“What was once an intractable problem is now solvable,” says Sparks-Austin. “That frees up a lot of time and resources for the CIO to be more strategic.”
AI platforms and tools make it more feasible for CIOs to build custom systems to meet specific business needs rather than deploying packaged applications that inevitably fall short of users’ expectations.
“CIOs can move away from their standardization playbook that delivered ‘good enough’ solutions and start building custom solutions that focus on customer value,” says Sparks-Austin.
“This is not an ‘I told you so’ moment for CIOs,” he explains. “It’s relief for CIOs who don’t have to disappoint the business anymore with long build cycles and escalating costs. Now there is a way to give the business what they want and iterate quickly.”
AI becomes the agenda
For leading organizations, AI is no longer a line item on the board agenda — it is the agenda. It forces organizations to confront what they uniquely understand and how they create value.
This shift requires CIOs to move from a scarcity mindset, where technology is constrained and optimized for cost, to an abundance mindset, where compute, engineering and AI capabilities are deployed to drive growth.
“This is an existential moment for CIOs to work with their boards and executive teams to explore what makes their business essential to their customers,” says Sparks-Austin. “And then leverage the technology to create and compound moats across the business.”
CIOs need to work with their leadership teams to position AI as a strategic growth lever rather than a cost-cutting tool that, in Sparks-Austin’s framing, causes organizations to turn inward — optimizing existing structures rather than pursuing new value.
How to adopt an abundance mindset
Organizations that are using AI primarily to optimize legacy business models and reduce costs may feel a false sense of progress because they’re not generating competitive advantage. Here are three steps a CIO can take to help their organization adopt an abundance mindset that drives sustainable growth.
1. Reverse-engineer enterprise IT around outcomes, not tasks.
CIOs have an opportunity to flip the orientation of enterprise IT. Instead of designing around core internal functions, they must orient every decision, from technology to talent to investment, around the edge: the points where the business meets the customer.
By mapping the critical capabilities that exist at the edge (such as customer experience, product agility and speed), IT teams can then design inward across the technology architecture, data flows, talent and operating model. AI efforts become guided by what companies want to achieve — outcome-focused rather than task-focused. As organizations move from “AI enabled” to “AI native,” they will open up opportunities to challenge current business models, deliver new offerings that create customer value and leverage their new AI workforces to seek greenfield opportunities.
2. Reallocate budget toward the edge.
Leading organizations are reframing every dollar of technology spend against a simple question: How does this improve our ability to compete and win at the customer edge? This framing drives more discipline in the portion of the budget that’s tied up in operations while accelerating investment in the capabilities that directly impact growth.
This approach is newly practical because CIOs can use AI to better understand where legacy systems are driving up maintenance costs.
“CIOs have always wanted to bring those costs down, but unpacking the systems was difficult,” says Sparks-Austin. “AI helps you interrogate those systems to get comfortable deliberately decommissioning them and bringing those costs down over time.”
In this sense, budget reallocation becomes more than a financial exercise — it serves as a catalyst for changing how the entire organization prioritizes, invests and executes.
“If a board or a CEO mandates that any dollar has to be spent on affecting the edge, you’ll see some pretty creative options come out of the typical cost centers — not just IT, but finance and supply chain as well,” says Sparks-Austin. Although this shift can create organizational tension, as it challenges long-standing budgeting practices, it’s critical for long-term growth.
3. Shift from tool adoption to problem ownership.
AI tools on their own won’t drive transformation. In reality, tools are the least differentiating part of the equation. The real advantage comes from identifying and solving high-value problems — particularly those that sit at the intersection of customer experience, product innovation and operational complexity.
For CIOs, this requires a shift in posture. Their role is no longer about standardizing platforms or enforcing architectural consistency — it’s about helping the business define what to build and why. As development costs and cycle times compress, more value shifts upstream. Successful organizations will pair deep domain expertise with the ability to apply AI to the right problems, in the right places. In this model, technology amplifies the strategy instead of leading it.
“Unpacking these problems is totally solvable,” says Sparks-Austin. “Defining what to build and how to build it will be the liberating function for the people overseeing this shift.”
