Hightouch is adding a veteran of Google’s advertising business to its leadership team as the data infrastructure company looks to make AI agents a more active part of how agencies and brands plan, build and execute advertising campaigns.
The company announced the appointment of Jitendra Kumar as Head of Commercial, Advertising. Kumar spent two decades at Google and most recently led U.S. agency partnerships, giving him experience across advertising platforms, agencies and major advertisers.
The move comes as Hightouch pushes deeper into agentic marketing, a model in which AI agents can use customer data, brand context and marketing tools to perform tasks that have traditionally required marketers to work across multiple systems.
Hightouch Bets on Data as Advertising AI’s Next Advantage
The strategic argument behind Hightouch’s advertising expansion is relatively straightforward: as advertising platforms automate more of the media-buying process, marketers may gain less competitive advantage from simply operating those platforms and more from the quality of the data and business context they provide to them.
That distinction is becoming increasingly important across programmatic advertising and digital media.
Platforms operated by companies such as Google, Amazon and Microsoft already use machine learning and automation to optimize campaign delivery, bidding and audience decisions. The next layer of automation is moving toward systems that can interpret business objectives, identify opportunities, generate creative and coordinate execution across multiple marketing channels.
Hightouch wants its Agentic Marketing Platform to sit closer to that layer.
The platform combines customer data, brand information and marketing orchestration capabilities so AI agents can work with the information and tools required to support marketing decisions. Its advertising capabilities include Ad Studio, which is positioned as part of the company’s broader effort to connect data and campaign execution.
For advertisers, the proposition is less about adding another AI assistant to the marketing stack and more about connecting AI to the underlying systems where customer and campaign data already live.
Why Kumar’s Google Background Matters
Kumar’s appointment also gives Hightouch an experienced operator with relationships across the advertising ecosystem.
At Google, Kumar spent 20 years working across the company’s advertising business and ultimately led U.S. agency partnerships. His new responsibilities at Hightouch will include developing relationships with holding companies, independent agencies, advertising platforms and the brands they serve.
That agency focus is significant.
Large agencies frequently operate across fragmented media environments, data platforms, creative systems and measurement tools. AI agents could theoretically reduce some of that operational complexity, but only if they can access reliable first-party data and execute actions across existing marketing infrastructure.
This is where Hightouch is positioning its data layer as a potential differentiator.
Instead of treating generative AI as a standalone content or productivity tool, the company is pursuing a model in which AI agents can act on business data and execute workflows. In advertising, that could eventually include identifying audiences, informing creative development, recommending campaign actions and coordinating execution across channels.
The harder problem is not generating an AI recommendation. It is giving an agent enough trusted context and controlled access to actually do something with that recommendation.
The Broader Shift Toward Agentic Advertising
The advertising industry is already moving toward greater automation. DSPs, retail media networks, social platforms and other media-buying environments increasingly use algorithms to determine bids, audiences, placements and optimization strategies.
Agentic AI could extend that automation upward into campaign planning and orchestration.
That creates a competitive landscape involving several layers of the advertising technology stack. Google and Amazon control major media ecosystems and can combine advertising inventory with enormous amounts of platform data. Salesforce and Adobe approach the problem from customer data, CRM and marketing-cloud infrastructure. NVIDIA, meanwhile, supplies much of the underlying computing infrastructure powering increasingly sophisticated AI systems.
Hightouch is taking a different route by emphasizing the connection between first-party data, AI agents and marketing execution.
That could appeal particularly to enterprises that already have sophisticated data environments but struggle to make those datasets usable across marketing workflows.
The company’s challenge will be proving that agentic marketing can move beyond demonstrations and deliver measurable improvements in campaign performance, speed and operational efficiency. Enterprise marketers will also need clear controls around permissions, privacy, brand safety, attribution and human oversight before autonomous systems can take meaningful actions in live advertising environments.
Hightouch’s Funding Gives the Strategy More Room to Scale
The appointment follows Hightouch’s reported $150 million Series D financing at a $2.75 billion valuation earlier this year. The company says it has grown more than 100% annually over the past two years.
That funding provides the company with significant resources to expand its platform while the market around AI-powered marketing infrastructure is still taking shape.
The bigger question is whether businesses will adopt agentic systems as another software category or begin treating them as a new operating layer across the marketing stack.
Hightouch is clearly betting on the latter.
For agencies and enterprise advertising teams, that could eventually mean fewer manual handoffs between customer data platforms, creative tools, media-buying systems and reporting environments. But the value of such a system will ultimately depend on whether AI agents can operate reliably within those environments while preserving the controls marketers need.
Kumar’s arrival gives Hightouch an executive with direct experience navigating the advertising ecosystem at scale. The next test will be turning that experience, combined with Hightouch’s data infrastructure, into an advertising platform that can make agentic marketing useful beyond experimentation.
Market Landscape
The advertising technology market is shifting from isolated AI features toward broader automation of campaign workflows. Google, Amazon, Salesforce and Adobe each have substantial positions across advertising, customer data, marketing automation or measurement, while specialist platforms continue to compete around data activation and orchestration.
For Hightouch, the opportunity is to occupy the connective layer between enterprise first-party data and the increasingly automated tools marketers already use.
That positioning could become more valuable as third-party signals weaken, privacy requirements increase and advertisers demand greater accountability from AI-driven campaign systems. First-party customer intelligence becomes more strategically important when automated platforms are making more decisions on a marketer’s behalf.
The agentic advertising model therefore depends on two things moving together: better access to trusted data and tightly governed AI execution.
Top Insights
- Hightouch appointed former Google advertising executive Jitendra Kumar to expand its agentic marketing strategy across agencies, brands and advertising platforms.
- The company’s Agentic Marketing Platform connects first-party customer data, brand context and marketing tools so AI agents can support advertising workflows.
- Hightouch is positioning trusted first-party data as a competitive advantage as DSPs, retail media platforms and other systems automate campaign decisions.
- Kumar’s agency-partnership experience could help Hightouch navigate fragmented advertising ecosystems where data, creative, media buying and measurement remain disconnected.
- Enterprise adoption will depend on measurable ROI, privacy controls, governance and reliable human oversight as AI agents move closer to campaign execution.
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