From Firefighting To Foresight: Why AI Is Becoming Humanity’s First Window Into Tomorrow

By Doug Shannon
Forbes Technology Council
Nov 13, 2025

Doug Shannon is a global leader in digital transformation, specializing in AI, GenAI and intelligent automation.

For most of human history, we have lived in a reactive world.

A fire breaks out, and we send people running. A virus mutates, and we scramble to update vaccines. A supply chain fails, and we call it a black swan and play catch-up.

Entire systems, from governments to enterprises, have been built on the idea that risk cannot truly be seen until it has already landed. The best we managed was probability: forecasts, models and dashboards. They told us what might happen, but rarely gave us a chance to act before the storm hit.

That era is ending.

We are entering what I call the Age of Pre-Cognition. AI models no longer simply process history; they are beginning to perceive what is about to come. Civilization is stepping into a world where we can anticipate events before they manifest and take meaningful action in advance.

What Pre-Cognition Really Means

Pre-cognition may sound like science fiction, yet in practical terms it means this:

• Reactive: Responding after the event. A hurricane hits, then we evacuate.

• Proactive: Preparing for general categories of risk. We know hurricane season is coming, so we stock supplies.

• Pre-Cognitive: Perceiving specific events before they land and allocating resources precisely. We know where and when the hurricane will make landfall, so we move people and supplies ahead of time.

This is not abstract theory. It is already happening.

The Pattern: Models That Learn the World, Not Just Words

AI began by learning language. Now it is learning reality itself, the physics, chemistry and biology of the systems we depend on.

• Health and Disease: MIT’s VaxSeer forecasts dominant flu strains months before they emerge, giving vaccine developers lead time. EVEscape predicts viral escape mutations, helping us prepare countermeasures before pathogens adapt.

• Weather and Climate: DeepMind’s GraphCast generates 10-day forecasts in seconds, often outperforming traditional models. Google’s Flood Hub provides flood predictions up to seven days ahead across 80 countries, protecting lives in regions that lacked early warning.

• Wildfires: ALERTCalifornia and WIFIRE combine cameras, satellites and AI to detect fires faster and forecast spread, turning minutes of warning into hours.

• Solar Threats: NASA and IBM’s Surya predicts solar flares up to two hours before impact. Released openly on Hugging Face, it allows enterprises, researchers and governments to protect satellites, grids, aviation and even astronauts.

Why This Is Different From Past Hype

Skeptics will say every technology has its hype cycle.

Although there is truth to this, I cannot help but think that this time the difference is more existential. Past bubbles promised productivity, connectivity or entertainment. The potential of pre-cognitive AI is about resilience, survival and foresight.

When we can see tomorrow’s threats today, it changes how everything works:

• Public Health: Instead of mass infections, vaccines and treatments can be pre-allocated.

• Energy and Infrastructure: Instead of cascading blackouts, grids and satellites can be protected before storms.

• Enterprises: Instead of supply chain collapse, shipments can be rerouted before bottlenecks choke global trade.

• Insurance and Finance: Instead of catastrophic losses, portfolios can be hedged with foresight built in.

The Human And Existential Dimension

At its core, this shift is not only about industries or enterprises. It is about humanity’s relationship with time itself.

For centuries, we lived with lag, the gap between when an event occurred and when we could respond. That lag defined wars, pandemics, economic crashes and natural disasters. Entire histories were written in the ashes of our inability to see early enough.

Now that lag is closing.

AI, trained on immense datasets of physics, biology and human behavior, gives us glimpses of what comes next. It does not make the future certain, but it makes it visible enough that choices can change. Lives can be saved. Economies can be shielded. Societies can be steadied.

What Enterprises Must Do

The organizations that thrive in the Age of Pre-Cognition will be those that stop treating AI as a tool for efficiency and start treating it as an early warning system for resilience.

This requires:

• Resilience Intelligence Stacks: Observatories for data ingestion, domain models like Surya or GraphCast, decision rails linking forecasts to playbooks and connectors that turn alerts into enterprise actions.

• Governance That Builds Trust: Using alignment, clarity and transparency (ACT). Document data sources through a chain of custody, clarify reasoning through a chain of thought and explain actions through a chain of reasoning.

• Pre-Activation Drills: Practicing the handoff from model output to human decision to enterprise action. The question is not only whether the model is accurate but also whether the organization can act fast enough.

The Bigger Picture

This is not about AI replacing humans. It is about AI extending human foresight. Civilization is moving from reactive firefighting to pre-cognitive resilience. From scrambling after the fact to preparing ahead of time. From living in lag to living closer to tomorrow. Enterprises that embrace this shift will look as though they can see the future. Those who do not will look permanently surprised, stuck in firefighting mode, while others quietly move pieces into place.

The question is not whether pre-cognitive AI will arrive. It already has. The question is whether we will be ready to act when tomorrow becomes visible today.

THAT’S A WRAP!

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December was a month of extremes in funding, with Bay Area startups collecting more than $25B. There were eighteen megadeals, with seven of them more than $200M and three billion-dollars plus. Databricks' $4.08B Series L closed on the last day of the year, demonstrating again that there is no lack of ready investment for late stage AI infrastructure companies to stay private.

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Early Stage:

• Cultivo closed a $14M Series A, accelerates investment into nature at scale.

• Traini closed a $7.5M Series A, innovates the way to communicate with pet dogs using generative AI and a cognitive wearable device.

• Double Blind Bio closed a $5.6M Seed, developers of DeBBy, the world's first AI-powered growth agent built to help research teams close more trials with less effort.

• Aravolta closed a $5.1M Seed, provides data centers with infrastructure management (DCIM) software, and digital twins, regulatory reporting, and autonomous control.

• Givefront closed a $2M Seed,the Financial Management Platform built for nonprofits

Growth Stage:

• uLink Labs closed a $8.6M Series B,developing a groundbreaking wireless implantable device and remote monitoring system designed to enable personalized heart failure management

• Resynergi closed a $6.4M Series B, an advanced recycling technology company accelerating plastic circularity to protect human health and the environment.

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