Via Hyperadaptive Solutions

And the key to this was: we knew that we wanted a brief. We didn’t know that we wanted an AI-capable, multi-agentic ecosystem in order to get to it. We just wanted to get a really good brief.

— Operationalizing AI: Best Practices and Real-Life Success Stories, at 22:15

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GMR Marketing’s successful AI journey began not with a desire to implement AI, but with a specific business problem: the need for a “better creative brief” to increase margins and elevate creative output.

Max Lenderman explains, “We knew that we wanted a brief. We didn’t know that we wanted an AI-capable multi-agentic ecosystem in order to get to it. We just wanted to get a really good brief.” This focus allowed them to identify the precise point where AI could act as a “steroid” to augment their process.

• Goal-oriented initiation: Starting with a clear business objective, such as achieving higher margins or improving creative output, grounds AI efforts in tangible value and measurable outcomes.
• Iterative development: GMR created an MVP (Minimum Viable Product) for brief generation, allowing their solution to evolve from a simple tool into a complex “Experience Engine” over time.
• Data leverage: The agency’s extensive “SOLE” Science (String Of Lights Effect) data proved critical, highlighting the immense value of proprietary data sets in training specialized AI tools for specific business needs.
• Avoid “random acts of AI”: Without a clear business goal, organizations risk experimenting with tools aimlessly, leading to an estimated 80% failure rate due to a lack of strategic focus.

By focusing on the desired outcome, organizations can strategically apply AI, ensuring that technology serves the business’s core objectives rather than becoming an end in itself.