Zombie businesses and the leadership gap: Why AI is exposing the unfit

Some businesses may look busy. Their teams are delivering, meetings are happening, and systems are running. But under the surface, they’re not innovating, not investing, and not evolving.

They’re surviving. Not scaling.

These are what we call zombie businesses.

Matt Bennett puts it plainly in Episode 64 of The Innovation Room:

“I still speak to businesses each week who have an AI ban… that’s probably a terminal zombie business.”

In today’s AI-driven market, delayed decisions, legacy thinking, and fear-based inaction aren’t just inefficiencies. They’re signs of slow death. The divide is widening between companies using AI to create scale and those quietly falling behind.

This article is a wake-up call. It’s designed to help you assess whether your organisation is on the path to scalable productivity or stuck in survival mode. More importantly, it outlines how leadership can course-correct before the gap becomes fatal.

Want to hear the full conversation?
Listen to Episode 64 of The Innovation Room: “Zombie Businesses in the Age of AI - A Wake-Up Call for Leaders”  

In 2025, a zombie business isn’t one that has collapsed. It’s one that continues to operate without truly moving forward. These companies are still delivering projects and maintaining operations, but beneath the surface, there’s no meaningful growth, no strategic investment, and no capacity to adapt to change. They are stuck in maintenance mode, often relying on legacy clients, outdated systems, or institutional momentum.

What makes these businesses particularly vulnerable today is the pace at which AI is accelerating competitive advantage. Companies that once appeared stable are now being left behind, simply because they failed to evolve when it mattered. Many were artificially propped up during periods of low interest rates or government-backed support, but those conditions have faded. In the current market, survival now depends on the ability to reinvent, not just sustain.

The root of the issue isn’t just operational, it’s cultural. Zombie businesses are often shaped by leadership teams who approach change reactively. AI is seen as a distant concept or a risky disruption, rather than a practical opportunity. These organisations hold back from experimenting, delay key decisions, and in some cases, avoid AI altogether. This reluctance signals a deeper resistance to growth, one that ultimately puts the entire business at risk.

A clear divide is forming across industries between organisations using AI to scale and those stuck managing legacy systems with legacy thinking. While some businesses are embedding AI into daily operations and unlocking new levels of productivity, others are hesitating, experimenting cautiously, or simply not moving at all.

This isn’t just about technology adoption. It’s about speed. In a landscape where AI tools are evolving monthly, delays of even a few quarters create disproportionate consequences. Falling behind is no longer a minor setback. It compounds over time, creating a widening gap in capability, customer experience, and growth potential.

The real cost of hesitation isn’t measured in missed tools. It shows up in more strategic losses like talent walking out the door because internal systems are slow, inefficient, or outdated. It shows up in declining relevance as competitors automate processes, personalise experiences, and deliver faster outcomes at lower cost. And it shows up in compressed margins, as manual-heavy operations struggle to keep up with AI-augmented rivals that are achieving more with fewer people.

This divide isn’t theoretical. It’s already visible. The businesses that scale with AI are gaining momentum. The ones that delay are not just slowing down. They’re decaying.

The biggest obstacle to AI adoption in many organisations is no longer the technology. It’s leadership.

While teams on the ground are exploring tools, testing prompts, and pushing for automation, executive decision-making often lags behind. In many cases, AI readiness exists across departments, but without top-down direction, that energy never scales. The result is isolated pilots, scattered experimentation, and a lack of strategic momentum.

Leadership hesitation tends to come from two places. Either the executive team is still treating AI as a theoretical concept rather than an immediate priority, or they’re approaching it with excessive caution, waiting for a perfect roadmap instead of enabling controlled experimentation. Both approaches stall progress. They signal uncertainty to teams, delay investment, and leave early adopters unsupported.

This disconnect is particularly damaging because AI has become deeply operational. It’s no longer a future phase in a transformation plan, it’s already reshaping how decisions are made, how time is spent, and how value is delivered. The longer the leadership waits to engage, the wider the gap becomes between internal capability and external opportunity.

Bottom-up AI adoption can create pockets of progress. But without a clear executive narrative, prioritisation framework, and cultural alignment from the top, it rarely scales. Leaders don’t need to master the tech, they need to remove the friction.

One of the challenges with zombie businesses is that they rarely look like they’re in trouble, until it’s too late. On the surface, things may appear stable. Teams are busy, projects are active, and pipelines are still moving. But under the surface, these businesses are slowly disconnecting from what makes them competitive.

If you’re in a leadership role, here are some of the early warning signs worth paying attention to:

• You’re still relying on outdated processes. If manual workflows, legacy systems, or spreadsheet-driven decision-making still dominate day-to-day operations, you’re not positioned to scale.

• There’s no meaningful AI experimentation happening. Whether it’s a formal ban or informal resistance, a lack of hands-on engagement with AI tools is a strong indicator of organisational stagnation.

• AI is discussed as a future goal, not a current capability. If your strategic roadmap talks about AI in the context of “the next three years,” you’re already behind. The technology is moving faster than that.

• There’s no plan for reskilling your workforce. Without a structured approach to build AI literacy and embed new capabilities across teams, your competitive edge will continue to erode.

• Your culture discourages experimentation. If teams feel unsafe to test, learn, or fail quickly with new tools, innovation won’t scale. Psychological safety is foundational to adaptation.

These signs are not superficial. They point to deeper issues in leadership alignment, organisational pace, and adaptability. Spotting them early gives you a chance to course-correct before the gap becomes too wide to close.

The leaders adapting fastest to AI are not waiting for permission, playbooks, or perfect timing. They are engaging directly and building confidence through hands-on use.

AI-ready leadership is not about technical expertise. It is about curiosity, consistency, and momentum. These leaders use AI tools to support their workflows, prioritise more effectively, and reflect on how they spend their time. For many, AI becomes a personal operating system that helps track progress, sharpen focus, and uncover blind spots.

Matt Bennett follows a simple but powerful routine. At the end of each day, he tells the AI what he achieved, where he struggled, and what needs attention next. The tool responds with structure and suggestions. Over time, this habit creates a feedback loop that builds clarity and forward motion.

When leaders use AI in this way and share what they learn, it sends a clear signal to the wider team. Experimentation is encouraged. Learning is visible. Progress is shared.

This approach is not about programming. It is about prompting. Leaders who learn to frame questions well and iterate with context are already operating differently. They are more decisive, more adaptive, and more aligned with how modern organisations need to think and act.

The gap between businesses that scale and those that stall often comes down to leadership behaviour. Many organisations are not falling behind because of a lack of tools or talent, but because decision-making is slow, experimentation is limited, and priorities are unclear. Leaders need to examine where progress is being blocked and where energy is being lost.

A simple way to begin is by running a focused ten-day AI experiment. Choose one real problem that exists today. Apply a practical AI tool and measure its impact. This should be quick, visible, and tied to actual business outcomes. If you are unsure where to begin, the Geeks AI Agent Lab can help you build and test a tailored AI prototype for your business in just ten days, giving you measurable results without unnecessary risk.

The path to scale rarely starts with a masterplan. It starts with one team that is given permission to move. Leaders who act early create momentum and clarity. Those who wait risk building strategies around conditions that no longer exist. The time to move is now.

To explore these ideas in more depth, listen to Episode 64 of The Innovation Room: "Zombie Businesses in the Age of AI." In this conversation, Matt Bennett joins me to unpack how AI is exposing outdated leadership models, what zombie businesses look like in 2025, and what forward-thinking leaders are doing differently.

Listen now 

In this episode, we discussed:

• How to recognise a zombie business before it’s too late

• Why falling one year behind in AI feels like falling five

• Practical ways leaders are using AI in their day-to-day

• What happens when bottom-up momentum hits a top-down block

If you're leading a team, setting direction, or shaping digital strategy, this episode offers a practical lens to assess where your business really stands.