Vbrick, a leading provider of Enterprise Video Platform (EVP) services, has announced a new integration with ServiceNow. The integration allows companies to use video assets stored within Vbrick as a “data layer” for generative-AI workflows inside of ServiceNow’s AI assistant capability, Now Assist. This turns what had been passive video content into structured intelligence, where transcripts, summaries, metadata, and semantic context are ready on demand, thus opening the door to video-based generative AI applications across business processes.
With this capability, users will be able to search, retrieve and surface relevant video content within ServiceNow workflows-for knowledge-sharing, support, training, customer service, or internal communications-enriched by AI metadata and summaries. Vbrick’s Chairman and CEO, Paul Sparta, said the move “unlocks a new frontier” where video becomes a dynamic, context-aware data layer powering smarter, faster and more human workflows.
The integration is available now through the ServiceNow Store and can be enabled within existing Vbrick + ServiceNow environments in enterprises.
What this means for video marketing: turning video archives into generative AI assets.
The Vbrick–ServiceNow alliance may at first seem like an enterprise-internal productivity upgrade. However, it carries broader implications for the video marketing industry, through fundamental changes in how video content will be managed, reused, and leveraged across businesses.
From static video libraries to dynamic video-data assets
Traditionally, corporate video content-training sessions, webinars, and internal announcements-sits in archives. Marketing teams seldom tap these assets post-publication. With Vbrick’s AI metadata-transcripts, semantic tags, summarization-and integration with generative-AI workflows, video libraries suddenly become searchable, actionable assets. Marketers can quickly discover past footage, repurpose snippets for campaigns, or generate new content based on insights mined from existing video.
This effectively turns “video marketing” from a one-time production cost into a long-term data investment, meaning video content gains in compounding value over time as part of a reusable video-content AI repository.
Enabling Scalable, AI-Powered Video Content Workflow
ServiceNow + Vbrick lets organizations automate many aspects of video content management: indexing, summarization, retrieval, and even the generation of video-based knowledge responses. Marketing departments or agencies could route common customer or internal queries to a “video knowledge base” rather than producing new content each time, reducing repetitive content creation tasks and lowering time and cost per deliverable.
For instance, a support team might automatically surface training clips to solve recurring issues. A marketing team might offer short video explanations for FAQs, all with minimum human intervention.
Lifecycle Integration: Video as part of business workflows, not just marketing channels
Since Vbrick‘s integration embeds video directly into enterprise workflows like self-service, support, and knowledge management, it really blurs the boundary between marketing video and enterprise video. Video becomes a part of the business operation itself: internal training, customer support, onboarding, rather than just external marketing.
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This convergence means video marketing agencies may increasingly service not only traditional marketing campaigns, but internal corporate functions, training & support, compliance, and enterprise communications.
Demand Growth for Video Marketing + AI Expertise
With video libraries as data sources, demand will likely increase for marketing agencies and content creators skilled in AI-augmented video production, metadata optimization, and strategic reuse. Agencies offering “video-as-data” services cataloguing, indexing, repurposing old video for new uses, generating AI-driven video summaries or micro-videos may find new business opportunities.
Companies investing in building solid video-content archives and metadata pipelines can see greater returns on investment in their video marketing spend over time.
Impact on Businesses Operating in the Video Marketing Industry
Marketing Agencies & Video Production Firms: Those that adapt to this trend-agencies offering added value on top of one-off video creation, such as video library management, AI-powered content search and repurposing, and workflow integration-could find themselves differentiating their offerings and opening up recurring revenue streams.
Large Video Archives: Enterprises with large repositories of videos can unlock value by repurposing that content instead of creating new ones, reducing cost and speeding go-to-market cycles: training videos, webinars, and past marketing campaigns.
SaaS/Enterprise-tech Vendors: Vendors building tools around video content, such as analytics, DAMs, and content-management systems, will be required to integrate AI metadata, video search, and generative-AI support in their offerings as Enterprise demands evolve.
Content Creators & Freelancers: There may be higher demand for creators who can work with AI-augmented workflows – e.g., extract short clips, create meta-content (summaries, captions), adapt old content for new marketing campaigns.
Training & Internal Comms Teams: Through video knowledge embedded across workflows, organizations have the ability to streamline onboarding, training, and support, enhancing user experiences and reducing manual documentation efforts.
Risk & Challenges to Consider
Metadata Quality & Relevance: The metadata in videos, such as transcription, tagging, and summarization, needs to be accurate and relevant if generative AI is to perform well. Poor quality metadata could lead to incorrect content retrieval, miscommunication, or misuse.
Content Governance & Privacy: With rich media content becoming deeply ingrained in enterprise workflows, perhaps containing sensitive internal or customer data, it becomes crucial that access controls are appropriate, privacy compliance is maintained, and storage is secure.
Dependence on Proprietary Platforms: The integration ties video content and AI workflows to the respective Vbrick and ServiceNow ecosystems. Vendor lock-in and loss of portability may result when companies switch platforms later.
Strategy Needed: To realize full value, businesses need thoughtful content-management strategy: deciding what video to archive, how to tag it and how to structure metadata for future reuse. Otherwise, video libraries risk becoming unmanageable.
Skill Gap: Staff need to be trained to work with AI-augmented video workflows, search metadata, and integrate video into broader business functions, possibly requiring new roles.
Conclusion
The integration of Vbrick with ServiceNow is an important inflection point for the video-content and video-marketing industry: video is no longer just a one-time marketing asset; it’s becoming a living, structured layer of enterprise data, ready to fuel generative-AI workflows, support business operations, and power both marketing, training, and support functions. As more organizations adopt this model, the boundary between marketing video and enterprise video will blur. Video marketing will shift from episodic campaigns to ongoing content lifecycle management. Agencies that evolve to support this lifecycle, embracing AI-powered video services and content repurposing, will be at a competitive advantage.