Small steps, Big unlock

We're in interesting times, especially when it comes to the state of leadership. Many CEOs are still caught between two worlds: one where they print out emails to mark them up by hand, and a new era where AI is radically changing the nature of work. Our Founder, Nina, sat down with Damien Woods, an expert in L&D, to explore the significant role AI is playing in how leaders lead and execute strategies. And the shift isn't just happening in boardrooms. Damien shared an anecdote that brings this closer to home: his son would ask Damien a question, then immediately fact-check his answer using AI to verify whether what his father had told him was accurate (even knowing that AI is not always accurate). This is the next generation, and the one after that, using the internet not to explore, learn, or play with information, but simply to summon it. It's safe to say a lot has changed, and that change is accelerating.

That acceleration is precisely where many leaders are struggling. Change is never easy, and it's not uncommon to feel nervous about new ways of working. Right now, there is no shortage of content about what AI can do for your business, but when work speeds up and decisions follow that pace, something important is exposed: structural weakness. This is one of the core issues we believe will surface as more and more organisations adopt AI without considering its place in the organisational ecosystem. In this blog, we break down why AI isn't a fix-all for structural dysfunction, and how to ensure your organisation is designed to handle the increased velocity that technology brings.

AI amplifies the system you have

AI is a force multiplier. If you give a high-performance tool to a broken process, you simply reach a failing conclusion faster. The problem isn’t the tool itself; the real issue is whether your organisation is designed to use them well, and, if it is, where AI fits in and at what point in the delivery it is most effective. Whether your current systems are strong or weak, AI will uncover the integrity of your organisational systems. Below are three things AI will uncover if you implement it and your organisation is not ready:

If roles are unclear, AI amplifies confusion.

When accountabilities are poorly defined, introducing AI creates ownership drift. Without a clear owner for specific outputs, the speed of AI-generated content leads to overlapping responsibilities and a lack of clear oversight. Instead of empowering staff, it creates a vacuum where no one is certain who is responsible for the final prompt, the verification, or the outcome.

If services are poorly aligned to strategy, AI accelerates inefficiency.

AI is exceptionally good at doing things quickly, but it cannot determine if those things are worth doing. If your service delivery is not tightly coupled with your strategic objectives, AI will allow your team to produce irrelevant outputs at a higher volume. You risk becoming efficiently useless, spending resources to generate high-quality work that does not move the needle on your actual goals.

If decision rights are blurred, AI increases noise.

Effective AI implementation requires fast, decisive governance. If your organisation struggles with a consensus culture or undefined decision rights, AI-generated data and options will burden your leadership. Without a clear framework for who decides what, the increased velocity of information leads to analysis paralysis and a surge of conflicting data points that obscure the path forward.

This is not to say that AI is evil and we should not explore using it, Damien even goes onto say, “AI is a fundamental game changer for the nature of work,” and, “It's no longer OK not to be really curious in this space and in fact more than curious, being active and investing in it." Because those who are will get ahead. But first, we need to start with the fundamentals so that we are using AI as an effective tool, not another tool that will just make more noise and stray from the business goals.

The "Performance Partner" Mindset

One of the biggest takeaways from our chat was that leaders often treat their support teams like order-takers. You feel a friction point in the business, and you instinctively ask for "Training X" or "App Y." But the better path is to find a Performance Partner, someone who won’t just build what you ask for, but will sit down and unpick the business problem first.

Damien shared a story from his time at a large Australian bank where a senior leader wanted to rebuild six out-of-date e-learning modules. Damien’s response? "You're going to have me back in six months because they'll be out of date again. This isn't efficient." Instead of a static course, they built curated social media feeds of industry experts. It was free, it was real-time, and it actually solved the performance gap. Designing training is one thing, but designing systems that your people are actually capable of using is where you’ll see the return on investment. We don’t have to invest in more "modules" just because that’s the way it’s always been done. We can think creatively, so the solution evolves with the business rather than becoming a "set and forget" relic.

Looking at this as a case study, here is what Damien did really well.

1. Find the root cause for the performance problem.

He challenged the initial brief. Instead of accepting a request for "six e-learning modules," Damien interrogated the utility of the request. He identified that the high rate of change in the industry made static content a liability, not an asset. By focusing on the half-life of the information, he prevented the organisation from investing in a set-and-forget relic that would have been obsolete by the time it was deployed.

2. Then design the service or workflow.

He prioritised workflow over training. Traditional training often creates a friction point because it requires staff to leave their work to learn. Damien integrated the solution into the natural flow of work. By curating social media feeds of industry experts, he turned professional development into a real-time, passive activity. This reduced the cognitive load on the employees while keeping their knowledge current.

3. Then select the technology that supports it.

He chose cost-effective longevity over expensive redundancy. Building bespoke modules is capital-intensive and requires ongoing maintenance. The curated feed solution leveraged existing, free, high-quality external data. This approach redirected the internal spend from content creation to system design, ensuring the solution evolved automatically as the industry changed, without requiring further budget cycles.

Why this works? Because Damien took a human-centric approach when he designed the system that would support the need. Like Damien, our team adopts the same approach, and this is how we ensure that strategy isn’t just executed, but embedded into the teams and workflows that are actually going to use it.

The "Trolley Cheat Sheet" (A Reality Check)

Transitioning from theory to implementation is where most digital strategies fail. It is easy to advocate for "innovation," but far more difficult to ensure an AI tool survives the practical constraints of a high-pressure work environment.

Damien applies a strict Human-Centred Design (HCD) lens to vet every proposal. Before any capital is committed, the solution must pass three specific tests:

· Feasibility: Do we have the technical infrastructure and internal skill sets to build and maintain this?

· Desirability: Does this solve a genuine frustration for the staff, or is it an unwanted imposition?

· Viability: Can this be executed long-term within the existing operational budget and daily cadence?

The Reality of Workflow Integration

We often over-invest in what is "feasible" (the tech works) or "desirable" (it looks impressive), but fail on viability. If a tool does not integrate seamlessly into how work actually happens, it will be ignored.

Damien’s experience with a retail frontline team serves as a functional reality check. His team developed a sophisticated digital interface designed to provide real-time learning for floor staff. However, when tested on-site, the feedback was immediate: the tool was a hindrance.

A staff member pointed to a laminated paper "cheat sheet" taped to his stock trolley. For that worker, the 20 seconds required to stop, unlock a mobile device, and navigate an app were a barrier to his primary task. The paper sheet was superior because it was a zero-friction intervention integrated into the physical workflow.

The Lesson: De-Risking via Observation

The only way to de-risk a technology investment is to observe the user in their actual environment. If an AI tool is less convenient than a piece of paper taped to a trolley, the adoption rate will be zero. Technology must adapt to the worker’s reality; you cannot expect the worker to change their physical workflow to accommodate a sub-optimal digital tool.

Here is what to do next

To manage the transition into an AI-integrated workflow without creating organisational dysfunction, leaders must provide a stable environment for experimentation. You do not require a comprehensive, multi-year AI strategy to begin; you require a framework that de-risks the process through small, measurable steps.

The Pilot Approach

Rather than a broad rollout, use a structured pilot approach to ensure the technology actually solves a problem. This moves the focus from "what the tool can do" to "what the business needs to achieve."

1. Define the Outcome: Identify the specific performance metric or business result you are trying to improve.

2. Map the Current Workflow: Document exactly how the work happens now, without the influence of new tech.

3. Identify Friction Points: Pinpoint where the process slows down, where errors occur, or where cognitive load is highest.

4. Introduce AI Strategically: Implement the tool specifically where it meaningfully reduces the identified friction.

5. Measure and Adjust: Review the impact against your original outcome and adjust the system intentionally before committing to a full-scale rollout.

Something to think about

Before thinking that AI will fix the gaps in your business, it is worth noting that, as we have discovered, AI is an enabler. If your operating model isn’t ready, it will expose that quickly. We know this for a fact because we help leadership teams with this support every day. We help them uncover the root cause of the dysfunction, create an operational model and flow that is centred around the teams that use it.

Not sure where to start? Three6 can help you there with a discovery workshop.

Contact us for more information.