Marketing in the Age of AI: Turning the Code Red into Competitive Advantage

OpenAI’s Sam Altman made tech headlines in December 2025 after declaring “code red” in response to Google’s release of Gemini 3. Not only is OpenAI now racing with a newer AI model that boasted a one-day rollout, but it is also burning through cash, with analysts estimating that by the next decade, the tech startup will have lost $140 billion since 2024.

Once the clear AI leader, OpenAI fell behind in the AI race as other tech giants like Google, Meta, and X subsequently introduced AI models. Yet according to experts, OpenAI’s recent challenges signify something more concerning for the entire industry: an AI bubble and a looming crash. From overevaluating products to repackaging generic models, tech companies are increasingly attempting to rapidly grow large user bases and generate revenue quickly with AI models that do not provide genuine consumer value.

For new AI startups to be successful and compete with existing tech, they cannot add to the carnage of generic programs and instead must create human-driven solutions by identifying market needs and focusing on organic growth.For new AI startups to be successful and compete with existing tech, they cannot add to the carnage of generic programs and instead must create human-driven solutions by identifying market needs and focusing on organic growth.

Understanding Market Needs

In just the three years since ChatGPT, Sora and several other “AI for everyone” models have been rolled out, criticism of these AI platforms has skyrocketed as consumers are frustrated with their generic blueprints and inability to solve meaningful problems. This is emphasized in studies where respondents report that nearly half of AI tasks are ultimately unwanted or unapplicable. Add to this the numerous industries like agriculture and manufacturing that are lagging in AI adoption, partially due to the lack of accurate, useful AI models.

AI models that solve real problems are more likely to become both useful and sustainable, adapting alongside rapidly evolving technology. To build a trusted, widely adopted platform, a startup must first identify market needs, analyze consumer behavior, and evaluate competitors through targeted research. These insights form the foundation of a strong go-to-market strategy and increase the likelihood of successful market entry.

Market Entry: Synthetic Growth vs. Organic Growth

It’s no secret that AI models face high operational costs as well as the need to create affordable solutions for the average consumer. Combined with the pressure to penetrate the market early and become the next blockbuster hit, many startups’ go-to-market strategies rely too heavily on synthetic growth, like massive early investments and circular financing with other tech companies, to bolster their platforms. These external investments too often provide little ROI for startups, and many business experts are noting the challenges startups face when investing billions of dollars early on without planning on how the AI model will monetize itself in the future.

What these startups fail to include in their business plans are organic growth strategies, which directly address important consumer desires like personalized experiences, streamlined workflow, and consumer adaptability, just to name a few.

Take Scale AI, the data infrastructure company creating and providing AI-generated resources that help other entities train and utilize their own AI models and technology. The AI startup has built its success heavily on organic growth strategies, including but not limited to starting off with small pilot projects, creating adaptable solutions that grew with market shifts, and collaborating closely with clients to build custom solutions. Yes, Scale AI still had to prove its value quickly, as all startups do, but before entering the market, the startup understood the need to monetize and, in response, applied and created solutions that could guarantee long-term growth.

To enter the market both effectively and efficiently requires the use of purposeful organic growth strategies. Even the seemingly smaller organic growth strategies like SEO and keyword optimization are just as crucial as thought leadership tactics and can be the difference between being dubbed a reliable or useless AI platform.

Creating AI Models that Last

AI is here to stay, but the question remains: will the market experience a crash if startups and tech companies continue to introduce flashy, generic models that only provide short-term solutions with no ultimate monetization? In the extremely short time period that AI has been universally accessible, it is already clear that AI platforms are missing the human-driven piece that offers long-term usage.

ARTÉMIA Communications assists AI startups and scaleups with effective marketing strategies and helps them build market entry campaigns focused on creating meaningful solutions that result in enduring success.