Council Post: Could AI Unlock A New Internet Of Brand Partnerships?

Tejas Manohar is the cofounder/co-CEO of Hightouch.

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For years, marketers have talked about partnerships as one of the most powerful ways to grow a brand. Retail media networks, co-branded campaigns, loyalty integrations, affiliate ecosystems, sponsorships and shared audiences all promise a version of the same idea: When two brands work together effectively, both companies can reach consumers with more relevance and credibility than they could alone.

The value of partnerships has never been in question. What holds them back is the operational complexity behind them.

Most brand collaborations still move slowly because every partnership requires layers of coordination across legal teams, creative reviews, brand guidelines, media planning, approvals, localization and channel customization. The standard workflow is already time-intensive for one brand, and a partnership at least doubles it, then adds the work of making the two versions agree. Even relatively straightforward collaborations can, in my experience, take weeks to launch. At scale, the process becomes almost impossible to standardize because every company protects its identity differently.

This is where AI can change the picture, and the change goes deeper than producing content faster.

Over the last year, I have seen many companies experiment with generative AI for marketing content creation. The results were mixed. Most large brands discovered that foundation models could generate content quickly, but they struggled to consistently produce work that aligned with the voice, tone, compliance standards and visual identity that define modern brands.

I believe the next phase of AI adoption will likely focus less on generic generation and more on context. Brands need systems that teach AI how the company communicates, how products are positioned, which phrases are acceptable, how visual hierarchy works and what "on brand" actually means internally.

The good news is that marketers don't need to wait for this shift to begin. Many of the building blocks already exist. In order to make progress, organizations need to treat AI less like a creative tool and more like a knowledge layer. They must give AI access to brand guidelines, approved messaging, legal guardrails, past campaign examples and product positioning so it understands how the company operates before it's asked to create anything. From there, they can apply AI to the most operationally intensive parts of partnerships, like adapting creative across channels, preparing assets for review or localizing campaigns, all while keeping people responsible for strategy and final approval. That foundation makes it much easier to scale collaboration as the technology matures.

Once that context layer exists, a new kind of collaboration could become possible.

Every company should maintain what could effectively become a "brand passport." Instead of static PDF guidelines buried in shared folders, brands should create structured, AI-readable context layers containing tone rules, visual standards, product positioning, audience preferences, channel priorities, legal requirements and campaign examples.

Now imagine two companies combining those passports dynamically.

A retailer and an advertiser could work through AI systems that understand both brands simultaneously. AI could generate creative assets tailored for specific placements while automatically balancing which brand should lead the experience depending on the environment. A campaign appearing on a retailer's website might prioritize the retailer's identity first, while an off-site email campaign could elevate the advertiser's voice more prominently.

Operationally, that changes everything for brand partnerships.

Today, much of this work requires large teams manually reconciling competing brand standards across multiple rounds of approvals. AI introduces the possibility of compressing timelines dramatically while still maintaining brand integrity.

The deeper benefit is competitive. This could shift the balance between the open internet and the walled gardens.

One reason major platforms have become so dominant is that they simplify execution. Brands can launch campaigns quickly within centralized ecosystems that already control the audience, creative formats and measurement infrastructure. Cross-brand collaboration outside those ecosystems often requires far more coordination.

If AI can reduce the friction involved in partnership execution, brands may have a greater incentive to collaborate directly across retail networks, publishers, commerce platforms and independent ecosystems. The operational burden may become lighter, while the quality and personalization of those collaborations may improve.

The broader implication is that AI may not simply automate advertising workflows. It could expand the number of partnerships that are economically feasible in the first place.

When collaboration becomes easier, brands experiment more. They can localize campaigns faster, tailor creative to more environments and test more combinations of audiences, products and experiences. Entire categories of partnerships that currently feel too expensive or operationally complex can suddenly become realistic.

For marketers, that may become one of AI's most valuable contributions: not replacing creativity, but making collaboration scalable.

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