1,000 Days In: Mapping the Generative AI Disruption

When disruption is gradual, you adapt at the edges. But when it arrives all at once, you need high ground—or you drown. 

The past 1,000 days have felt like that kind of flood. Since ChatGPT’s release in late 2022, generative AI has surged from novelty to infrastructure—rewiring how we write, code, plan, decide, and secure. This wasn’t a quiet shift. It was a detonation. 

And the deeper story isn’t just about scale. It’s about speed—and scope. We’re not watching a wave crest. We’re watching it sweep through the core of business and security, remapping the landscape in real time. 

The Velocity Gap: AI vs. Internet vs. Cloud 

Every modern tech revolution has changed the world. But none have moved like this. 

• The Internet took ~15 years to reshape commerce and communication. 

• Cloud computing compressed that curve to ~10 years—upending IT but mostly behind the scenes. 

• Generative AI changed everything in under three years. From ChatGPT’s 100 million-user debut to AI features embedded in nearly every enterprise tool, it went from demo to default in less time than it takes most companies to reorganize.

More telling: this wasn’t just adopted by technologists. AI showed up in sales decks, in HR workflows, in boardrooms and Slack channels. This disruption began at the edge—and worked its way inward. 

But rapid adoption isn’t the whole story. The floodwaters are still rising. And not every foundation is built for it. 

The Three-Front Disruption 

This isn’t a single thread shift. It’s hitting every business across three deeply interconnected lanes.

1. The Economics of Work and Software

AI didn’t just make software cheaper to build—it made it faster, more accessible, and infinitely flexible. 

• First drafts now write themselves. 

• Minimum Viable Products are weekend projects. 

• A team of three with AI can match the output of thirty without it.

The old software development bottlenecks—budget, headcount, time— have been shattered. What cloud did to infrastructure, AI is doing to software. Anyone with a prompt and a browser can now create niche, usable software to solve a problem on-demand. 

That erases any conventional software moat. 

What used to protect enterprises—custom applications, slow-moving process chains, internal tools guarded by IT—can now be replaced by a weekend coder with an agent-based automation stack. The rise of AI has turned bespoke into baseline. 

Shadow IT has exploded, and with it, the complexity of governance. If anyone can build it, anyone will. And they’ll deploy it across cloud platforms you don’t monitor in coding ??languages your security team doesn’t audit.

2. Cybersecurity’s New Texture

But AI doesn’t just create more software. It changes the limits of what software is and fundamentally shifts what business problems can be solved by software alone. 

Modern software now has pieces that are non-deterministic. It reasons. It responds. It can be manipulated by language alone in its input data or led into hallucination. That means the threat surface for modern software isn’t just bigger—it’s weirder. 

• Prompt injection is now a top risk. 

• Model manipulation, jailbreaks, and data leakage are live concerns. 

• Attackers can generate polymorphic malware in minutes—and so can defenders.

But here’s the real strategic shift: language itself is now part of your attack surface. We’ve moved from firewalls to “trust layers,” from static scans to real-time reasoning about the intent of the things your software is processing. 

And if your AI outputs (aka: any modern software) are touching customer experiences, financial decisions, or critical business flows, then “good enough” isn’t good enough. AI governance is now cybersecurity hygiene. The only thing worse than an insecure model is a misaligned one.

3. The Human Core

Even as AI eats software, some roles remain fundamentally human—and the importance of these roles, to a business,  have increased substantially.    

• Judgment: knowing when to say no to an AI suggestion. 

• Alignment: understanding what the AI should do versus what it can do. 

• Relationships: trust still requires a face, especially when everything else is automated. 

• Accountability: someone must decide whether to click “approve.” 

The AI+human pair is now the atomic unit of knowledge work. Just like power tools redefined skilled labor, AI is reshaping what it means to be a competent professional. The skill isn’t beating the AI—it’s piloting it. 

The professionals who thrived in past revolutions weren’t the ones who outperformed the machines. They were the ones who knew how to use them better than anyone else. In the age of AI, prompting, reviewing, and aligning outputs with business risk is the new craft. 

Strategy Takeaways in the Age of Cheap Code and AI 

In medieval times, castles were moats. Then gunpowder arrived, and stonewalls didn’t matter. Today, many businesses are still guarding stone—manual processes, human middleware, and slow-cycle software. 

The revolution already happened. Now the question is: do you have a defensible position? 

If you lead in business or security, here’s what the first 1,000 days of AI have made clear: 

• Speed alone is not strategy. Alignment is. In a world moving this fast, your only safety is clarity—of goals, of governance, of who’s responsible for the AI’s actions. 

• The moat is trust, not tooling. Your proprietary data, your oversight systems, and your ability to align AI with your customers’ real needs, that’s your edge. 

• Cybersecurity isn’t just about protection. It’s about enablement. Modern security teams must match the attackers in speed and imagination. AI-assisted defense is a must. So is AI-assisted red teaming. 

• Skills are being redefined. If AI can do your job for 1/1000 of the cost, your value lies in how well you direct it, not in how well you used to do it yourself. 

The Next 1,000 Days 

This isn’t anywhere near the end of the arc. It’s the beginning of a new information explosion. Just as every company became a software company in the cloud era, every team and modern software application is now being blended with AI. 

But this wave isn’t giving anyone a decade to adapt. 

So, look at yourself and your organization. Ask yourself:
What has changed in the last 1,000 days—and what hasn’t, but must? 

Because disruption doesn’t wait. It doesn’t slow down. And it favors those who learn, lead, and align faster than the disruption can outpace them. 

Your moat is gone. The platform is shifting. But the high ground? That’s still up for grabs.

Bio for Alexander Feick

Alexander Feick is Vice President of Labs for global cybersecurity company, eSentire.  Feick leads a team responsible for fostering innovations for eSentire’s MDR platform and integrating new technologies, including generative AI security, into the company’s services.