Why making better use of AI may begin with rethinking how your business works, rather than simply adding another tool.
Artificial intelligence is becoming part of everyday business. From drafting correspondence and preparing documents to answering enquiries and analysing information, its potential applications are expanding rapidly. But using AI and transforming a business with AI aren’t necessarily the same thing.
In his recently published book AI Native: The Mandate to Transform Your Company, AI researcher and entrepreneur Kai-Fu Lee argues that organisations need to look beyond adopting individual AI tools and reconsider how work is organised, decisions are made and value is created.
In a November 2026 interview with Reuters, Lee discussed why widespread access to powerful AI hasn’t necessarily translated into comparable improvements in business performance. One important obstacle is that every organisation has its own information, processes, relationships, and ways of working. General purpose AI doesn’t automatically understand that context.
His perspective raises an interesting question for smaller businesses. What might becoming more AI-native look like when you don't have an enterprise budget, a dedicated technology team, or the capacity to redesign your entire organisation?
Beyond adopting another tool
Consider a small professional services business. Customer enquiries arrive by email. Details are transferred into a spreadsheet or business application. Documents are prepared, reviewed, and saved. Tasks are assigned, deadlines are monitored, and invoices are issued.
AI might already help the business draft emails, summarise documents, or prepare reports. Each application can be useful, yet the broader process may still involve repeated data entry, disconnected information, inconsistent handovers, and unnecessary administrative effort.
The opportunity may not lie in finding another AI application. It may lie in reconsidering the entire sequence of work: what information is needed, where it belongs, who acts on it, which decisions require human judgement, and where AI could provide meaningful assistance.
That is a different starting point from simply asking which AI tools a business should adopt.
Transformation doesn't have to happen all at once
Lee's argument for AI-native organisations is ambitious. It involves fundamentally rethinking enterprise structures and operations around AI capabilities.
For a small business, the underlying principle can be applied on a more proportionate scale. Rather than trying to transform the whole business simultaneously, an owner might begin with one process, service, or recurring operational challenge.
For example, a business experiencing delays between completing work and issuing invoices could examine how job information moves between employees, applications, and records.
A practical improvement might involve:
Establishing one reliable place to record completed work
Clarifying when information is ready for invoicing
Removing unnecessary copying between applications
Using AI to prepare draft invoice descriptions where appropriate
Retaining human review before financial information is finalised
Not every improvement requires AI. Some may be achieved through clearer procedures, better information organisation, or fuller use of existing software.
The important shift is designing the process around the outcome the business wants to achieve, and then deciding how technology can best support it.
Three perspectives on becoming AI-ready
A business doesn't need to become fully AI-native before it can benefit from thinking more carefully about its systems. Three complementary perspectives can help identify where meaningful improvements are possible.
Readiness: Understand the foundations
Before introducing new capabilities, consider whether the business has the information, processes, applications, and working practices needed to support them. Is important information accessible to the people who need it? Are recurring tasks sufficiently understood? Are responsibilities clear?
AI can be more useful when it has appropriate, reliable context. Equally, improvements to information quality and process consistency can create value even without AI. Readiness is about understanding the starting point, not achieving technical perfection.
Renewal: Reconsider how value is delivered
Once the current system is understood, opportunities emerge to rethink particular activities. Could employees spend less time transferring information and more time serving customers? Could routine preparation become easier while important decisions remain with experienced people? Could existing information be used to improve planning or identify emerging problems?
Renewal looks beyond faster completion of individual tasks. It asks whether a different arrangement of people, technology, information, and activities could produce a better result. Sometimes the answer involves AI. Sometimes it involves redesigning an existing workflow.
Resilience: Make improvements dependable
A successful improvement should remain useful after its initial implementation. That requires attention to knowledge, accountability, information security, and continuity.
If an AI-assisted process produces incorrect information, who checks it? If an employee leaves, can someone else understand the process? If a technology service changes or becomes unavailable, is there a reasonable way to continue operating?
Human oversight, appropriate access controls, and documented decisions are important parts of sustainable improvement. Resilience means building systems that a business can understand, maintain, and adapt as circumstances change.
From one improvement to the next
One of the practical advantages smaller businesses have is the ability to make targeted changes without necessarily establishing a large transformation program.
The process can begin with a simple sequence:
Discover: Understand the current business system and identify an opportunity worth exploring.
Plan: Compare possible approaches and determine what a suitable change would involve.
Implement: Introduce the chosen improvement through manageable activities, with clear responsibilities and supporting information.
Evaluate: Review what actually changed, using available records and feedback rather than assumptions about success.
Evolve: Retain what was learned and identify the next worthwhile opportunity.
This approach allows improvements to build upon one another.
A more reliable customer enquiry process might later support better job scheduling. Improved job records might make performance reporting more useful. Better organised knowledge might create opportunities for more capable AI assistance.
Each improvement can strengthen the foundation for the next, without requiring every future application to be known in advance.
Thinking AI-native, working at your own pace.
The discussion around AI-native organisations is a useful reminder that the greatest opportunities may come from changing how work is designed, rather than simply increasing the number of AI tools in use. But small businesses should not have to adopt enterprise-scale transformation programs to explore those opportunities.
A more useful starting point may be three questions:
What are we trying to achieve?
How do our current systems and ways of working help or hinder that objective?
What is one practical improvement we could make, and how would we know whether it worked?
The answers can lead to better use of existing tools, new applications, more thoughtful AI adoption, or changes to the way work is organised. The objective is not to become AI-native for its own sake. It is to develop a business system that continues to serve the organisation's needs and ambitions.
And that can begin with one considered improvement.
Start from where you are
Scaling It helps Australian small businesses understand their current systems, explore practical Solution Options, and follow a guided journey through implementation, evaluation and continuous improvement.
Explore a starting point for your business with Scaling It today - try a free Starter Quiz, sign up for a Free Plan and look more closely at how different parts of your system are working, or subscribe to the Basic Plan to survey your whole system, receive solution recommendations with guided implementation, and access insights for ongoing improvement.
Further reading
Reuters Breakingviews, An AI pioneer on extracting value from technology, 10 November 2026
SmartBrief, Why companies must become AI native: A Q&A with Kai-Fu Lee, 11 November 2026
Penguin Books Australia, AI Native: The Mandate to Transform Your Company
This article draws on publicly available interviews and publisher information about Kai-Fu Lee's ideas. The practical small-business interpretation is Scaling It's own perspective.
