In a village just outside Nairobi, a multinational company funded the construction of a new water pump. A ribbon was cut. Smiles were photographed. A press release declared: “Clean water for all.”
But within months, the pump broke. No one had been trained to repair it. No local ownership, no follow-up. The company moved on. The community didn’t.
This is the story of too many corporate social good efforts. A good deed, performed once, and then forgotten. A billboard where there should’ve been a blueprint. An applause line where there should’ve been a legacy.
We live in an age where companies are expected to stand for something beyond profit. Climate justice. Equity. Mental health. Community resilience. These aren’t just trends. They are tectonic shifts in public expectation.
But according to a new 2025 benchmarking report, Understanding the Emerging Field of Evaluation in Corporate Social Good, most companies are still struggling to answer one basic question:
Let me be clear: doing good without knowing what’s working is not just inefficient—it’s irresponsible.
You can’t fix what you won’t face. You can’t grow what you won’t measure. And you can’t lead if you don’t listen to the data.
The Three I’s of Modern Impact
If we want to close the yawning gap between intention and outcome, between the glossy brochure and the lived reality, we need a new operating system for corporate responsibility—one built around three fundamentals:
Intention — The moral will to do good.
Information — The data and tools to know what’s working.
Integrity — The courage to act on what you find.
Right now, we’re short on the second and starving for the third.
This report lays it out plainly. While C-suites talk the talk, only 10% of companies invest in building evaluation capacity. Fewer than a third bring nonprofit partners into the process of interpreting results. And most treat evaluation as a PR function, not a feedback loop. It’s not learning—it’s laundering.
That has to change.
Because when metrics are vague and budgets are thin, we get performative philanthropy: theater instead of transformation. We measure smiles, not systems. We celebrate moments, not movements.
What Companies Can Do—Today
This isn’t just a critique. It’s a call to action. Every company that claims to stand for something has a responsibility to build a better way. Here’s where to start:
1. Fund Evaluation Like It Matters If your impact budget doesn’t include evaluation, you don’t have a strategy—you have storytelling.
2. Hire or Train the Right People Would you trust your financial reporting to an untrained intern? Then why leave impact measurement to chance?
3. Use What You Learn Insights aren’t trophies. They’re tools. They should change how you fund, partner, and show up in the world.
From Vanity to Vision
Too often, corporate impact is measured in impressions, not improvements. Headlines, not healing. We must reject the comfort of performative good in favor of a radical accountability—one that listens, learns, and leads with truth.
Because the world doesn’t need more promises. It needs proof.
And proof begins with a simple, courageous question: “What changed?”
What if the future of artificial intelligence was already mapped out—month by month, twist by twist, like a Netflix series you can’t stop binging but also can’t stop fearing?
That’s what AI-2027.com offers: a meticulously crafted timeline by Scott Alexander and Daniel Kokotajlo that projects us forward into the near-future of AI development. Spoiler: It’s not science fiction. It’s disturbingly plausible. And that’s the point.
But this isn’t just a speculative sci-fi romp for AI nerds. It’s a psychological litmus test for our collective imagination—and our collective denial.
The Future Has a Calendar Now
The site lays out an eerily realistic month-by-month narrative of AI progress from 2023 through 2027. The breakthroughs. The existential questions. The human reactions—from awe to panic to collapse.
It feels like a prophetic script, written not in the stars, but in Silicon Valley boardrooms.
But here’s the uncomfortable twist: The most shocking thing about this speculative future is how… reasonable it sounds.
We’re not talking about Terminators or utopias. We’re talking about:
AI models quietly overtaking human experts,
Governments fumbling to regulate something they barely understand,
Entire industries made irrelevant in quarters, not decades,
A society obsessed with optimization but allergic to introspection.
Is This a Forecast—Or a Mirror?
What makes AI-2027 so fascinating—and so chilling—isn’t just its content. It’s the format: a timeline. That subtle design choice signals something terrifying. It doesn’t ask “if” this will happen. It assumes it. You’re not reading possibilities; you’re reading inevitabilities.
That’s how we talk about weather. Or war.
The real message isn’t that the timeline will come true. It’s that we’re already living as though it will.
The Comfort of Fatalism
There’s a strange comfort in deterministic timelines. If AI will do X in June 2026 and Y in October 2027, then we’re just passengers on the ride, right? There’s no need to ask messy questions like:
What kind of intelligence are we really building?
Who benefits from it?
And who is being erased by it?
The AI-2027 narrative doesn’t answer those questions. It forces you to.
Luxury Beliefs in the Age of AGI
This timeline exists in the same cultural moment where billionaires spend fortunes on yacht-shaped NFTs while workers are told to “reskill” for jobs that don’t yet exist and may never come. We’re living in a dystopia disguised as a tech demo.
In this context, AI isn’t a tool—it’s a mirror held up to power. It reflects a world that prioritizes acceleration over reflection, data over wisdom, and product releases over public good.
So What Now?
If AI-2027 is right, then the time to think critically about what we’re building—and who we’re becoming—is now. Not in 2026 when the genie’s out. Not in 2027 when the market’s crashed and ethics panels are writing blog posts in past tense.
This timeline isn’t a prophecy. It’s a provocation.
The future is being imagined for us. The question is: do we accept the script?
