BlackRock Profits US$ 1 Bi With ‘Army of PhDs’ in AI While Oracle Plummets 10.8% - Why These 24 Hours Expose the Difference Between Real Capability and Hype

You know that moment when you're at a party and someone tells you all about some grandiose project, but when you ask “what about the results?” they change the subject? The last 24 hours in the world of AI have been just like that - but with billions of dollars at stake and a brutal lesson in the difference between real technical capability and inflated promises.

While the BlackRock celebrated record results of its systematic investment unit - which uses a veritable army of physicists and PhDs analyzing more than 1,100 market signals with machine learning and had a turnover of almost US$ 1 billion in 2024 -, the Oracle saw its shares plummet 10.8% after revealing that he will need US$ 15 billion more in investments for 2026, without demonstrating when (or if) this will generate a proportional return.

This is not just another piece of market news. It's a watershed that separates those who are building real value from those who are riding the wave of hype. And that matters deeply to all of us who work with AI - from executives making investment decisions to entrepreneurs defining their strategies.

The ‘Army of PhDs’ That's Winning the AI War

Let's start with the winning side of this story. BlackRock's systematic investment unit is not just another department using AI to look modern in corporate presentations. It's a US$ 378 billion under management that attracted at least US$ 40 billion in new resources in the last two years.

What makes it different? Three fundamental elements that I consistently observe in successful AI implementations when I work with companies:

• Deep specialization: The team is led by physicists and PhDs who understand both mathematics and the specific domain (financial markets). They are not generalists promising miracles.
• Proprietary quality dataThey trained their language model with 20 years of financial data creating a real competitive advantage, not just using ChatGPT out of the box.
• Validation capacity: They can demonstrate that their model predicts stock returns more accurately than generic models - and more importantly, they can taste with measurable financial results.

CEO Larry Fink is promoting the division as a model of how AI-supported human managers can outperform the market. Note the emphasis: supported, no replaced. Human analysis skills are still needed for adjustments and unforeseen situations.

In my experience helping companies implement AI, this is precisely the difference between projects that thrive and those that fail. AI isn't stand-alone magic - it's a powerful tool in the hands of experts who know what they're doing.

The Other Side of the Coin: When Investment Becomes a Burden

Now to the less comfortable side of the story. Oracle, which has a US$ 300 billion contract with OpenAI for the cloud, presented weak forecasts that revived concerns about an AI bubble.

The problem isn't that Oracle is investing in AI - it's that its high spending isn't converting into revenue at the expected speed. And the market, which was tolerant of promises, has begun to demand results.

As the Economic Value, Oracle has become a “thermometer of market stress with AI”. The jump in the company's Credit Default Swaps (CDS) - an indicator of credit risk - reinforces its role as an indicator of the risks of complex investments in the artificial intelligence ecosystem.

Investors like Michael Burry (yes, the one from “The Big Short”) are comparing the current situation to the internet boom, warning of overvaluation. And unlike the “hyperscalers” (Alphabet, Microsoft, Amazon), which can demonstrate real demand by struggling to meet data center orders, Oracle is under pressure from the perception that the competition can move faster.

What Does This Reveal About the AI Market?

This disagreement between BlackRock and Oracle is not accidental. It exposes an uncomfortable truth that I have observed in the ecosystem: the market is starting to differentiate between real capacity and promises.

A survey cited by Forbes Brazil shows that 53% of investors believe in an AI bubble - and MIT studies show that 95% of the 300 projects analyzed have not yet made a profit. This is even as UBS projects global spending of US$ 375 billion by the end of 2025 and US$ 3 trillion by 2030.

It's a fascinating contradiction: massive investments coexisting with growing skepticism about returns.

Disney and OpenAI: The Agreement That Changes the Rules of the Game

And while the war between capacity and hype rages on in the financial markets, another strategic move has made headlines: the Disney's US$ 1 billion investment in OpenAI.

This three-year agreement licenses Disney, Pixar, Marvel and Star Wars characters for use in the Sora video model. But it's not just about Mickey Mouse generating cute videos - it's a structural change in the entertainment business model.

Analyst Nicholas Grous of Ark Invest predicts a “pre- and post-AIA” era in entertainment. His thesis is provocative: the saturation of AI-generated content will make the public value human-made content more.

Think about it: in a world where anyone can generate videos with AI, what will be the value of scarcity? Of authentic human labor? Of quality curation?

Disney's strategy is intelligent: saturate the market with AI-assisted content while reserving its high-budget projects for the refinement of more promising concepts. It's using AI to quickly test what resonates with audiences before investing tens of millions in traditional productions.

CEO Bob Iger and ‘Thoughtful and Responsible’ Use’

What struck me was Bob Iger's emphasis on the “thoughtful and responsible” use of generative AI. This isn't just marketing - it reflects Hollywood's hesitancy to embrace AI due to union fears and data use issues.

This agreement signals, in the words of Bloomberg Line, “a capitulation by the entertainment industry to the age of AI”. But it's a strategic capitulation, not a desperate one - setting the rules of the game rather than being run over by them.

AI Architects and Time Recognition

In the midst of this whirlwind of investments, results and strategies, Time magazine made its symbolic choice: it chose the “architects of artificial intelligence” as Person of the Year 2025.

The list includes Jensen Huang (Nvidia), Mark Zuckerberg (Meta), Elon Musk (X/xAI), Fei-Fei Li, Lisa Su (AMD), Dario Amodei (Anthropic) and Demis Hassabis (Google DeepMind). The editor-in-chief said that “no one has more impact in 2025 than the AI builders”.

But experts make a crucial point, quoted by BBC: recognition does not mean that AI systems are reliable and responsible. The future will depend on how millions of people apply this technology.

This is a fundamental distinction that I constantly reinforce in my work: building technology is one thing; using it wisely is quite another.

And in an interesting irony, the Team launches its own AI - an AI agent developed with Scale AI that combines language, speech synthesis and translation. The Poder360 test showed competencies in summaries, but bottlenecks in complete translations. Time recommends using AI as a “partner”, keeping the “human brain in the loop”.

Three Practical Lessons From These 24 Hours

So what should executives, entrepreneurs and professionals take away from this whirlwind of news? Let me break it down into three practical lessons:

1. Real Capacity Surpasses Hype - But Takes Longer

BlackRock didn't build its AI operation overnight. It took years of accumulating data, recruiting experts and refining models. Oracle, on the other hand, is rushing to catch the wave - and the market has noticed.

If you are implementing AI in your company, resist the temptation of instant results. Build solid foundations: quality data, trained staff, well-defined processes.

2. AI as a Partner, Not a Substitute

Notice that both BlackRock and Disney emphasize the role of AI as amplifier of human capabilities. Time talks explicitly about keeping “human brains in the loop”.

This is the right approach. As you write Rafael Parente in GZH, In his opinion, AI can be used as a “thinking partner” - simulating difficult customers, sorting through the daily brain dump, acting as an archaeologist of personal data. But he warns: there is a limit between amplifying human judgment and using it as a crutch.

In my mentoring work with executives, I constantly emphasize this balance. AI amplifies both human qualities and limitations - especially the absence of ethical discomfort.

3. The Market is Maturing - Fast

The fall of Oracle, the skepticism of the 53% who see a bubble, the 95% of unprofitable projects - all this signals a market moving from the infantile phase of “promise a lot, deliver later” to the adult phase of “show results”.

This is great for those who are doing their homework. But it will be brutal for those who are just riding the wave.

Data from the Fortune Business Insights report supports realistic optimism: the global AI market is expected to grow from US$ 294.16 billion in 2025 to US$ 1,771.62 billion by 2032 (CAGR of 29.2%). And SMEs that implement AI could see a 6% to 10% increase in revenue - because AI is a “great equalizer”, allowing small companies to achieve multinational data intelligence.

The Brazilian Context: Advertising Agencies and Journalists

And how is this reflected in Brazil? Two complementary pieces of news reveal our growing maturity.

First, the Google Brazil's annual survey shows that Brazilian advertising agencies have had a leap forward in AI integration in 2025. Six agencies have reached the highest level of maturity, and a significant proportion have migrated to intermediate levels. AI is structurally guiding processes and new offers in the Brazilian advertising market.

Secondly Oxford University study (Reuters Institute) on British journalists - but which reflects global trends - reveals an interesting paradox: 62% see AI as a threat, against only 15% who see it as an opportunity. But even so, 56% use AI weekly for tasks such as transcription, translation and grammar checking.

The most revealing? Those who use AI on a daily basis are the less pessimistic about its impact. Practical use transforms perceptions - further evidence that familiarity with the tool reduces fear and increases the ability to judge its real value.

The Case of the IBGE: When AI Creates New Challenges

AI is not all about opportunities and growth. Sometimes it creates completely new challenges that we need to solve.

THE IBGE postpones release of 2022 Census microdata for 2026 due to the “high risk” of data confidentiality being breached by Artificial Intelligence tools, which can re-identify people even in unnamed data.

This is a perfect example of how AI not only transforms what we can do, but also requires us to rethink existing policies and procedures. The president of IBGE, Marcio Pochmann, confirms that the advance of AI requires a revision of the confidentiality policy to guarantee statistical secrecy, in accordance with the LGPD.

This delay impacts scientific publications and the formulation of public policies, as researchers depend on this micro-data for detailed analysis. It's a real cost of adapting to the AI era - but a necessary cost to protect fundamental rights.

What does this mean for you?

Let's go back to the initial question: why does all this matter?

Because we are living in a time when AI is no longer a futuristic promise but an operational reality. And in this transition, the gap between those who master technology and those who are mastered by it is widening rapidly.

BlackRock demonstrates what is possible when you combine deep expertise, proprietary data and strategic vision. Oracle shows the risk of throwing money at the problem without any real ability to generate value. Disney reveals how established players can use AI strategically without losing their essence. And IBGE reminds us that every technological advance creates new ethical and governance challenges.

If you're an executive, the question is no longer “should we invest in AI?” - it's “how do we build real capacity instead of accumulating costs with no return?”

If you're an entrepreneur, the opportunity lies in being like the SMEs mentioned in the Fortune report: use AI as a great equalizer to compete with bigger players, not in promising to be the next AI unicorn without a solid foundation.

If you're a professional, the path is clear: familiarize yourself with the tools, but keep the human brain in the loop. As the study with journalists shows, those who use it on a daily basis are less pessimistic because they understand both its potential and its limitations.

Building Real Capacity in AI

After years of working with startups, companies, governments and support entities, I have identified a clear pattern in the organizations that thrive with AI versus those that waste resources:

The winners treat AI as a strategic capability, not an IT project.

They invest in:

• AI literacy for leadership and teams - not for everyone to become a data scientist, but to understand possibilities and limitations
• Data infrastructure before sophisticated algorithms - because AI without quality data is like a Ferrari without gasoline
• Controlled experimentation with clear metrics of success - starting small and scaling up what works
• Governance and ethics from the outset - not as an obstacle, but as a competitive advantage
• Partnership between humans and machines - using AI to amplify human judgment, not replace it

And the losers? They buy expensive solutions promising miracles, implement them without a clear strategy, expect magical results and blame technology when they fail.

The gap between these two groups is widening - and fast. As Oracle's fall shows, the market is losing patience with broken promises.

The Window of Opportunity Is Open - But Not For Long

These 24 hours of news reveal a fundamental truth: we are in the middle of a massive reorganization of winners and losers.

Companies like BlackRock, which built real capacity, are reaping billions. Organizations like Oracle, which bet big without demonstrating a return, are under increasing pressure. Established players like Disney are using AI strategically to protect and expand their businesses. And the whole chain - from advertising agencies in Brazil to journalists globally - is discovering that practical familiarity with AI is the best answer to fear.

The window of opportunity to position your organization on the winning side is still open. But it is closing as the market matures and differentiates between real capacity and hype.

It's not time for panic - it's time for strategic and informed action.

In my mentoring and consulting work, I help executives and companies through this very transition: building real capacity in AI that generates measurable value, not pretty projects in presentations that drain resources with no return. If you want to understand how to position your organization to be the BlackRock of your industry - not Oracle - now is the time to act.

Because at the end of the day, the difference between success and failure with AI isn't in the technology itself. It's in how you use it. And that, fortunately, is a choice that is still in your hands.