Leveraging Proprietary AI Systems to Drive Brand Accountability

Leaders from Mastercard, Newell Brands, and Uber Advertising suggest that the best way to use AI is not just for adoption, but to clear away operational hurdles so human creativity can focus on emotional connection. This shift moves marketing away from a focus on performance alone toward contextual utility, where brands succeed by offering help when the consumer needs it most. The real advantage for leaders is to stop using AI for raw volume and instead build proprietary systems, such as AI personas or commerce media networks, that create lasting value. Those who balance algorithmic efficiency with human storytelling will win the attention that competitors, who are focused on superficial metrics, are currently losing.

The hidden trap of bullspend and performance metrics

Modern marketing dashboards often provide a false sense of security. As the conversation notes, teams often optimize for impressions because they are easy to measure, even when those numbers do not lead to actual pipeline growth. The industry calls this bullspend.

The problem is a reliance on vanity metrics that offer quick, positive feedback while hiding a lack of real business results. The move toward attention metrics, as Uber Advertising explores, tries to fix this by pairing eye tracking and duration data with actual research.

"It is not about viewability or attention, it is about accountability for us. What we are trying to do is start to tell our partners that these media surfaces matter and when you can actually start to innovate with the measurement firms to get to that place, it becomes a lot more meaningful to us."

-- Edwin Wong

When brands move from simple viewability to accountability, they stop acting as simple fulfillment channels and start providing relief and release. By aligning with the immediate needs of the consumer, brands can shorten the funnel and create a lasting advantage that performance tactics cannot match.

AI as an orchestrator, not a content factory

A common mistake is treating AI as a tool for mass content generation. Newell Brands uses a different approach: human initiated, AI amplified workflows. By using AI to handle tedious tasks, such as coding emails or creating digital twins for product shoots, they cut production cycles from eight weeks down to one or two.

The key is that by automating the boring parts of the creative process, teams save time and free up human capital to focus on the emotional core of the brand. This requires strict safeguards. Newell Brands avoids hallucinations by training AI on proprietary data. This creates a competitive advantage: while competitors use generic AI models that produce similar content, companies building proprietary systems ensure their AI output stays true to their specific brand voice.

The 12-18 month payoff: building proprietary moats

The most important insight is the move toward proprietary infrastructure. Mastercard’s development of a commerce media network is a prime example of big bet innovation. By combining existing assets, such as transaction data, loyalty platforms, and personalization tech, they created a new business line in under a year.

"We looked at what are big bets and new businesses as a network business, which is what we are. What are the kind of businesses we could be in and diversify from our traditional line of business? And the assets were all sitting right there."

-- Cheryl Guerin

This strategy requires patience that most organizations lack. It involves moving past a performance only mindset to justify investments in multisensory branding. While a CFO might question the return on investment for a restaurant experience, the result is a measurable increase in brand trust, which grows over time. The advantage goes to those who can map these soft brand signals back to hard transaction data, proving that emotional resonance is a driver of growth.

Key action items

• Audit your bullspend: Over the next quarter, identify which metrics in your dashboard are vanity based, such as impressions, and replace them with accountability based metrics, such as attention duration or purchase incrementality.
• Implement human initiated AI workflows: Audit your creative supply chain to find tedious tasks like coding or asset formatting and automate them. Ensure every output is reviewed by a human to maintain brand voice.
• Build proprietary personas: Instead of relying on generic LLMs, develop AI personas trained on your own consumer data. Use these to test innovation concepts before going to market.
• Shift from product to context: Over the next 6-12 months, move your advertising strategy toward contextual relevance. Align offers with the immediate need or location of the consumer rather than just demographic targeting.
• Develop a big bet infrastructure: Identify underutilized internal assets like data, loyalty programs, or tech platforms and explore how they can be combined to create a new revenue generating network. This is a 12-18 month investment.
• Measure soft signals: If you are investing in brand experiences, establish a way to link those experiences back to brand perception and long term usage. Use this data to defend top of funnel spend to your CFO.