For over eight years, Propel Ventures has been at the forefront of product thinking in Australia—helping businesses not only build great products but also embed a strong product mindset across their organisations. A true product-led business isn’t just about having product managers—it’s about ensuring that everyone understands the broader business context, is connected to customer needs, and continuously iterates to refine product-market fit.
Why AI is Exposing Gaps in Agile
As industries across food, logistics, and retail reposition themselves as tech-enabled businesses, many are realising that Agile alone is not enough. Agile has helped optimise engineering delivery, but it doesn’t inherently ensure that companies are building the right things. With AI unlocking new opportunities, businesses need a clear way to prioritise investments and align technology with strategic goals. This is where a Product Operating Model (POM) becomes critical.
A well-defined Product Operating Model helps businesses move beyond feature-driven roadmaps and focus on outcome-based product development. However, many organisations lack mature product management capabilities. Instead, we often see BAs or project managers rebranded as product owners or product managers, without the necessary upskilling in product discovery and strategic thinking. The result? Backlog-driven development that delivers outputs rather than real business and customer value.
For businesses serious about scaling AI adoption, these weaknesses in product management and Agile delivery are now being exposed.
The AI Shift: From Cost Cutting to Revenue Growth
AI adoption has followed a familiar trajectory. Early investments focused on cost-cutting and efficiency gains—what we call the "corporate Ozempic" approach. These quick wins were attractive because they provided measurable savings with low risk. However, once costs are optimised, the benefits plateau.
The next evolution of AI is revenue enablement—using AI to create new products, services, and business models. The potential upside here is far greater and uncapped, but realising this value requires a mature Product Operating Model.
Companies that lack clear product leadership and structured decision-making frameworks are struggling to apply AI effectively. They have no systematic way to evaluate opportunities, prioritise investments, or ensure AI initiatives are delivering measurable business value. The absence of a strong POM leads to AI being deployed in fragmented, tactical ways—rather than being embedded strategically into core business offerings.
What This Means for Leadership
Just as Agile transformations required leaders to adapt their mindset, the shift to AI-enabled businesses will demand an even greater change. Executives can no longer rely on top-down decision-making—they must trust and empower their teams, providing the right structures and guardrails rather than micromanaging execution.
For AI to be a competitive advantage, organisations must integrate it within a strong Product Operating Model. This ensures that AI investments are:
✔ Prioritised based on business and customer value
✔ Governed effectively to manage risks like IP security and compliance
✔ Integrated into broader product strategy, rather than remaining isolated experiments
The Bottom Line
The companies that succeed in AI-driven growth will be those that have already done the work to build a strong product mindset, refine their Product Operating Model, and evolve their leadership approach. Those that haven’t will struggle—not because AI isn’t valuable, but because they lack the organisational structures needed to unlock its full potential
