AI gold rush
In 2025, we are in the AI arms race. Almost every tech company and more businesses in almost every industry (from finance, healthcare, manufacturing, etc.) claim to be an AI company.
As generated AI tools, large language models and machine learning continue their mainstream parade, executives are clamoring for headlines on their AI plans. Despite a massive influx of press releases and media marketing, most AI vendors find themselves lost in the noise and have little coverage.
This is not due to media interest in AI. In fact, artificial intelligence is one of the most popular topics in today’s technology journalism. The problem is the quantity: loose torrents of announcements, buzzwords and renamed heritage tools that make the line between innovation and imitation. For journalists, such content economies present a real challenge as they strive to distinguish signals from noise.
Media landscape drowned by “AI”
From traditional newspapers and technology blogs to niche newsletters, industry podcasts and Tiktok interpreters, the media ecosystem has exploded with new media channels. Across all of these channels, a new wave of AI-related news comes every day, including new open source models, research papers, investments, product integration and thought leadership articles.
Nowadays, AI is common in almost every major sector. In finance, companies are launching algorithmic trading systems and fraud engines. In healthcare, AI powers diagnostic imaging, predictive modeling of treatment plans, and drug discovery algorithms. In manufacturing, it drives vision systems for quality control and predictive maintenance tools. In retail, logistics, energy, and education, existing tools are often hastily reshaped into AI-powered, often based on third-party large language models with minimal proprietary development.
The result of this saturation is that journalists are filled with the same sounding tone. When every company claims to be changing its industry with AI, novelty becomes thinner. The vendors who announced that they added chatbots to the platform no longer aroused meaningful interest.
result? Every company hates listening to two words from reporters. “I will pass.” Otherwise they will not respond to your stadium at all. Either way, this is not good.
Why giants always catch the spotlight
Media coverage often attracts a group of familiar tech giants. Openai, Microsoft, Google and Meta dominate not only because of their innovations, but because they have resources that attract attention.
These companies enjoy name recognition, make substantial investments in research and development, and have always announced billion-dollar funding rounds and flagship product launches.
Consider some recent developments. As Reuters reported, Openai received $4 billion in financing led by SoftBank. According to Reuters, Alphabet invested $7.5 billion in capital expenditure on AI infrastructure in 2025. Since 2019, Microsoft has invested $13 billion in Openai, according to Bloomberg.
These stories naturally attracted media attention because they combine scale, relevance and urgency. Also, a lot of cash. For smaller suppliers, breaking into the spotlight without billions of dollars in capital or blockbuster products requires a very different approach.
Reporter’s Hawkeye: Suspicion and Proof
The current AI media climate is a censorship. The initial wave of AI Euphoria has been suppressed by moral debates, misinformation issues and a huge array of product claims. As a result, journalists became more acute about how they handle AI stories.
Today’s reporter asked a difficult question. They wondered whether a company developed a proprietary AI model or just wrapped the GPT-4 in a new interface. They require proof in the form of ROI, performance metrics and realistic usage data. They look for customer recommendations, benchmarks and peer-reviewed research.
Companies that provide vague statements such as “we use machine learning to improve operations” are unlikely to gain coverage. Suspicion is the default, especially if the vendor cannot confirm its claims.
Hype cycle and its dissatisfaction
We enter an era where the term AI is expected to release attention and funding at nearly every touch point, from pitch deck to press releases. But, as Gartner hype cycle repeatedly proves, over-promotion leads to inevitable disillusionment.
Media fatigue is growing. Hyperbolic languages such as “changing games” and “revolutionary” are often flat unless they are measurable. Worse, companies that exaggerate their capabilities can be overlooked or publicly reviewed.
Experienced communicators understand that credibility is more than just a buzz. The most compelling AI narrative combines ideal goals with clear evidence of execution. They not only provide a vision, but also a way to realize it.
Breakthrough: Today’s PR script for AI vendors
For emerging AI vendors, it takes a strategic and substantial approach to stand out in today’s media environment. The key is to be specific and journalist-friendly.
The focus of the niche helps. Suppliers should not make broad claims, but should highlight breakthroughs in vertical vertical aspects. For example: demonstrate how AI solutions can reduce false positives in fraud detection by measurable percentages than general statements about how AI will bring innovation to fraud and security. Prove impact is crucial.
The lifeblood of the impact is data. ROI, performance benchmarks and client quotations provide journalists with the materials they need to evaluate and communicate value.
Third-party verification by analysts or independent experts enhances credibility and visibility. Suppliers should also focus on building long-term relationships with journalists by providing access to technology leaders, early product previews or exclusive insights.
Finally, know what media audiences are looking for in communication. Newsletters benefit from short, timely, data-backed Blurbs. Trade publications often require in-depth interpreters or written Q&A. Top journalists may need multiple conversations before citing subject matter experts or writing products.
In short, suppliers must prioritize specificity, reputation and media unity.
Conclusion: From quantity to value
Attention is precious in today’s AI gold rush. It has not been awarded the loudest supplier or the most gorgeous jargon. It is those who provide real, differentiated impact.
As media censorship intensifies, AI vendors must develop from simply broadcasting their functions to displaying their results. The good news is that smart, stark stories still have a chance. The road to headlines in 2025 is not to be loud. It’s about being smarter.
