Fuel retailers are increasingly competing on more than pump prices. Loyalty programs, retail partnerships and customer data are becoming important tools for attracting drivers and measuring the effectiveness of branded fuel networks. CITGO Petroleum is putting those capabilities at the center of its latest marketer meetings.

CITGO is hosting its Light Oils Marketer Roundtable Meetings from Sept. 17 through Oct. 29 across 16 cities, with Walmart+ Gas Savings and enhancements to the Club CITGO loyalty program among the primary topics. The meetings are intended to give branded marketers updates on customer loyalty, marketing programs and technology designed to simplify retail operations.

The Walmart+ partnership gives eligible Walmart+ members additional savings at participating CITGO locations when they enroll in Club CITGO. The program illustrates how fuel retailers are increasingly using partnerships and loyalty ecosystems to connect fuel purchases with broader consumer memberships.

Loyalty Becomes a Digital Layer in Fuel Retail

The shift is significant because fuel loyalty programs are moving beyond simple discounts. For marketers, the underlying customer data can provide information about purchasing behavior, campaign response and the effectiveness of promotional offers.

CITGO will also discuss upcoming Club CITGO enhancements and new loyalty reporting features designed to give marketers greater visibility into program performance. Those reporting capabilities could help branded locations evaluate customer engagement without relying solely on transaction volume.

The company is also highlighting its Good to Go marketing campaign and Illuminate image program, expanding the discussion beyond loyalty into brand consistency and customer acquisition.

For a network of independently operated branded locations, centralized digital marketing tools can help standardize customer engagement while allowing individual marketers to understand local performance.

Walmart+ Partnership Adds a Broader Customer Ecosystem

The Walmart+ relationship is particularly notable because it connects a fuel loyalty program with a large consumer membership platform rather than requiring CITGO to build every customer relationship independently.

This type of partnership reflects a broader trend across retail: loyalty programs increasingly function as interconnected ecosystems. Fuel, grocery, convenience retail and digital memberships can overlap around the same consumer, giving brands additional opportunities to influence purchasing decisions.

The model also creates a competitive consideration for fuel marketers. Discounting can attract customers in the short term, but loyalty platforms can potentially create more persistent relationships by combining incentives with customer identification and personalized engagement.

CITGO's approach is therefore less about a standalone gas discount and more about integrating fuel savings into a wider digital loyalty experience.

Data and Market Intelligence Move Closer to the Foreground

The meetings will also feature a State of the Industry presentation from OPIS Chief Oil Analyst Denton Cinquegrana, covering petroleum-market conditions and trends.

That combination of market intelligence, loyalty reporting and marketing programs reflects the operational pressures facing fuel retailers. Marketers must respond to commodity-price movements while also managing changing consumer expectations around discounts, convenience and digital engagement.

For enterprise marketing teams, the CITGO example highlights how loyalty technology increasingly connects front-line transactions with analytics. The value of these systems depends not only on the incentive offered to customers but also on whether marketers can translate customer and campaign data into actionable decisions.

Fuel retail is becoming increasingly connected to digital commerce and loyalty infrastructure. Large retailers and fuel brands are competing through mobile experiences, membership programs, payment integrations, personalized promotions and partnerships.

CITGO's Walmart+ initiative sits within that broader movement toward ecosystem-based loyalty. Rather than treating a fuel transaction as an isolated purchase, retailers can connect it with a consumer's wider membership and purchasing relationship.

For branded fuel networks, the challenge is balancing centralized programs with local operator needs. Reporting, customer data and marketing automation can help provide scale, but individual locations still operate in markets with different competitive conditions and customer behaviors.

The technology layer is consequently becoming an increasingly important component of fuel marketing, particularly as brands seek ways to measure loyalty beyond enrollment numbers.

Top Insights

• Fuel loyalty is becoming digital: CITGO's Club CITGO enhancements show how loyalty platforms can connect fuel purchases with customer data and marketing performance.
• Retail partnerships expand reach: Walmart+ connects CITGO savings with an established membership ecosystem, giving eligible customers another reason to engage with participating locations.
• Reporting matters for marketers: New loyalty reporting capabilities are designed to help CITGO marketers understand program performance and make data-informed business decisions.
• Brand and loyalty converge: Good to Go and Illuminate complement loyalty initiatives, showing how fuel marketers are combining customer acquisition with brand consistency.
• Market data remains critical: OPIS industry analysis adds petroleum-market intelligence to a marketer agenda increasingly shaped by digital customer engagement and loyalty technology.

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Localizing video for international audiences has traditionally meant a combination of translation, voice recording, editing and post-production work for every target market. Vosko AI is entering that workflow with a platform designed to automate much of the process while retaining the original speaker's voice and emotional delivery.

Vimia Tech Limited announced the launch of Vosko AI on September 16, positioning the platform as an end-to-end AI video localization system for creators, educators, e-commerce companies, marketing teams and businesses. The platform supports video translation across 99 languages and combines AI dubbing, voice cloning, subtitle localization and audio preservation in a single workflow.

AI Moves Video Localization Toward Production Automation

Vosko AI's core proposition is not simply automated translation. Its system separates spoken dialogue from background audio, translates the dialogue and generates a localized voice track intended to retain characteristics of the original speaker.

The company says the platform can preserve individual voices in multi-speaker videos while retaining background music and sound effects. It also includes speaker detection and voice mapping for formats such as interviews, podcasts and other multi-person recordings.

The workflow is aimed at high-volume production. Users can process up to 150 video or audio files in a session, generate versions in as many as eight target languages simultaneously and upload individual files lasting up to 200 minutes. That puts the product beyond short social clips and into webinars, courses, corporate training, podcasts and long-form educational content.

For marketing teams, the potential value is operational rather than purely linguistic. A product demonstration or campaign video can theoretically become a set of localized assets without requiring a separate recording and post-production process for every market.

The Competitive Shift in AI Dubbing

AI-assisted dubbing is becoming part of a wider transformation in media production. McKinsey's analysis of AI in film and television found that AI is already being used for dubbing and localization, alongside applications such as footage clipping and video-library discovery.

Vosko AI therefore enters a market that includes dedicated translation platforms, AI voice companies and broader creative-production suites. The differentiating factor in this segment is increasingly workflow depth: whether a platform can handle translation, voice preservation, subtitles, speaker separation, synchronization and post-production from one environment.

The company's own website claims capabilities beyond the launch announcement, including subtitle replacement, script editing and automatic timing adjustments. Those claims are company-reported rather than independently verified, so enterprise buyers would need to evaluate output quality, language accuracy, voice-consent controls, security and synchronization performance before deploying the technology at scale.

That distinction matters because AI localization is not simply a cost-reduction exercise. Brand messaging, cultural context and speaker identity can all affect how localized marketing content performs. Human review may remain necessary for regulated industries, technical terminology and campaigns where cultural nuance is particularly important.

Enterprise Marketing Implications

For global marketing organizations, video localization sits at the intersection of content operations, marketing automation and digital experience. Instead of producing one master video for a worldwide audience, teams can increasingly treat the original asset as a source from which market-specific versions are generated.

This could be particularly relevant to e-learning providers, SaaS companies, consumer brands and agencies managing large libraries of video assets. The ability to process long-form material and multiple files in parallel also addresses a common bottleneck: localization capacity rather than content creation itself.

Vosko AI is now available commercially, according to the company. The launch adds another AI-native option to a rapidly developing video technology category where speed, voice authenticity and production control are becoming central competitive considerations.

AI video localization is moving from a specialist post-production function toward an integrated component of digital content operations. Platforms such as Vosko AI compete not only on translation accuracy but also on voice preservation, speaker separation, synchronization and the ability to manage large asset volumes.

For enterprise marketing teams, this creates a new layer in the content stack. Adobe, Microsoft, Google and other major technology ecosystems are investing broadly in AI-powered content creation and productivity, while specialist platforms are targeting individual production workflows. The result is a market where integration and quality control may become as important as the underlying translation model.

AI dubbing also changes the economics of international content distribution. McKinsey notes that dubbing and localization are already among the areas where media companies are experimenting with AI-assisted production.

Top Insights

• AI localization becomes scalable: Vosko AI's batch processing and multilingual exports target production teams managing large volumes of international video assets.
• Voice preservation becomes strategic: Retaining speaker identity, tone and emotion could help brands maintain consistency across localized campaigns and educational content.
• Long-form video expands the market: Support for files up to 200 minutes makes AI localization relevant to webinars, podcasts, courses and corporate training.
• Localization enters the MarTech stack: Automated translation and dubbing connect video production with broader content operations, campaign management and global customer engagement.
• Human review remains important: Translation quality, cultural context, consent and brand terminology remain considerations for organizations deploying synthetic voices at enterprise scale.

Get in touch with our MarTech Experts.

Search visibility is becoming less about occupying a position on a results page and more about whether a company can be discovered, understood and referenced across AI-driven discovery systems. That shift is behind a new strategic partnership between CEO Coaching International and GreenBanana SEO.

CEO Coaching International announced GreenBanana SEO as its newest Platinum Strategic Partner, giving the coaching firm's CEO and entrepreneur community access to expertise spanning traditional search engine optimization, Answer Engine Optimization (AEO), Generative Engine Optimization (GEO) and AI search visibility.

Founded in 2009, GreenBanana SEO will support clients with diagnostics across Google Search, Google Maps, Google's AI-powered search experiences and AI platforms including ChatGPT, Gemini, Perplexity and Claude. The partnership is positioned around a growing problem for enterprise marketers: visibility is increasingly distributed across multiple discovery interfaces rather than concentrated in conventional search results.

Why AI Search Is Changing SEO

Traditional SEO largely focuses on helping search engines crawl, understand and rank webpages. AI-mediated discovery introduces another layer. Systems can synthesize information from multiple sources and present an answer rather than simply returning a list of links.

For businesses, that creates a different visibility question: not only whether a page ranks, but whether the company's information, expertise and digital entities are sufficiently clear and credible to be surfaced in AI-generated answers.

GreenBanana's offering therefore combines technical SEO, content architecture, structured data, entity development and analysis of AI citations. Its competitive analysis component is designed to identify which companies are being surfaced by AI systems and examine the factors behind that visibility.

The challenge is significant because consumer confidence in AI-generated search is still developing. A September 2025 Gartner survey of 377 U.S. consumers found that 53% distrusted or lacked confidence in the reliability and impartiality of AI-powered search results.

That finding puts authority and source credibility alongside conventional ranking signals. It also means companies cannot simply treat AI search as another traffic acquisition channel.

What the Partnership Means for Enterprise Marketing

The partnership extends beyond organic search. GreenBanana will also provide guidance covering Google Business Profile optimization, paid media across Google Ads, Meta, LinkedIn and YouTube, and measurement connecting search performance with leads and CRM data.

That broader approach reflects how enterprise marketing stacks increasingly operate. Search visibility, paid acquisition, content, customer data and revenue attribution are interconnected rather than isolated functions.

McKinsey estimates that generative AI could create $2.6 trillion to $4.4 trillion in annual economic value across analyzed use cases, with marketing and sales among the functions positioned to capture substantial value.

For marketing leaders, the practical implication is a shift toward measuring discovery quality rather than rankings alone. A company may need to monitor how frequently it appears in AI-generated answers, which competitors are cited alongside it, whether its corporate entities are consistently understood, and how those discovery events translate into qualified demand.

The announcement also builds on an existing relationship between the organizations. GreenBanana CEO Kevin C. Roy previously appeared on the CEO Coaching International podcast discussing SEO, AEO and AI-driven marketing.

Market Landscape

GreenBanana enters an increasingly crowded AI-search optimization ecosystem. Google is integrating generative experiences into its search environment, while Microsoft, OpenAI and other technology companies are expanding AI-assisted discovery through their respective platforms.

The competitive distinction is therefore less about a single optimization technique and more about how agencies connect technical SEO with content authority, structured information, brand entities and measurable business outcomes.

For enterprise teams already investing in platforms from Salesforce, Adobe and other marketing technology providers, AI search adds another visibility layer to an existing MarTech stack. It does not eliminate traditional SEO; instead, it changes what marketers may need to measure beyond rankings and clicks.

The partnership between CEO Coaching International and GreenBanana SEO is an example of that transition: SEO remains foundational, but the destination is increasingly an ecosystem in which search engines and generative AI systems interpret, summarize and recommend information.

Top Insights

• AI search expands SEO: Companies increasingly need visibility across traditional search and generative interfaces, affecting SEO, content and enterprise marketing teams.
• Authority becomes measurable: GreenBanana's AI visibility analysis focuses on citations and recommendations, highlighting the growing importance of credible, structured company information.
• Search and revenue converge: Connecting rankings, AI visibility, leads and CRM outcomes could shift enterprise SEO reporting from traffic metrics toward commercial performance.
• AI trust remains unresolved: Gartner found substantial consumer distrust in AI-powered search, reinforcing the importance of accurate, authoritative and transparent business information.

Get in touch with our MarTech Experts.

Kustomer is introducing a formal certification standard for implementation partners as customer experience teams increasingly rely on agencies, BPOs and systems integrators to configure AI-powered support environments.

As customer experience platforms become more dependent on artificial intelligence, the quality of implementation is becoming an increasingly important part of the technology buying decision.

Kustomer is addressing that issue with the launch of its Partner Certification Program, a new framework designed to verify that implementation partners can configure Kustomer's platform and AI capabilities through practical, Kustomer-reviewed assessments.

The program is aimed at a growing implementation ecosystem that includes business process outsourcers, agencies and other service partners. Rather than relying exclusively on partner experience, referrals or self-directed training, Kustomer says certification requires partners to demonstrate hands-on competency before independently implementing the platform for customers.

The program reflects a broader challenge emerging across enterprise AI deployments. Buying an AI-enabled platform is only one part of the implementation process. Organizations must also configure workflows, connect data, establish appropriate automation and determine how AI capabilities operate within existing customer-service processes.

Poor implementation can create operational problems even when the underlying software is capable of delivering the required functionality. For customer experience teams, that can translate into longer deployment cycles, additional remediation work and delays in realizing the expected value from automation.

Kustomer's certification program attempts to address that implementation layer through structured learning and practical evaluation.

Partners can pursue certification tracks covering platform fundamentals, implementation methodology and AI configuration. The company says candidates must complete graded assessments, including a practical exercise reviewed by Kustomer, before receiving certification.

The initial structure includes two broad paths: Platform + AI implementation and Standalone AI configuration. That track-based approach recognizes that partners may have different technical capabilities and customer responsibilities rather than requiring every partner to demonstrate the same scope of expertise.

The program also introduces recurring recertification. That is particularly relevant for AI-enabled platforms because capabilities, workflows and configuration requirements can change more quickly than conventional enterprise software.

For Kustomer, certification therefore functions as both a quality-control mechanism and a partner enablement strategy.

Certified partners will receive access to additional resources, including partner office hours, escalation support involving Kustomer's support and professional services teams, and a partner sandbox environment. A planned partner directory is also intended to allow customers to identify certified providers based on specialization.

The directory could become particularly useful as enterprise buyers navigate an increasingly fragmented CX implementation market. Customers evaluating an implementation partner often have limited visibility into the technical capabilities of individual teams, particularly when AI configuration is involved.

Kustomer CEO and Co-Founder Brad Birnbaum said the program is intended to give customers greater confidence in partner delivery while providing experienced partners with a way to demonstrate their capabilities.

The company is initially launching the certification program with a group of strategic BPO and agency partners. Additional certification tracks and the partner directory are expected to be introduced in later phases.

The development also fits into a wider enterprise software trend: vendors are increasingly treating implementation ecosystems as part of the product experience. As platforms become more configurable and AI capabilities become embedded in customer-facing workflows, implementation quality can influence everything from deployment speed to governance and ongoing operational performance.

For Kustomer, the certification program puts a formal qualification layer around that ecosystem. Its effectiveness will ultimately depend on how rigorous the practical assessments remain, how frequently certifications are updated and whether customers use the forthcoming directory when selecting implementation partners.

Market Landscape

AI is changing the implementation requirements for customer experience platforms. Traditional platform configuration can involve workflows, integrations, routing and reporting, while AI deployments can add model behavior, automated decisions, knowledge sources and escalation rules.

That makes implementation expertise increasingly relevant to enterprise buyers evaluating AI-enabled CX systems.

Certification programs can provide a common qualification mechanism, but their value depends on the depth of assessment and how consistently vendors enforce the standard across their partner networks.

Strategic Outlook

Kustomer's program represents a move toward treating partner competency as part of AI deployment governance.

For customers, a practical certification model can provide another data point when comparing implementation providers. For partners, recurring certification creates an incentive to maintain expertise as platform capabilities evolve.

The larger industry question is whether similar standards become more common as enterprise AI moves from experimentation into customer-facing production environments.

Top Insights

• Kustomer's new certification program requires implementation partners to demonstrate practical platform and AI configuration skills before receiving certified status.
• The program covers both broader Platform + AI implementation and more focused standalone AI configuration capabilities.
• Kustomer is introducing recurring recertification to keep partner expertise aligned with changes in its AI and CX platform.
• A planned partner directory will allow customers to identify certified providers according to implementation specialization.
• The initiative highlights a growing enterprise concern: AI platform performance can depend heavily on implementation, configuration and ongoing governance.

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Staples is marking 40 years in business with a new brand platform that reframes its long-running “Easy” positioning around a familiar problem for business customers: the operational friction created by fragmented suppliers, disconnected processes and unreliable fulfillment.

Staples is turning its 40-year “Easy” brand promise into a broader business-services proposition with the launch of Hard vs. Easy, a campaign designed to contrast workplace complexity with the processes and services Staples says can simplify it.

The platform moves beyond individual office products and places procurement, fulfillment, workplace services and expert support at the center of the brand narrative. Staples says the campaign is aimed at businesses of different sizes, highlighting challenges such as managing multiple vendors, inconsistent product availability, last-minute purchasing and fragmented workplace operations.

At the center of the campaign is a new Hard Button, positioned as a counterpart to Staples’ familiar Easy Button. The two physical symbols are intended to represent a choice between workplace friction and a more consolidated purchasing and service experience.

That positioning reflects a broader change in how business-supply companies compete. Rather than focusing exclusively on product assortment and price, providers increasingly package procurement, delivery, services and account support into broader workplace solutions.

Staples says its business offering now spans janitorial and sanitation supplies, breakroom products, furniture consultation and installation, custom print and marketing services and other workplace requirements. The company also says 75% of Fortune 500 companies have Staples Business accounts.

The campaign's emphasis on supplier consolidation is particularly relevant to procurement teams. Gartner's January 2026 research says supplier spread can increase administrative burden, duplication, fragmented risk and cost leakage, while its procurement research recommends evaluating when supplier consolidation can improve sourcing efficiency.

That gives Staples' campaign a practical business context beyond its advertising creative. For procurement and facilities teams, the number of suppliers involved in workplace purchasing can affect administrative workload, ordering processes and supplier management.

Staples' “Easy” proposition is therefore being positioned around infrastructure as much as convenience. The company identifies three areas supporting the platform: workplace solutions, expert guidance and what it describes as reliability across its infrastructure and supply chain.

Its existing digital and physical footprint also supports that omnichannel proposition. Staples currently promotes next-day delivery to more than 98% of the U.S. on qualifying in-stock orders and one-hour in-store pickup, according to its website.

The company has also retained the Easy concept across its existing brand ecosystem. Its website continues to use “That was easy” messaging while presenting products, services, delivery and business solutions through the same convenience-oriented positioning.

For Staples, Hard vs. Easy gives the established brand idea a more explicitly B2B dimension. Instead of simply presenting “easy” as a consumer convenience, the campaign connects it to procurement decisions, vendor management, workplace operations and fulfillment.

That distinction matters because business buyers often evaluate workplace suppliers across more than product selection. Delivery performance, service expertise, account management, implementation support and the ability to consolidate purchasing can all influence the operational value of a supplier relationship.

The campaign also illustrates a broader direction in B2B marketing: turning operational capabilities into a recognizable consumer-style brand narrative. Rather than explaining procurement efficiency through technical language, Staples is using the visual contrast between Hard and Easy to make an operational proposition easier to understand.

The long-term effectiveness of the platform will depend on whether the campaign's promise is supported consistently by availability, delivery, service and account experiences. For a brand built around “Easy,” those operational touchpoints become part of the marketing message itself.

Market Landscape

B2B procurement is increasingly focused on simplifying processes while balancing supplier concentration against operational and supply-chain risk.

Gartner's procurement research identifies supplier consolidation as a potential way to reduce administrative complexity and improve sourcing efficiency, while also emphasizing that organizations need to consider concentration risk rather than treating consolidation as an automatic solution.

Staples' new positioning sits within that broader shift: workplace purchasing is increasingly being presented as an integrated service relationship rather than a collection of individual transactions.

Strategic Outlook

Hard vs. Easy gives Staples a framework for translating its established brand identity into a broader B2B proposition.

The strategic question is whether customers experience the promised simplicity across the entire journey—from supplier selection and ordering through delivery, installation, support and repeat purchasing.

That makes the campaign notable not simply as an anniversary rebrand, but as an example of B2B marketing increasingly linking brand positioning with operational experience.

Top Insights

• Staples' Hard vs. Easy platform expands its longstanding Easy positioning into procurement, fulfillment, workplace services and business operations.
• The new Hard Button creates a visual counterpart to the Easy Button, turning supplier complexity and operational friction into the campaign's central contrast.
• Staples is positioning workplace expertise and infrastructure alongside product assortment as part of its business-services proposition.
• Supplier consolidation gives the campaign a procurement angle as businesses examine administrative complexity and fragmented vendor relationships.
• The platform demonstrates how B2B brands can translate operational capabilities into simpler consumer-facing marketing narratives.

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B2B marketing teams are increasing their use of AI, but new research from Integrate and Demand Metric suggests that the quality and governance of underlying marketing data may be closely associated with how prepared organizations are to deploy AI at scale.

Marketing organizations are investing heavily in artificial intelligence, but the ability to turn those investments into operational systems depends on a less visible layer of the technology stack: data governance.

A new study from Integrate and Demand Metric, based on 245 marketing, revenue operations and commercial operations leaders across B2B and B2B2C organizations, identifies a substantial difference in data practices between organizations reporting higher and lower year-over-year revenue growth. The research also finds that the same gap appears in reported AI readiness and governance.

Among organizations classified as high-growth in the study, 24% said at least 75% of their marketing data was AI-ready, meaning clean, governed and accessible. That compares with 10% among lower-growth organizations. High-growth organizations were also nearly four times as likely to rate their data governance maturity as Advanced or Leading, at 57% compared with 14%.

The findings extend beyond data quality.

Seventy-nine percent of high-growth organizations reported automating lead validation before CRM ingestion, compared with 44% of lower-growth organizations. The high-growth group was also more likely to report real-time or near-real-time lead delivery, at 45% versus 17%.

Sales acceptance showed another pronounced difference. Thirty-one percent of high-growth organizations reported sales lead acceptance rates of 80% or higher, compared with 9% among lower-growth organizations.

The study also connects governance with AI oversight. Twenty-nine percent of high-growth organizations strongly agreed that they have formal frameworks covering AI bias, fairness and explainability, compared with 10% of lower-growth organizations. This suggests that AI readiness in the surveyed organizations extends beyond having usable datasets to establishing processes for controlling how AI systems operate.

The distinction is increasingly relevant as marketing teams move from experimentation toward larger-scale AI deployment. Gartner reported in May 2026 that marketers allocated an average of 15.3% of their marketing budgets to AI, while only 30% of surveyed organizations described their AI readiness capabilities as mature or fully developed. Gartner specifically identified data foundations, processes, governance and talent as factors needed to scale AI investments.

Gartner's July 2026 research similarly describes AI-ready marketing data as a foundation for marketing's broader AI transformation.

For B2B marketing operations, the implications reach into the entire lead-management process. Standardized vendor intake, automated validation, deduplication, consent controls and faster routing can determine whether data reaches a CRM or marketing automation platform in a usable state.

That becomes particularly important when AI systems consume CRM, campaign and customer data to generate recommendations or automate workflows. Poorly governed inputs can introduce errors into downstream analysis and automation, while fragmented processes make accountability harder to establish.

The Integrate and Demand Metric research describes this difference as the "Governance Gap": organizations that treat data governance as an upstream operating discipline versus those that depend on manual intervention and downstream cleanup. The study recommends standardizing data intake, validating records before CRM or marketing automation ingestion, improving lead-delivery speed and formalizing data and AI accountability.

The findings do not establish that stronger governance directly causes higher revenue growth. Instead, they show that the surveyed high-growth organizations report stronger governance, operational efficiency and AI readiness at the same time.

That distinction matters as marketing teams move toward AI-enabled revenue operations. The next phase of AI adoption may depend less on adding another model or application and more on whether the systems feeding those applications are clean, governed and operationally accountable.

Market Landscape

The study arrives as marketing organizations move from isolated AI experiments toward broader automation. Gartner reported that marketing leaders expect AI-driven automation to increase from 16% of marketing work in 2026 to 36% by 2028.

That expansion increases the importance of data infrastructure. AI systems operating across lead management, campaign optimization, analytics and customer engagement require consistent inputs and defined rules for access, quality and accountability.

For B2B organizations, governance therefore increasingly intersects with marketing operations, revenue operations and CRM administration rather than remaining solely an IT concern.

Strategic Outlook

The research points to a shift in how marketing teams may need to evaluate AI readiness.

Instead of measuring readiness only through the number of AI tools deployed, organizations can examine whether marketing data is standardized, validated, accessible and governed before it reaches downstream systems.

The strongest operational distinction in the study is not simply AI adoption. It is the combination of data quality, automation, speed-to-lead, sales acceptance and formal AI oversight reported by high-growth organizations.

For marketing leaders, that makes governance an operating capability that connects demand generation with the systems responsible for turning marketing signals into revenue processes.

Top Insights

• High-growth organizations in the study were more than twice as likely to report that at least 75% of marketing data was AI-ready.
• Data governance differences extend into lead operations, with high-growth organizations reporting substantially higher automated validation and faster lead delivery.
• Formal AI governance frameworks covering bias, fairness and explainability were reported much more frequently among high-growth organizations.
• The research connects data quality with sales operations, including a large difference in reported lead acceptance rates between the two growth groups.
• Current Gartner research similarly identifies data foundations and governance as prerequisites for scaling marketing AI beyond experimentation.

Get in touch with our MarTech Experts.

Healthcare marketing is moving beyond generic educational content as Onspire Health Marketing partners with Vidscrip to bring provider-recorded videos into automated patient communications, practice websites and digital campaigns.

Healthcare practices increasingly have to communicate with patients across multiple digital touchpoints, from appointment-related messages and websites to email, text and social media. The challenge is producing content that feels personal without creating a separate production burden for already busy providers.

Onspire Health Marketing and Vidscrip are targeting that problem through a new partnership that allows healthcare practices to incorporate short, provider-recorded videos into existing patient engagement and marketing programs.

The initial rollout is focused on independent specialty practices, with the companies saying the model could eventually extend to hospitals, health systems and other healthcare organizations.

Through Vidscrip, clinicians can record short videos addressing recurring patient questions, explaining treatment options or describing different stages of a care journey. Onspire then integrates those recordings into communication and digital marketing programs already being managed for the practice.

The model is deliberately different from traditional healthcare video production. Instead of requiring a large-scale shoot or dedicated content program, providers can create short, single-topic recordings that can subsequently be reused across multiple channels.

A video answering a common question, for example, could become part of an automated email or text journey, appear on a relevant practice website page and be repurposed for social media.

That reuse is important because healthcare organizations face a persistent content challenge: patients need information at different points in their decision-making and care journeys, while providers have limited time to repeatedly answer the same questions outside clinical encounters.

The partnership effectively turns those recurring explanations into a reusable content library.

The approach also reflects a broader change in healthcare marketing. Digital channels increasingly play a role in how patients research conditions, evaluate providers and prepare for appointments. Healthcare marketing platforms are consequently placing greater emphasis on educational content, provider expertise and communication that can be delivered across multiple channels.

Onspire already positions video as part of broader healthcare marketing programs, including educational clips, provider introductions and condition explainers. Its current services also emphasize distributing video across websites, search, AI-driven discovery, social media and patient communications.

There is historical evidence supporting the educational role of clinician-created video. A 2017 evaluation cited by the companies, published in The Joint Commission Journal on Quality and Patient Safety, examined 1,203 viewer responses to an academic medical center's video program. The release says 86% of responses indicated that a video helped viewers understand their health, medical condition or treatment plan. That study is older and should not be treated as a current measure of healthcare video effectiveness.

The technology also creates an opportunity for healthcare marketers to connect content production with patient-journey automation. Instead of building communication sequences entirely around written copy, practices can introduce provider voices at moments where additional explanation may be useful.

That can include pre-appointment education, treatment explanations, frequently asked questions or follow-up communications, depending on the practice's workflow.

The partnership's larger significance is therefore less about adding another video channel and more about changing how provider expertise is captured and distributed.

For healthcare organizations, the challenge will be maintaining clinical accuracy, privacy, accessibility and appropriate review processes as video becomes a larger part of patient-facing digital communication.

Market Landscape

Healthcare marketing platforms increasingly combine content, patient communications, websites, automation and analytics rather than treating each channel independently.

Video adds another layer because provider-recorded content can simultaneously serve educational, engagement and marketing functions. The growing use of short-form video also makes reusable content libraries more practical for organizations that cannot support traditional high-production workflows.

For smaller specialty practices, the ability to record short answers and reuse them across several channels may reduce the operational barrier to creating provider-led content.

Strategic Outlook

The Onspire-Vidscrip partnership points toward a healthcare marketing model in which provider expertise becomes a reusable digital asset.

The key shift is from creating videos for individual campaigns toward building libraries of answers that can be activated according to patient needs and communication stages.

That model could become increasingly relevant as healthcare organizations expand digital patient engagement. However, content governance remains critical: provider videos need appropriate clinical review, current information, privacy safeguards and clear boundaries between patient education and promotional messaging.

For healthcare marketers, the opportunity is to make provider participation easier without separating content creation from the broader patient communication infrastructure.

Top Insights

• Onspire and Vidscrip are integrating provider-recorded videos into automated patient communications, websites and digital marketing programs for healthcare practices.
• The partnership uses short, single-topic recordings that can be reused across email, text, websites and social channels instead of requiring separate production projects.
• Provider video can turn frequently answered clinical questions into reusable digital content that supports multiple stages of the patient journey.
• The initial rollout targets independent specialty practices, with the companies identifying hospitals and health systems as potential future applications.
• Historical research cited by the companies found 86% of 1,203 viewer responses indicated that video helped improve understanding of health or treatment information.

Get in touch with our MarTech Experts.

Profound has raised $180 million in a Series D round at a $1.8 billion valuation as the AI-search company expands from visibility analytics into an agentic platform designed to execute marketing work across research, content, advertising and optimization.

Profound is expanding its ambitions beyond helping brands understand how they appear in AI-generated search results. The company has raised $180 million in Series D funding at a $1.8 billion valuation, with Sequoia Capital and Kleiner Perkins co-leading the round.

The financing comes less than seven months after Profound's $96 million Series C. Existing investors including Lightspeed Venture Partners, Khosla Ventures, Saga Ventures, Evantic and South Park Commons also participated. TechCrunch independently reported the financing and valuation.

Profound says the new capital will support product development and applied AI research as it expands its platform for marketing teams. The company reports that it now serves more than 1,000 enterprise brands, including Comcast, Walmart, The Estée Lauder Companies, Zoom, ServiceNow, Figma and MongoDB, and says more than one-third of the Fortune 100 use its platform.

The company's evolution reflects a broader change in AI marketing software. Profound initially focused on helping businesses understand how consumers discover brands through AI search systems. It is now positioning AI Marketer as an agent orchestrator that can interpret those insights and perform marketing tasks.

AI Marketer analyzes brand data and AI-generated answers, identifies opportunities and can deploy specialized sub-agents to execute work. Profound says the system can support activities ranging from competitive research and content refreshes to earned-media discovery, paid advertising analysis and campaign optimization.

A related product, Context Manager, is designed to provide AI Marketer with persistent organizational context. It synthesizes information from knowledge-base files, meeting transcripts and communication threads so that the agent can incorporate a company's positioning and working practices into its outputs.

That context layer is significant because enterprise marketing work rarely depends on isolated prompts. Campaign decisions typically require knowledge of positioning, products, competitors, target audiences, previous decisions and brand guidelines.

Profound is also connecting organic AI-search optimization with paid media through Ads Studio. The company says marketers can create and manage AI-search advertising campaigns, make campaign-wide edits, analyze performance and optimize bidding across OpenAI, Google and Meta advertising environments.

The strategy reflects an emerging view of AI search as a marketing channel rather than simply an analytics problem. As consumers use systems such as ChatGPT, Gemini and Perplexity for product discovery, brands have to consider how their information is represented across a wider collection of third-party sources.

That creates a substantially larger operational workload. Product pages, reviews, editorial coverage, social content, documentation and other sources can all influence how an AI system constructs an answer about a company.

Profound's response is to combine visibility measurement with agents capable of acting on the resulting intelligence.

The timing aligns with broader industry research. Gartner reported in May 2026 that marketing leaders expect AI-driven automation of marketing work to increase from 16% in 2026 to 36% by 2028. Gartner also found that only 30% of surveyed CMOs considered their organizations mature or fully developed in AI readiness.

The challenge, therefore, is moving from AI experimentation to repeatable workflows. Profound is betting that specialized agents, persistent context and proprietary marketing data can provide that bridge.

The company also plans to use the new funding to expand its applied AI research teams in New York and San Francisco. Its research program will evaluate how frontier models perform on complex marketing assignments and develop benchmarks for capabilities such as business understanding, market-signal analysis and cross-functional marketing execution.

Market Landscape

Marketing software is moving from AI-assisted features toward agentic workflows. Gartner's 2026 research identifies agentic AI as an emerging area where marketing organizations are attempting to move beyond pilots and connect AI investments to measurable business outcomes.

Profound sits at the intersection of answer engine optimization, generative engine optimization, marketing intelligence and AI agents. The competitive landscape includes platforms focused on AI-search visibility as well as broader marketing suites adding AI assistants and agents.

The distinction is increasingly about what happens after an insight is generated. Visibility reporting can identify a problem; agentic software attempts to turn that finding into research, content, advertising or optimization work.

Strategic Outlook

Profound's funding round signals continued investor interest in software designed around the emerging AI-mediated discovery environment.

The company's expansion from analytics into execution also reflects a wider change in marketing technology architecture. Instead of adding another dashboard to an existing stack, agentic platforms are attempting to become an operational layer that coordinates multiple tasks across existing systems.

That model raises practical questions around brand governance, accuracy, permissions and measurement. Marketing teams will need to determine which activities agents can execute independently, which require human review and how the resulting work should be evaluated.

Profound's research investment suggests that model capability and evaluation will become part of that equation. As marketing agents take on more complex assignments, the quality of the underlying context and the ability to measure outputs could become as important as raw model intelligence.

Top Insights

• Profound's $180 million Series D values the company at $1.8 billion as it expands from AI-search analytics into broader agentic marketing workflows.
• AI Marketer is designed to interpret brand intelligence and deploy specialized agents across research, content, competitive analysis, advertising and campaign optimization.
• Context Manager gives Profound's marketing agent persistent organizational information from knowledge bases, meetings and communications to support more contextual work.
• Ads Studio connects organic AI-search strategy with paid campaigns across OpenAI, Google and Meta, bringing two increasingly connected discovery channels together.
• Gartner expects AI-driven automation of marketing work to more than double from 16% in 2026 to 36% by 2028.

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