The AI Incubation Factory Operating Model

An operating model for scaling AI innovation and supercharging growth

Most companies stand at a pivotal crossroad in an era of profound transformation. Significant pressures on economic growth and competitiveness, driven by new Artificial Intelligence (AI) products and experiences, whilst navigating risks of geopolitical volatility and new regulation. In this new AI era, companies can choose to lead with ambition and purpose — or risk being left behind.

AI is no longer a futuristic concept but a present-day catalyst for innovation, competitive advantage and continued relevance. From generative AI (Gen AI), which creates new content and insights, to applied AI, which integrates these capabilities into products and operational processes, organisations that strategically leverage AI will continue to outperform their peers.

Research indicates that between 2023-2030, greater utilisation of AI in key Australian industries will lead to a short-term boost in GDP of more than AU$200 billion per annum and the creation of 150,000 jobs over this period (Note 1). This transformative potential is evident as companies across various sectors, from finance to healthcare, are reimagining their operations and customer experiences through AI solutions and platforms. From a global banking industry perspective, Gen AI has potential to add US$200 – UA$340 billion in value annually, or 2.8 to 4.7 percent of the total revenues, largely through increased productivity (Note 2).

However, the “flip side” of such transformative potential is that it introduces risk of disruption for all companies. AI is compressing the traditional innovation cycle. What once took months — from ideation to scaled commercialisation — is now occurring in record time.

Within this context, how do companies strategically lead with purpose and ambition? One option is to invest in an AI Incubation Factory.

An AI Incubation Factory is a company’s ‘startup engine’—where it discovers and builds AI ventures from scratch, rapidly prototype new products, and spin out solutions that can transform the current business or launch entirely new revenue lines driving delivering +10x growth. To bring this to life, Figure 1 below provides an illustration of an AI Incubation Factory Operating Model.

Figure 1: AI Incubation Factory Operating Model

The AI Incubation Factory Operating Model has five main components:

1. The company “mothership”, and potential external funding sources such as VCs, provides funding to the Incubation Factory Ventures.
2. The funding is being used to establish the people, processes and technology used to build, scale and optimise AI products. Each AI venture, and associated AI product, is organised in agile pods. Biweekly sprints are executed to rapidly prototype AI minimal viable products (MVPs).
3. A technology and data platform supports the agile pods. Strategic technology investments, partnership and architecture decisions are made concerning which LLM(s) to use and what infrastructure is required, e.g., data centre and GPUs. It is also critical to cohesively adhere to principles of being able to re-use data products across AI solutions, e.g. AI Agents, and have microservice APIs.
4. The AI incubation Factory is governed by the “mothership” sponsor(s) and investment committee, using stage-gated funding release principles. A centralised management function is established to lead execution of the AI Incubation Factory. Quarterly business reviews ensure alignment between the “mothership” strategy and OKR expectations.
5. Finally, the customer pays to use the company’s AI products and services to obtain better, faster and cheaper productiity and experiences, whilst delivering the expected financial return on AI investments to the “mothership” corporation. AI products and experiences are continuously and rapidly improved and released by the agile AI venture pods to drive growth and productivity improvements.

An AI Incubator Factory pairs the entrepreneurial hustle of a startup with the resources and reach of the “mothership” corporation, letting companies pilot innovations internally before scaling them for commercial success. It’s a proven way to tap in-house talent, fast-track AI breakthroughs, and stay ahead of emerging trends—all while creating the next generation of growth engines for the company.

We have entered a new era of humanity powered by artificial intelligence. Companies that do not rapidly build and scale their AI capabilities, augment products and experiences, rewire business and operating models are unlikely to be in business by end of this decade. Hopefully your organisation is rapidly incubating and scaling AI ventures to remain competitive…?

Notes:

1. Kingston AI Group: Australia’s AI Imperative, May 2024
2. McKinsey: Scaling Gen AI In Banking: Choosing The Best Operating Model, March 2024

If interested in exploring how you could benefit from building your AI Incubation Factory, then connect with us.

Tom Dissing is the founder and Managing Director of Technology Connect. He has deep expertise in collaborating with companies to digitally transform and scale their businesses through better, faster and smarter use of emerging technology and optimising value from digital ecosystems. He works as a trusted advisor with senior executives in Financial Services (Banking, Insurance, Wealth and Superannuation), Health, Media & Entertainment, Construction & Engineering, Technology Services and Government (Federal and State) in Australia, New Zealand, Asia and Europe.

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