The Landscape of Data Governance is Changing
While many organizations have robust data governance programs in place, AI is fundamentally changing the landscape. Unlike traditional data assets, AI systems learn, adapt, and sometimes behave unpredictably. Their outputs can be difficult to explain or audit, introducing new ethical, legal, and operational challenges. This necessitates a refinement of existing governance programs to ensure they remain effective in this new era.
Building Upon Existing Foundations
With its charter, policies, council, and dedicated data owners and stewards, your current data governance program likely already provides a strong foundation. However, these elements must evolve to encompass the unique demands posed by AI systems. To protect brand reputation and comply with rapidly emerging regulations, companies need to extend their governance frameworks to include AI considerations.
Key Areas for AI Governance Enhancement
To govern AI effectively, organizations should expand their data governance framework to include:
- Model Lifecycle Oversight: Implement mechanisms to track training data, performance metrics, and retraining triggers—ensuring ongoing model accuracy and reliability.
- Ethical & Responsible AI: Establish guidelines for fairness, explainability, and human oversight to mitigate bias and ensure ethical AI use.
- Risk & Compliance Alignment: Map AI models to relevant regulations while maintaining comprehensive audit trails to ensure compliance and accountability.
- Operational Integration: Embed governance practices into MLOps and analytics workflows to ensure seamless and effective governance across all AI operations.
A Present Priority
AI governance should be a present priority, not a distant concern. By building on existing data governance foundations, organizations can manage AI risks while unlocking its strategic value. Start with what works, scale with intention, and treat AI as both an asset and a responsibility. Embrace this opportunity to refine your governance program, ensuring it is equipped to handle the complexities and opportunities brought by AI.
Ready to Enhance Your Data Governance for AI?
If you’re interested in starting down the path of integrating AI considerations into your data governance framework, now is the time to act. Begin by assessing your current governance structures and identifying areas where AI-specific enhancements are needed. Engage with stakeholders across your organization to foster a culture of ethical and responsible AI use.
Consider partnering with experts in AI governance to guide the expansion of your framework and ensure compliance with emerging regulations. By taking proactive steps today, you can safeguard your organization against potential risks while leveraging AI’s strategic benefits.
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If you need guidance or expertise in developing a comprehensive AI governance strategy, don’t hesitate to reach out. Let’s work together to ensure your organization is ready.
Choosing the Right Banking Technology Also Comes with Challenges
Although upgrading to modern tech offers benefits to both banks and customers, financial and operation concerns are valid. While core banking technology systems provide a backbone for your banking operations, they can impede your company’s growth in a few key areas.
- Outdated legacy systems — Relying so heavily, for so long, on legacy systems makes it hard to pivot to more modern systems. Replacing or upgrading a legacy CBS takes careful thought and planning that can’t happen overnight.
- Integration with other systems — Consumers expect smooth, seamless integration with other technologies. This poses a challenge when trying to implement new systems alongside old, existing systems.
- Security concerns — Robust security measures are critical for banks to protect sensitive customer information. Legacy core banking systems’ outdated technology and limited security features make them vulnerable to cyberattacks and data breaches. This lack of robust security protocols and encryption methods makes legacy systems no match against modern cyber threats.
- Handling modern data loads — Financial institutions manage enormous amounts of data. Banks using old CBSs must think about how to best manage and leverage this data, not to mention protect it.
- Scalability issues — As financial institutions grow, they can experience significant growing pains that require serious conversations about their tech. Integrations, data management, performance, infrastructure costs, and user experience are all concerns that scalability concerns that banking technology must be able to accommodate.
Banks must often choose between maintaining their legacy systems or investing in modernizing their core technology. The key to successful upgrades is to not make technology-related decisions in the dark. Banks need insight into how the technology will impact customers, internal teams, and core systems.
The Missing Piece: You Can’t Rely on Tech Alone
Like history, trends tend to repeat themselves. While customers expect and rely on digital banking systems, their needs are multifaceted, especially across an intergenerational customer base. Relying on technology alone without considering a 360-degree customer experience (CX) strategy could hurt your bottom line and erode trust in your brand.
While in-person banking was on its way out going into the 2020s, institutions like Capital One are bringing back the brick-and-mortar in the form of bright, plant-filled Capital One Cafes. These cafes bring in a wider audience than just banking customers, serving as community-focused third spaces for the public. Cafe customers are also offered the opportunity to engage with Capital One products through interactive displays in-store or chat with banking representatives at the cafe site for a full-service experience that entices interaction and builds both brand recognition and trust across demographics.
This illustrates the importance of staying innovative without losing the humanity threaded throughout the banking experience. The goal should be for banking technology to stay on pace with technological advances and modern banking services, all while keeping the customer firmly planted at the heart of it all.
Are You Maximizing Your Banking Technology? We Can Help.
According to a 2022 McKinsey & Company report, many depository institutions still use legacy core systems up to 40 years old that reside on mainframe hardware coded with outdated programming languages. So, why is this an issue in 2025? Modern security concerns and customer interactions require modern core systems.
Outdated systems leave institutions and their customers vulnerable to serious financial risk and even litigation. While costly and time-consuming up front, updates to digital infrastructure are a smart investment that will save money down the road.
Growth of technology in the banking industry is no longer monolithic. Success now requires a solid customer experience strategy that incorporates technology as a piece of the larger puzzle. If you see your organization’s growth slowing or your legacy systems need a revamp, let’s talk. As your CX solutions consulting partner, we can collaborate to determine how to develop or enhance your CX strategy to meet your organization’s goals.