Partner with us for reliable IT support. Contact us now and find out how we can streamline your IT needs!
As autumn kissed summer farewell, ADAPT CIO Edge 2025 landed in Melbourne. Outside, it was still, warm, and drowsy. Inside, a frenetic hive of activity.
And what a difference a year makes. If last year was all about the AI hype, this year it’s about the reality. The CIOs and IT leaders in the room – over 200 in total – were no longer asking if AI, automation, and digital transformation were important. The burning questions were: How do we actually make this work? How do we prove value? And how do we manage the risks?
Across the sessions, a few big themes bubbled to the surface: the growing demand for AI governance, the power (and limitations) of automation, the CIO’s evolving role, and the reality that people—not just technology—will decide the success or failure of digital transformation. Here’s our top five takeouts.
AI has officially moved from the “shiny object” phase to the “show me the money” stage—and for many CIOs, that’s proving to be a real challenge.
Sure. According to Michael Kollo from ADAPT, only 4% of IT budgets have been allocated to AI, although half of CIOs plan to increase spending by FY26. But even that optimism is tempered by the fact that many AI initiatives struggle to demonstrate value. CFOs aren’t convinced either – 40% say AI isn’t even in use or is outright wasted, and 34% call it ineffective.
The problem isn’t necessarily the technology. The organisations that report success with AI do things differently:
• They experiment more aggressively with GenAI pilots.
• They have higher numbers of data engineers in-house.
• They invest in workflow automation to make AI usable at scale.
• They secure stronger executive buy-in.
MIT’s Dr. Peter Weill reinforced this in his four-stage Enterprise AI Maturity Model, showing that most organisations are still in early experimentation or pilot phases. Only 7% of firms are truly “AI future-ready,” using AI across all decision-making and business functions. Until CIOs can crack the code on tracking ROI and building AI into core operations, the struggle for AI legitimacy will continue.
AI is everywhere—but guardrails are still missing in many organisations. That’s a problem.
ADAPT’s research shows that 50% of CIOs don’t have clear frameworks for AI use, and CFOs remain deeply sceptical about AI investments. Meanwhile, an MIT study found that the first two stages of AI adoption—where most organisations are stuck—deliver little to no measurable value. AI only starts proving its worth when it becomes embedded into decision-making, and at scale.
The problem? Many companies are running AI pilots with no clear strategy for scaling or governing them. The solution? Treat AI governance as a priority from day one.
What the AI leaders are doing differently:
• Setting clear policies for acceptable AI use.
• Making data accessible but controlled.
• Measuring business value, not just AI activity.
• Moving beyond experiments into AI-driven operations.
Coles provided a perfect example of why governance matters. Their AI-powered HR bot saved millions by cutting down HR call costs, but John Cox, CTO of Coles, stressed that responsible AI use is key—poorly designed AI could easily introduce bias, misinformation, or compliance risks. CIOs need to get ahead of these risks before they scale.
Automation isn’t just about efficiency—it’s about survival. IT teams are drowning in complexity, security risks, and burnout. Melissa Bischoping from Tanium highlighted some staggering numbers:
• 69% of IT teams report burnout.
• 75% believe automation could prevent it.
• IT teams spend up to three days a month fixing human error.
The sheer volume of vulnerabilities—30,000 to 40,000 new ones reported annually—makes manual patching and security response unsustainable. AI-powered automation is now a necessity, not a luxury.
But automation comes with its own risks. False positives burn energy, and AI-driven security solutions need careful implementation. AI can act as a force multiplier, but only if organisations have a clear strategy for its use—real-time risk visibility, unified data sources, and deliberate curation of AI-driven insights.
Coles’ experience reinforces this. Their AI-powered HR bot reduced call costs from $8-$10 per call to just 10 cents. That’s real value. But as John Cox pointed out, automation needs imagination. AI solutions need to be built responsibly – bad AI recommendations (like a nutritional bot suggesting harmful diets) can create bigger problems than they solve.
It has to be applied strategically, too. WalkMe’s Adam Dinneen warned that layering AI-driven automation on top of already complex workflows can backfire. If automation simply adds more tools without reducing complexity, it defeats the purpose.
Forget the old-school CIO stereotype—the modern CIO isn’t just a tech expert but a business strategist, expectation manager, and transformation leader.
Coles CTO John Cox put it bluntly: being a CIO today means knowing just as much about business outcomes as you do about IT. It’s about setting clear boundaries on what your team will (and won’t) take on, avoiding the agility trap of “faster and cheaper is always better,” and ensuring AI and automation projects don’t spiral into chaos.
That shift in expectations is reflected in ADAPT’s research, which found that:
• 60% of CIOs struggle to build compelling business cases for tech investments.
• 50% admit they aren’t tracking value effectively.
• 80% of their CEOs don’t think they can track value either.
It’s a lonely role. CIOs are expected to drive innovation, but without clear financial outcomes, executive trust erodes quickly. The takeaway? Successful CIOs don’t just implement tech—they sell the vision, communicate in business terms, and ensure their AI and automation investments directly tie to financial or operational impact.
Technology doesn’t drive transformation—people do.
Despite all the talk about AI and automation, one of the biggest themes at CIO Edge was the importance of bringing employees along for the ride. WalkMe’s research revealed a massive gap in AI expectations versus adoption:
That’s a problem. AI and automation won’t deliver value if employees don’t understand or trust them. The best CIOs focus just as much on change management as they do on technology implementation.
John Cox made it clear: it’s not just about rolling out new tools—it’s about making sure employees can actually use them. That means:
MIT’s research backs this up. The organisations that successfully reach full AI maturity don’t just develop AI capabilities—they embed them into how people work. Without a strong focus on people, AI initiatives stall.
AI and automation aren’t futuristic concepts anymore—they’re today’s reality. But as ADAPT made clear, success isn’t necessarily about adopting the latest tools. It’s about execution, governance, and people.
The CIOs who succeed in this next phase of transformation will be the ones who:
The hype cycle is over. Now comes the hard part—and the CIOs who get this right will define the next decade of enterprise success.
Partner with us for reliable IT support. Contact us now and find out how we can streamline your IT needs!