Insights & news

Dear C-Level, If in my previous article I highlighted that Artificial Intelligence (AI) is essential for the survival of your business, now it's time to focus on what really matters: Return on Investment (ROI). The enchantment phase with Generative AI has passed; Now we need a practical and strategic approach. The market predicts that AI will add trillions to the economy, but many companies are still unhappy with the results. The problem is not technology, but the lack of a clear strategy and adequate data. As someone who has developed expertise in AI, from the use of no-code tools to the strategic use of OPEN AI's CODEX and multiple agents through orchestrator in N8N, I have learned that the difference between hype and real profit is in value-driven execution.

Article 2: Uncovering the Black Box: Essential Fundamentals and the Language of Strategic Command Generative Artificial Intelligence (GIA) has captured the attention, imagination and concern of most business leaders around the world. The "honeymoon" with IAG is over; Now, the leader needs to build the "marriage" with strategy and governance. For us, executives, the priority is no longer just to experiment, but to understand the working mechanism of AI to shield the organization against the hype and, crucially, master the skill that generates the fastest Return on Investment (ROI): Prompt Engineering.

Article 1: AI is not Cost, it is Survival: Why Great is the Enemy of Good in Technology Adoption

If AI is still an “IT project” in your company, you are already behind. And the data shows exactly how big this delay is. Leading AI companies generate $10.30 in return for every $1 invested. The market average? Only $3.70. The difference is not in technology. It's in the strategy. Only 5 to 11% of AI projects reach production. This means that 95% of pilots die before generating real value. The problem is not technical — it is leadership. The CRAFT Framework that we present in the article solves this with a 5-dimensional approach: Capabilities, Readiness, Alignment, Feasibility and Timeline. It's not theory — it's a roadmap for CEOs who need to make decisions now. Some data that should change your perspective: - 27% of the tasks professionals perform with AI are completely new — things that simply didn't exist before. - Teams with AI produce 40 to 50% more output without increasing headcount. - The Innovation Basket concept allows allocating investments in AI without compromising the core business. But there is one point that few CEOs consider: Duty of Care. Not adopting AI when it can protect employees, customers and shareholders already constitutes a fiduciary risk. AI is no longer an optional competitive advantage. It is a strategic obligation.

I consolidated more than 10 hours of content from the biggest global governance and AI forums — from CEOs at Goldman Sachs, JPMorgan, and BlackRock to Brazilian board debates — into an article for those who need to make decisions, not write code. Some data that draw attention: 📊 82% of companies report positive ROI with AI ⚠️ But 95% of AI projects fail before they scale 🔒 80-100% of AI tasks require active human supervision ⏱️ Cycles of 4-8 months tablets to 2 weeks 💰 Prompt caching reduces AI operational costs by up to 90% The article covers 4 dimensions that every advisor and president should master: 1. Strategy — From “Conversational AI” to “Agentic Delegation” 2. Governance — Oversight frameworks, dual-use risks, data sovereignty 3. ROI — Real cases: TELUS, Zapier, Rakuten, Fountain, CRED 4. Brazil — How our councils are (or should be) dealing with the topic If you lead people and also need to lead the adoption of AI in your organization, this is the starting point.