AI sometimes feels like the newest, shiniest tool in the digital transformation toolbox. It’s exciting, yet opaque, has huge potential, yet also carries risk. And according to the Australian Department of Industry, Science and Resources, only around 35% of Australian small and medium businesses are adopting AI.
As digital transformation experts, 9Yards hears first-hand from clients the issues that can lead to a low rate of adoption. Many businesses simply don’t know where to start, how AI fits into their overall business strategy or what AI readiness looks like for them.
In this blog we talk to 9Yards Senior Consultant Tatiana Konnova about how businesses can prepare for AI adoption. “As digital transformation consultants, 9Yards approaches working with any client by understanding the current state and the target state then mapping the two to create a digital transformation roadmap. A capability assessment is often a starting point when we work with clients. That applies across the board. And AI is not different to that.”
Whether your organisation is one of the 35% that’s already embraced AI, or one of the businesses holding back to see how the dust settles, Konnova suggests there are 4 important things to think about as you determine your AI readiness.
AI success depends on strong data foundations
“AI is only as useful, or as accurate, as the data that it relies on. If your data is incomplete, inconsistent, or poorly governed, your AI initiatives may not yield meaningful or reliable results. “
Konnova is clear: data maturity is one of the most important indicators of AI readiness. She says that as a minimum, your organisation should have a data governance framework, reference data architecture, and a roadmap for ongoing data quality improvement.
A business capability model is always an effective starting point. It maps what the organisation does and what capabilities support those activities. It can also help you understand whether your business already uses data to support decisions, and whether that data is structured and governed in a way that will support scalable AI use.
Build guardrails before scaling AI
Governance isn’t the most exciting topic in AI conversations, but it’s critically important. Guardrails for AI include policies and reference architecture, defined ethical standards, and ensuring there are controls in place to monitor and mitigate risks. AI risks include, for example, the risk of confident but incorrect outputs (‘hallucinations’), model drift, and unintended bias.
And a word of warning: many vendors are introducing AI-powered features before organisations have had the chance to evaluate their impact. Without a solid governance framework, your business may find itself activating these features without considering the consequences for data security, compliance, or customer trust.
As the regulatory landscape is outstripped by the pace of change, the responsibility for “doing the right thing” has to lie with your business.
Just because something is technically possible doesn’t mean it’s right for your customers or your brand. Build guardrails and say yes when it makes sense and no when it doesn’t.
Design your digital transformation target state for an AI-enabled future
“When 9Yards works with organisations, we begin by mapping the current and target state. This gives a clear picture of where you are today and what capabilities you’ll need to enable future business goals, including AI capabilities. A clear target state roadmap is essential to any successful digital transformation or systems modernisation. AI is no different.”
An example in practice of future AI implementation
An example might be a higher education sector client with a strategic objective to start applying AI in the world of students and teaching. The first step for a digital transformation consultant like 9Yards working with this client would be to build a business capability model that features AI capabilities. This could include developing use cases that answer questions about how students and other stakeholders would use and benefit from AI. Approaching a business capability model in this way makes it possible to put development of AI reference architecture on the digital transformation roadmap, along with AI-specific policies and standards. It outlines activities that will set the organisation up for successful future AI implementation.
You don’t need to roll out AI tomorrow. But you do need a plan to be AI ready when the time is right. Treat AI as a business capability that needs to be integrated, not a standalone tool to be bolted on later.
Select vendors with AI-readiness in mind
Many vendors are rapidly embedding AI features into platforms you already use. But just because a vendor offers AI capability doesn’t mean they align with your goals, risk posture, or technical requirements.
Good vendor management practices are essential here. Before adopting any AI-powered solution, assess the vendor’s track record, transparency, ethical stance, and support for governance. Do they provide enough visibility into how their models work? Do they offer tools for monitoring and control? Can you change vendors easily if needed?
The pace of change in the AI landscape means businesses need to stay agile. Locking into a vendor too early or without the right checks in place can limit your flexibility and expose you to risk.
Is AI explicitly mentioned in your existing vendor selection and management policies and processes? Including it will help you make decisions about AI that support your strategic business goals and ensure you’re not just jumping on the latest trend.
How 9Yards digital transformation consultants can help your business be AI-ready
Successful implementation of AI depends on treating it like any other significant initiative. Start with strategy. Build from strong data. Put governance in place. Map your path before you walk it. And choose partners wisely. If you’re ready to partner with expert digital transformation consultants who can help you navigate implementing AI, let’s start the conversation.
