The path to scale with GenAI
The opportunity for GenAI to deliver value continues to rapidly expand - we've learned from our own transformation, client engagements and alliances that you need to focus on six priorities to achieve scale.
Different factors are important in clearing the path to scale GenAI, including:
- Leadership and accountability
- AI strategy and value
- Trustworthy AI
- Operating model
- Technology choices and data
- Change readiness
The key to driving value is recognising that these six priorities are interconnected in nature and need to be considered together and not individually to clear the path to scale with GenAI.
Six priorities to achieve scale with GenAI
Leadership and accountability
It’s not just the use case – it’s the leader
To achieve scale, organisations need to do more than just develop a list of GenAI use cases. GenAI needs to be on the leadership agenda – with clear accountability, alignment on risk appetite, agreed priorities and investment choices all supported by outcome focused executive KPIs.
This creates alignment on how GenAI is linked to executing the business strategy, increasing return on investments and sustaining competitive advantage – whilst also reducing roadblocks in decision making.
AI strategy with a clear ambition
Is your GenAI adding value or cost?
AI, which includes GenAI, shouldn’t be a standalone initiative; it needs to be embedded in the execution of your business strategy. This means having a clear AI ambition – that defines where and how you will deliver solutions and monitor value with AI – to support and enhance your overall strategy.
An integrated strategy will also include the supporting investments required to deliver your AI ambition whilst ensuring your AI costs, which can be significant, clearly drive benefits aligned to your business strategy.
This will ensure your AI and GenAI initiatives are adding value and not just technology cost.
Trustworthy AI
Scale faster with a clear plan for trust
Trustworthy AI is delivered through good AI governance.
A plan for trust usually focuses on managing risk and compliance so that your AI doesn’t have unintended impacts. However, a well-designed plan can also unlock delivery speed through efficient decision making, approved AI tooling and usage guardrails.
Building a robust plan for Trustworthy AI in this way addresses both safe and responsible use, as well as enabling wide access for teams, so innovation and adoption can thrive. In addition, this will allow you to progress whilst regulatory uncertainty remains in Australia.
A flexible yet robust plan ensures your path to scale remains clear.
Operating model
Setting up for two speeds
Setting up your organisation for success with GenAI needs to factor two speeds: how fast you want to adopt and deploy solutions, as well as how quickly the technology itself is progressing.
The speed of adoption and deployment is a function of how quickly you can identify, build and deploy solutions together with your team’s ability to adopt the change. Importantly, this also includes having access to the right skills and capabilities for delivery.
GenAI is rapidly progressing and will continue to increase its transformational and value potential. We see this almost weekly, with major announcements confirming GenAI’s extended applicability across the enterprise. Whilst the software development lifecycle is traditionally set up to protect application development and usage from change to IT or other business functions – with GenAI, ensuring the continual inclusion of the latest capability will be challenging but important to achieving scale and maximising value.
Technology choices and data
GenAI brings a new lens
GenAI technology choices are quickly becoming more complex and it’s not just about which foundation model or how much GPU you will need. Consideration needs to be given to where and how models are trained and monitored – as well as ensuring the right data is available and achieving regulatory compliance. These choices also have flow on impacts.
For example, choosing to leverage native enterprise software AI capability within CRM and ERP systems may require upgrades such as moving to cloud, integrating additional data, or managing associated data security and privacy implications – all of these areas need to be addressed. Alternately, choosing to use a separate AI platform alongside an existing ERP or CRM will require a build/buy decision and create possibly different data availability and integration challenges. Both approaches will have impacts on licensing, tokens, GPU consumption, security, skills, support and cost.
To avoid getting locked into software choices or cost models that are unfavourable in future, developing a set of principles to guide choices and understanding impacts is key to a sustainable path to scale value with GenAI.
Change readiness
The scope for change is bigger than you think
The speed at which any organisation can adopt new technology is directly tied to its readiness for change. It’s no different for GenAI – but the scope of change is bigger than you think and moving more quickly, fuelled by the progression of the technology and its integration into enterprise software.
A change plan needs to be holistic and consider more than AI fluency and change communication. For example, if your ambition extends to reshaping your workforce, you will need to plan for the implications on workforce agreements, union dynamics, HR regulation and employment contracts.
Change readiness also extends to your customers, suppliers and broader ecosystems. For example, if your strategy drives AI into your supply chain, but your suppliers are not ready to work in new ways – it won’t work. Similarly for customers, if they won’t engage or accept AI, sales and customer retention may be at risk.
Understanding these factors is crucial for ensuring a smooth transition as you automate or revise work processes. Without a holistic plan for change, you don’t have a plan for scale.