FICO's CAO and State Street’s VP of Automation and AI on breaking down siloes achieving a strategic edge through cross-departmental collaboration
By Corinium Global Intelligence
AI may be a strategic priority in the boardroom, but on the ground, misalignment is undermining impact. Data from a recent survey by FICO and Corinium points to a widespread disconnect between AI initiatives and core business objectives – one driven by collaboration breakdowns and a lack of solid solution design.
When asked how well AI investments, development efforts, infrastructure, and end-user strategies align with overall business goals, only 5.2% of CAOs and CAIOs surveyed reported full alignment. That means nearly 95% of organizations are making life harder for themselves – developing AI systems that may not serve the very needs they were designed to address.
The problem isn’t ambition. Most organizations now have dedicated teams focused on data science and AI development. But too often, these teams operate in silos, cut off from business leaders, end-users, and risk stakeholders.
“So many projects fail because there was a difference in expectations and no process, no outcome defined, and no mutual accountability,” says Cortnie Abercrombie, Founder and CEO at
AI Truth. “When business walks away after giving a vague brief and comes back six weeks later, that’s not collaboration – that’s a setup for failure.”
A massive 72% of CAOs and CAIOs cite insufficient collaboration between business and IT as a major challenge to organizational alignment. It’s not that AI teams lack vision, but rather that the vision isn’t shared, and when it is shared, it isn’t shared effectively. Different departments use different metrics, assumptions, and roadmaps. There’s plenty of technical sophistication but not nearly enough of a unifying strategic focus.
It's a disconnect highlighted by Barbara Widholm, VP of Automation and AI at State Street: “The fragmentation between Chief AI Officers and Chief Technology Officers is a major barrier to value realization. Tech-led solutions often lack strategic or data nuance, while AI-led initiatives can miss infrastructure constraints. Cross-functional alignment is critical.”
The issue is further compounded by a widespread lack of AI literacy across businesses. More than 65% say this is a core challenge when trying to scale AI. Many business decision-makers are eager to harness AI but struggle to understand what it can, and cannot, do.
This is, in many ways, a retelling of a very common business story in recent decades: overhyped expectations, underwhelming results, and growing frustration on all sides.
This literacy gap doesn’t just affect adoption: it shapes how AI is scoped, implemented, and governed. Without a shared baseline of understanding, business units struggle to articulate business needs, and AI teams struggle to prioritize the right AI development. Risk and compliance stakeholders, meanwhile, may find themselves brought in too late to meaningfully shape outcomes, which often torpedoes the whole effort.
“Everybody believes they’re an AI expert when they’re not,” says Dr. Scott Zoldi, Chief Analytics
Officer at FICO. “Many organizations lack a clear line of demarcation around how AI decisions get made. If you don’t have an AI board, if you don’t have AI governance, and you let each silo decide for itself, what you get is confusion.”
Closing this gap will require more than workshops or explainability dashboards. It demands a cultural shift – one in which AI fluency becomes a leadership competency, not a technical afterthought. This shift should also focus on AI leadership roles and seasoned expertise instead of fettered opinions or misplaced beliefs in the capabilities of AI, held by those that barely understand the technology or how to make it work to produce value.
The cost of misalignment
The consequences of misalignment are significant. AI systems developed in isolation are more likely to:
All of these, naturally, undermine the very ROI that AI is meant to deliver. The solution is not simply more oversight, but cross-functional collaboration embedded into every stage of the AI lifecycle. Collaboration enables clarity of purpose and mission.
Fortunately, leaders are recognizing this. When asked about innovation enablers, 83% of all survey respondents rated cross-departmental collaboration as either “very important” or “critical”: a clear signal that alignment has ascended in significance from optional to foundational.
To move from proof-of-concept to profit, organizations must align their people, their processes, and their platforms. That means breaking down silos, elevating literacy, and giving AI a seat at the strategic table – not as a buzzword, but as a full-fledged business function.
For a deeper dive into our benchmarking research on the state of responsible AI, download the full report.