Why AI Initiatives Stall And What CIOs Must Do Differently
- Details
- Written by Jeff Ishii
Insights from Nasheen Liu on the AI Future Leaders Podcast.
AI is no longer a future conversation. It’s a boardroom mandate.
In a recent episode of the AI Future Leaders Podcast, Nasheen Liu, Partner & SVP of CIO Program Strategy at The IT Media Group (ITMG) and a strategic advisor at AI Future Leaders (AFL), joined host Alina Rivilis, Co-founder of AFL and a Data Science & AI leader in financial services, for a candid discussion on a question many executives are quietly wrestling with:
Why do so many enterprise AI initiatives stall, underperform, or fail to scale?
Their conversation went far beyond technology. It was a leadership discussion, one that lands squarely in the remit of today’s CIOs.
The Real Reason AI Struggles in the Enterprise
According to Liu, the problem isn’t a lack of tools, models, or ambition. Organizations are racing to pilot AI, but many are still operating with yesterday’s leadership playbook.
Through her work with cross-industry CIOs across Canada and globally, Liu sees a consistent pattern: Companies invest in proofs of concept without first aligning on purpose, governance, and operating model.
The result? AI becomes a collection of experiments instead of a driver of measurable business value.
She emphasizes that AI is not an innovation project, It is an enterprise capability. And enterprise capabilities require executive alignment, cross-functional ownership, and clear accountability.
From Pilots to Performance: The CIO’s Expanding Mandate
Liu highlights a major shift in the CIO role.
In the past, CIOs were measured on system reliability, cost optimization, and digital enablement. Today, they are increasingly expected to shape how intelligence itself is embedded into the organization.
That means CIOs must now lead in four critical areas:
1. Strategy Before Technology
Many AI initiatives begin with tools and use cases. Liu argues the order must be reversed.
CIOs should start by asking:
- What business decisions do we want to improve with AI?
- Where does intelligence create competitive advantage?
- What risks are we willing, and not willing, to take?
Without this clarity, AI remains interesting but not impactful.
2. Governance as an Enabler, Not a Barrier
AI governance is often treated as a compliance exercise. Liu reframes it as a “trust strategy”.
Strong governance builds trust with regulators, employees, and customers. It clarifies ownership of data, models, and outcomes. And it allows organizations to scale AI confidently rather than cautiously.
Liu notes that responsible AI is not about slowing down innovation. On the contrary, it’s about making sure innovation can survive contact with reality.
3. Operating Models Must Evolve
AI cuts across traditional silos. Yet many organizations still manage it within isolated teams.
Liu stresses that CIOs must be “ecosystem orchestrators” who help bring people together, design new operating models where technology, data, business, risk, and HR collaborate by design, not exception.
This includes:
- Shared accountability between IT and business units
- Embedded AI expertise in domain teams
- Clear pathways from experimentation to production
- Create learning and feedback loops with customers and partners
Without structural change, AI remains stuck in the lab.
4. Human Readiness Is the Make-or-Break Factor
Perhaps the most overlooked issue is people.
Employees don’t resist AI because they dislike technology. They resist it when they don’t understand how it affects their roles, decisions, and value.
Liu encourages CIOs to partner closely with HR and business leaders to address:
- Skills evolution and workforce planning
- Transparent communication about AI’s role in work
- Empowering teams to use AI, not compete with it
“AI transformation is as much cultural as it is technical,” she explains. “If people aren’t brought along, the technology won’t go far.”
A Leadership Moment for CIOs
Throughout the interview, one theme stood out: AI success is now a leadership challenge more than a technical one.
Liu’s vantage point through working closely with CIO communities while advising emerging AI leaders, gives her a unique cross-generational perspective. She sees established enterprises and fast-growing innovators grappling with the same core issue:
How do we turn AI from hype into sustained business capability?
Her answer is clear. CIOs must step forward not just as technology leaders, but as architects of intelligent organizations in shaping strategy, governance, operating models, and workforce readiness in tandem.
Watch the Full Conversation
For CIOs, technology leaders, and executives navigating enterprise AI, this episode offers practical, experience-grounded insights on what it really takes to make AI work at scale.
Watch the full interview with Nasheen Liu on the AI Future Leaders Podcast here
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