Financial institutions need a clear strategy and close collaboration among their finance, IT and operations teams to get their systems and data ready to launch an artificial intelligence (AI) center of excellence.
AICoEs, as they’re known, require clean, accessible data to deliver meaningful results. Without this foundation, financial institutions’ progress will inevitably stall.
While these centers allow CFOs to leverage AI to accelerate business outcomes by uniting technical and domain expertise, only 31% of CFOs surveyed have launched one, according to IBM’s 2024 CFO Study.
“The primary challenges mirror broader obstacles to AI adoption in finance, with many organizations still focused on modernizing legacy systems and improving data quality before they can effectively launch a CoE,” says Monica Proothi, a vice president and global finance transformation leader at IBM Consulting. “The payoff is worth it, but it requires the same level of discipline and cultural change as any successful AI initiative.”
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AICoEs Demand Governance and Cultural Change in Financial Services
Governance presents another barrier for CFOs, particularly in the highly regulated financial services sector. Defining clear oversight responsibilities, implementing proper controls and developing policies that balance innovation with proper risk mitigation can prove challenging, Proothi says.
And those aren’t the only changes required of financial services.
“Perhaps most significantly, establishing an AICoE demands organizational culture change, requiring new ways of working, breaking down traditional silos and embracing more agile approaches,” Proothi says. “While the potential benefits make these efforts worthwhile, this combination of technical, governance and cultural challenges could explain why many CFOs have yet to make the transition — despite recognizing the strategic value of AICoEs.”
Securing Buy-In from All Stakeholders, Including the Finance Team
Often, finance and tech teams at organizations operate in silos. IBM found that fewer than half of CFOs said their finance teams were closely involved in developing technology business cases.
AI can’t be a one-off project that a single department owns.
“It takes a truly holistic approach, and that means strong collaboration across the C‑suite,” Proothi says. “When standing up a CoE, CFOs and CTOs should be working in tandem to identify the best AI use cases — things like automating reconciliations or improving cash flow forecasting — and then prioritizing them based on business impact.”
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An organization’s finance team will ultimately bring the AICoE to life and sustain its impact because it possesses the domain expertise to contextualize AI solutions within financial operations and can identify practical applications. Therefore, it’s equally important to secure their buy-in, Proothi says.
CFOs empower these teams to embrace AI while applying their financial expertise by cultivating a culture of innovation and continuous learning.
“This human element cannot be overlooked, as even the most sophisticated AICoE will falter without engaged stakeholders who understand both its purpose and their role in its success,” Proothi says. “When all stakeholders — from C-suite leaders to frontline finance professionals — align around the CoE’s vision, organizations can more effectively navigate the complexities of AI implementation and maximize return on their technology investments.”
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