Marketing Processes Broken? AI Will Break Them Faster

Many years ago, I spent almost two years helping a major organisation make a fundamental change. At the end of the project, we succeeded. We posted two posts on this ‘new platform’ called Instagram. That’s right, it took two years to complete three board presentations, numerous meetings and two Instagram posts, writes Alison McKinnon, managing director at CM.OSX. 

Excessive caution can slow innovation. But today we’re seeing the opposite dynamic. Organisations are adopting AI faster than many can effectively govern it to speed innovation and scale growth.

But while AI can scale great strategy and empower organisations, it allows mistakes to happen faster, more frequently and at a greater scale. It can rapidly scale errors and magnify organisational failures, thereby also slowing down innovation.

AI scales whatever system exists, even if it is terrible

A persistent misconception about AI is that automation automatically improves outcomes. But the fact is, AI scales whatever system already exists.

If your processes are effective, your data is reliable and your controls are strong, AI can accelerate performance and increase productivity. But if your processes are inconsistent, your controls are weak or your decision-making is flawed, AI can accelerate those outcomes too.

Technology does not automatically improve quality. It increases the speed and scale at which work is performed. Historically, human error was largely self-limiting. One employee makes a mistake, one campaign is affected, one report contains an error. And typically, the impact can be contained and corrected before it spreads.

AI changes that equation. A flawed prompt, an incorrect business rule or a poorly designed workflow can be replicated hundreds or thousands of times before anyone notices. What was an isolated error can quickly become a system-wide issue.

The risk here is that AI can repeat mistakes with extraordinary efficiency because AI is an amplifier, of both the good and the bad.

The key challenge: the speed of AI is outpacing governance

Almost all organisations have mature governance frameworks in place for finance, procurement, HR and legal obligations. But AI adoption in most organisations is happening through experimentation, some structured, some not. Someone connects as a tool, buys a subscription, connects an API, launches a workflow. Suddenly AI is operating inside the business before governance has caught up – or before the business is even aware.

The fact is AI adoption is moving faster than most organisations’ ability to govern it.

Shadow AI is becoming the new shadow IT

Shadow AI is emerging for the same reason shadow IT did: people are trying to solve real business problems faster than formal systems can respond. Employees are experimenting with tools, building prompts, creating workflows and uploading information into AI platforms, often with good intentions and

little visibility. What leadership sees as a handful of approved tools may be a growing ecosystem of unofficial AI use across the organisation.

The risk is not experimentation itself. The risk is unmanaged experimentation at scale. Without clear governance, organisations lose visibility over what data is being used, which outputs are being trusted, where decisions are being influenced and who is accountable when something goes wrong. Shadow AI may accelerate productivity in the short term, but without guardrails it can also scale privacy, compliance, brand and operational risk just as quickly.

Scale changes the risk equation

We can all recount a mistake we make – Our CEO remembers the time she sent 50,000 Calendars to print with the wrong logo. A typo in a brochure is annoying. A hallucination published across 50,000 customer communications is a crisis.

This is where many organisations underestimate the impact of AI. The risks associated with a small pilot program and those associated with enterprise-wide deployment are fundamentally different.

As automation scales, so does the potential impact of inaccurate outputs, biased recommendations, compliance breaches and governance failures. What might once have been a contained issue can quickly become a systemic one.

The more organisations rely on AI to drive decisions and execute workflows, the more important governance becomes. Scale does not simply increase efficiency; it magnifies both value and risk.

The governance conversation eventually becomes an accountability conversation

We talk a lot about capability – What can AI do? How quickly can it be deployed? How much productivity can it create? But as AI becomes embedded in business-critical processes, a different set of questions begins to emerge. Who is accountable when an AI-generated recommendation leads to a poor decision? Who approved the model? Who designed the workflow? Who validated the outputs? And who is responsible when something goes wrong?

The reality is that governance is ultimately about accountability. Organisations have established frameworks that define responsibility for financial decisions, legal compliance and operational risk. AI will be no different. As regulatory scrutiny increases and AI becomes more deeply integrated into how organisations operate, leaders will need clear answers about ownership, oversight and decision-making authority.

And AI agents do not appear in courtrooms. Brands do. Regulators such as the ACCC, privacy commissioners and industry compliance bodies will not hold the AI model accountable for breaches, misleading conduct or governance failures. The business, its executives and its governing teams remain legally and commercially accountable for the final output.

And when AI is influencing decisions at scale, accountability cannot be automated. It must be designed into the system from the beginning.

Governance is an enabler, not a barrier

In the new world full of possibilities that AI is opening, governance sounds boring. In reality, it is what makes enterprise-scale AI possible.

Without it, organisations cannot trust outputs, manage risk or scale adoption with confidence. Because AI will amplify whatever exists inside the system. Strong processes become stronger and weak processes become weaker. Good decisions scale and bad decisions scale faster.

Every organisation wants AI to accelerate productivity. Good governance is the foundation that makes that possible.

Published in B&T

https://www.bandt.com.au/marketing-processes-broken-ai-will-break-them-faster-2/