoo has officially launched zMaticoo SDK 2.0, a comprehensively upgraded programmatic ad monetization SDK designed for global mobile developers. The event brought together industry professionals from Google, PubMatic, Tencent and other leading companies for technical exchanges and ecosystem collaboration.

Backed by proprietary AI algorithms and deep learning models, SDK 2.0 has been validated by rigorous global A/B testing, delivering exceptional improvements across core monetization metrics: 26.7% higher ad fill efficiency, 27.4% growth in theoretical revenue, and 3.9% positive eCPM lift, breaking the industry trade-off between fill rate and unit price.

Marketing Technology News: MarTech Interview with Nicholas Kontopoulous, Vice President of Marketing, Asia Pacific & Japan @ Twilio

The upgrade features five key technical optimizations covering the entire ad lifecycle.

  1. Low-latency loading cuts initialization time to under 100ms with intelligent caching and progressive asset loading.
  2. Load-show decoupling eliminates rigid binding, boosting ad show success rate by over 30%.
  3. Native rendering replaces WebView, reducing template size by 80% and accelerating speed by 90%+.
  4. Optimized click paths adopt DeepLink/CCT for e-commerce and in-app Google Play installation for CPI campaigns, lifting conversion efficiency by 20%+.
  5. Built-in GDPR, CCPA, and COPPA compliance ensures global readiness, while mandatory two-week gray release validation guarantees stability.

zMaticoo also previewed its upcoming AIGC-powered smart template system, which will dynamically optimize creatives based on user behavior, region, and app scenarios to further improve CTR and conversion.

Marketing Technology News: The ‘Demand Gen’ Delusion (And What To Do About It)

With developer-centric design, zMaticoo SDK 2.0 balances performance, user experience, and revenue, helping global publishers maximize traffic value and achieve sustainable growth.

zMaticoo holds IAB certification and Google Index validation, ensuring full compliance, transparency, and secure integration for global publishers.

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Envisionit Names Tiffany Kirby President and Chief Growth Officer

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Business Wire
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Envisionit Names Tiffany Kirby President and Chief Growth Officer

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Envisionit named Tiffany Kirby President and Chief Growth Officer, expanding her mandate to lead the agency into its next phase of growth as the marketing industry reaches an inflection point.

Since joining in 2022, Kirby has driven double-digit growth year over year by doing something most agencies still can’t: delivering truly integrated solutions across brand, media, and technology without sacrificing depth in any of them.

Marketing Technology News: MarTech Interview With Fredrik Skantze, CEO and Co-founder of Funnel

That integration-first mindset is now more critical than ever. Agencies across the industry have rushed to attach the word “AI” to their capabilities, but few have done the work to make it operational or meaningful for clients. Envisionit has. In 2023, CEO Todd Brook founded Unchained, a specialized AI consultancy focused on AI strategy, education, and development. Kirby has been central to bridging that capability back to Envisionit’s clients, partnering with Unchained to apply AI in ways that strengthen marketing outcomes rather than just streamline internal processes.

As President, Kirby’s scope now extends beyond growth to encompass operations, client strategy, and team development. She is joined in the leadership structure by Jason Goldberg, an owner and Chief Innovation Officer, who reports directly to Kirby and ensures that innovation and AI integration remain embedded in how the agency serves clients.

The result is a leadership model built for where the industry is heading: fully integrated services with AI applied practically to help clients work smarter and maintain a competitive edge.

Marketing Technology News: The Death of Third-Party Cookies Was Just the Start. Are You Ready for Consent Orchestration?

“AI without a marketing lens risks efficiency at the expense of experience. Marketing without AI means falling behind. Our clients get both: integrated marketing excellence and specialized AI working together, so the technology behind the scenes works to improve the brand experiences people feel,” said Kirby.

“What Tiffany has built at Envisionit speaks for itself: double-digit growth and real results for clients driven by truly integrated thinking,” said Todd Brook, CEO of Envisionit. “She’s carried our AI vision forward, made sure every department has the resources to be successful, and leads with a people-first mindset that gets the best out of the team. This role puts her at the center of all of it.”

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AI Won’t Transform Your Business. Your Data and Systems Will.

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Craig Dempster
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AI Won't Transform Your Business. Your Data and Systems Will.

Eighty-eight percent of organizations are now using AI in at least one business function. Only 34% are genuinely rethinking how their business operates around it. And just 20% have seen real revenue growth from their investments. That gap is not a technology problem. It’s a readiness problem. Most organizations are dropping AI onto broken data, misaligned teams, and workflows that were never intentionally built. Then they wonder why the results aren’t coming.

The Foundation Was Already Broken

Here’s something I’ve seen time and again: AI doesn’t fix broken systems. It runs faster inside them. When CRMs hold conflicting records, AI produces conflicting outputs. When sales and marketing can’t agree on what a qualified lead looks like, AI accelerates that disagreement. When workflows were patched together through years of reactive decisions, AI speeds up the chaos. The vast majority of enterprise AI initiatives fail to deliver a measurable return, and the reasons have nothing to do with the technology itself. Poor strategy, misaligned teams, and disconnected systems and data are driving those failures.

Revenue leaders feel this directly. They’ve invested in CRMs, tech stacks, and sales enablement tools. None of them talk to each other the way they should. Teams spend more time pulling reports than acting on them. And now there’s pressure to layer AI on top of it all. Adding AI to a broken operating model is a liability, not a strategy.

Marketing Technology News: MarTech Interview With Fredrik Skantze, CEO and Co-founder of Funnel

Data Quality Is a Revenue Problem

Before any AI initiative can deliver, the data underneath it has to be clean and connected. Most organizations aren’t there yet. Data quality consistently ranks among the top operational challenges for senior leaders, and the financial cost of bad data is significant. Organizations that ignore it aren’t just dealing with reporting headaches. They’re leaving real revenue on the table.

The fallout extends directly into AI deployments. Some companies are already reporting negative results from their AI investments, and the most common barrier isn’t budget or technology access. It’s on the people side. Teams that don’t have the skills or the clean inputs to work effectively with the tools they’ve been handed. Many data and analytics leaders will say their data strategy needs a serious overhaul before their AI ambitions can work. Companies are regularly drawing wrong conclusions from data that lacks business context, and AI accelerates that problem rather than correcting it.

The Martech Stack Isn’t the Answer

The tools were supposed to solve this. They haven’t. McKinsey’s martech research found that 47% of martech decision-makers say stack complexity and integration problems are the main reasons they can’t get value from their tools. Not one of the 50+ senior marketing leaders interviewed at Fortune 500 companies could clearly explain the ROI of their martech investment.

The organizations winning with AI in 2026 built the foundation before they built the model. They started with infrastructure. They treated data governance as a revenue priority, not an IT task. They rebuilt workflows to operate with AI. And they aligned their sales, marketing, and customer success teams around shared data and shared definitions before adding any new technology layer. The pattern is consistent across high-performing organizations: workflow redesign comes before model deployment. The operating system built around the model is what defines leaders, not the sophistication of the model itself.

What Comes Next

The organizations that will pull ahead in 2026 are the ones that got the basics right before deploying advanced AI. The ones still chasing model sophistication are building on unstable ground. Start with one clean source of truth. Sales, marketing, and customer success data all in one place, no exceptions. Align your teams around shared KPIs before you even think about deploying tools that depend on that alignment to work. Treat workflow redesign like the business priority it actually is, not something you get to when things slow down.

And be honest with yourself: AI will move you faster in whatever direction your operations are already pointed. If the foundation is broken, AI just accelerates the break. Get the foundation right, and AI becomes a real growth driver. Skip it, and you’re adding speed to a system that was already headed in the wrong direction.

Marketing Technology News: The Death of Third-Party Cookies Was Just the Start. Are You Ready for Consent Orchestration?

Lucid Software integrates real-time visual context into ChatGPT with MCP server app

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PRNewswire
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Lucid Software integrates real-time visual context into ChatGPT with MCP server app

Lucid Software, the leader in AI-driven work acceleration, announced the launch of its Lucid app for ChatGPT, which enables users to search, summarize, and generate Lucid documents directly in ChatGPT.

As teams leverage AI to ideate and execute work, fragmented information across applications hinders them from accessing the context they need to move work forward. The Lucid app for ChatGPT bridges Lucid’s visual intelligence and the conversational power of ChatGPT, so users can:

  • Find Lucid documents instantly by asking ChatGPT to locate diagrams and boards related to a topic or project.
  • Unlock instant insights by generating summaries of visual work from intricate diagrams or large-scale brainstorms in seconds.
  • Turn complex ChatGPT discussions into editable diagrams and open them directly in Lucid.
  • Share diagrams and documents with teammates directly from a conversation.

Marketing Technology News: MarTech Interview with Liat Barer, Chief Product Officer @ Odeeo

“The Lucid app for ChatGPT is yet another example of how Lucid is bringing the systems and context teams rely on into the AI tools they use every day,” said Jamie Lyon, Chief Product & Strategy Officer at Lucid Software. “When that context is readily available, teams can move faster and stay aligned. That’s where Lucid excels—bringing clarity to how teams work with AI so they can execute with confidence.”

The integration is powered by Lucid’s MCP server, which connects large language models with Lucid documents so AI tools can securely search for diagrams, fetch document content, create visualizations, and share documents.

Marketing Technology News: What Marketers Need to Know About the European Accessibility Act

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UJET Launches New Channel-Led Global Sales Motion with Google Cloud, Accelerating Agentic AI and CX Transformation in Midmarket and SMB Segments

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PRNewswire
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UJET Launches New Channel-Led Global Sales Motion with Google Cloud, Accelerating Agentic AI and CX Transformation in Midmarket and SMB Segments

New partnership delivers rapid deployment of Google Cloud CCaaS and Gemini Enterprise for Customer Experience through AVANT’s Global Network of Trusted Advisors

UJET, a leader in AI-powered contact center innovation, announced the launch of Google Cloud CCaaS by UJET, a new managed service offering and strategic sales motion designed to bring Google Cloud’s enterprise-grade agentic AI, CX, and contact center solutions to the small-to-medium business (SMB) and midmarket sectors through AVANT’s Technology Solutions Distributor (TSD) channel.

“This launch represents a significant expansion of our long-standing relationship with Google Cloud,” said Vasili Triant, CEO of UJET. “Through this managed service approach, we are providing the channel with Google Cloud’s industry-leading, AI-first CX solutions, backed by world-class support and dedicated customer success resources. This motion allows small business and midmarket organizations to easily purchase and adopt the same powerful AI tools used today by the largest global enterprises.”

Trusted Advisors (TA) can now offer Google Cloud CCaaS and the full Gemini Enterprise for Customer Experience (CX) suite to businesses of any size looking to leverage Google Cloud’s leading agentic AI capabilities without the requirement for large Google enterprise agreements or Google Cloud Platform spend commitments.

Marketing Technology News: MarTech Interview with Stephen Howard-Sarin, MD of Retail Media, Americas @ Criteo

“A hyperscaler entering the TSD channel is a turning point for CX. By bringing Google Cloud’s AI-powered platform into the channel exclusively through AVANT, organizations gain both a stable, scalable foundation for innovation and the guidance of a Trusted Advisor to navigate it,” said Andrew Pryfogle, Head of CX/AI and Global Education Lead at AVANT. “With Google Cloud’s Gemini-powered CX stack at the core, this is what an AI-first customer experience truly looks like.”

Bridging the Digital Divide with AI-First CX

The new Google Cloud CCaaS by UJET offering brings Google’s brand recognition, AI innovation and leadership, along with transactional speed and simplicity, to the Trusted Advisor Channel, including:

  • Google Cloud CCaaS – self-service and routing, omnichannel, mobile/digital, conversational insights, analytics, CRM-first and standalone agent desktop.
  • Gemini Enterprise for CX – native Google AI embedded across the end-to-end customer journey.
  • Google CX Agent Studio – low-code/no-code agentic agent builder, supporting shopping and service/support use cases.
  • Google Agent Assist – AI coach, next-best action, real-time transcription, and post-interaction summarization.
  • White-glove customer success managers and technical support – value-added services designed to ensure success for SMB-Midmarket CX buyers.

Marketing Technology News: From MarTech Stack to MarTech Fabric: Weaving Brand, Content, and Conversion Into One Thread

“Our goal is to make every business agentic and every customer experience streamlined. By launching this motion with UJET and AVANT, we’re giving SMBs sophisticated AI tools and foundations they need to succeed in the agentic era,” said Darshan Kantak, VP, Applied AI, Google Cloud.

Google Cloud CCaaS by UJET and Gemini Enterprise for CX are available immediately through AVANT and its network of Trusted Advisors. Partners can also offer standalone, over-the-top, point solutions, such as virtual agents, agent assist, and conversational analytics, to provide incremental value to customers on their existing stacks, giving them flexibility to move to the end-to-end solution and CCaaS platform in the future.

Write in to psen@itechseries.com to learn more about our exclusive editorial packages and programs.

Prosper Insights & Analytics Says AI’s Next Competitive Battleground Is High-Quality, Forward-Looking Data

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MTS Staff Writer
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Prosper Insights & Analytics Says AI’s Next Competitive Battleground Is High-Quality, Forward-Looking Data

Prosper Insights and Analytics

Forbes article by CEO Gary Drenik and Prosper podcast briefing highlight why reliable signal—not just larger models—will define the next era of AI

Prosper Insights & Analytics is calling attention to what it believes is the most important emerging issue in artificial intelligence: the growing shortage of high-quality, forward-looking data needed to make AI systems more reliable, explainable and economically useful. That perspective is outlined in a recent Forbes article by Prosper co-founder & CEO Gary Drenik, “AI’s Real Bottleneck Isn’t Algorithms, It’s The Rare Earths Of Data,” which argues that AI’s biggest constraint is no longer model architecture alone, but the scarcity of trustworthy data inputs that reflect real human intent and behavior over time.

When data captures consumer intent, confidence and changing behavior before it appears in conventional reports, AI becomes more than an automation tool—it becomes a strategic intelligence asset.”

— Phil Rist, EVP-Strategic Initiatives, Prosper Insights & Analytics

In the article, Drenik compares scarce, high-value data to rare earth elements—inputs that are difficult to source, yet essential to powering modern technology at scale. He explains that many AI systems continue to struggle because they are trained primarily on backward-looking digital exhaust such as clicks, logs, scraped text and transactions, rather than clean, auditable and longitudinal signals that help explain why people make decisions and how they are likely to behave next. Prosper believes this distinction is becoming increasingly important as enterprises push AI from experimental demos into mission-critical forecasting, planning and decision support.

Marketing Technology News: MarTech Interview with Nicholas Kontopoulous, Vice President of Marketing, Asia Pacific & Japan @ Twilio

That same theme is explored in a Prosper Spotify podcast episode, “Prosper Insights AI & Innovation Briefing 2026 E25: The Rare Earth Moment: AI’s High-Quality Data Bottleneck.” As described, the podcast argues that the AI industry’s central challenge has shifted from algorithmic complexity to the scarcity of premium data capable of producing dependable, forward-looking insight. The episode emphasizes that proprietary datasets with longitudinal depth are becoming more valuable than broad open-web scraping when the goal is to predict macroeconomic shifts, market trends and consumer behavior with greater confidence.

“AI will not create durable enterprise value simply because a model is bigger or faster,” said Phil Rist, co-founder of Prosper Insights & Analytics and EVP-Strategic Initiatives. “The real advantage comes from the quality of the signal going in. When data captures consumer intent, confidence and changing behavior before it appears in conventional reports, AI becomes more than an automation tool—it becomes a strategic intelligence asset.”

Marketing Technology News: The ‘Demand Gen’ Delusion (And What To Do About It)

Prosper notes that this issue has major implications for businesses, investors and policymakers alike. As accountability, regulation and performance expectations rise, organizations will increasingly need AI systems built on transparent, representative and well-governed data foundations. In Prosper’s view, the winners in the next phase of AI will not simply be those with the largest models, but those with access to scarce, high-integrity datasets that improve prediction, explainability and decision quality over time.

Drenik’s Forbes article also points to the growing market value of proprietary signal-rich data as AI leaders seek more dependable inputs for real-world applications.

Write in to psen@itechseries.com to learn more about our exclusive editorial packages and programs.

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