The 2026 mandate: why AI governance and XAI will define the future of finance

By 2026, the question of whether or not to adopt artificial intelligence is resolved. The focus has firmly shifted to execution for finance and accounting teams. As businesses face limited budgets and time-consuming manual tasks, teams are intrigued by AI’s ability to help them get more work done.

But in the future, these digital transformation efforts will no longer be measured by the speed of automation of new tools. Instead, the focus will be more on the data integrity of AI deployments and whether they are based on strong governance frameworks.

Risks of adopting AI in finance

There will be more focus on governance with the future of AI adoption. Finance and accounting departments have zero tolerance for inaccuracies, and rushing AI implementation without putting the appropriate governance frameworks in place is risky and could present costly problems.

If companies integrate AI without putting the proper foundation for data integrity and governance safeguards in place, it becomes extremely difficult to verify the results of AI. Without this visibility, leaders cannot confirm the source or reasoning process behind AI results. This lack of auditability can result in significant financial losses, ranging from reputational damage and customer distrust to substantial regulatory fines.

Not only are AI models deployed without the necessary foundation, but many organizations also fail to take the crucial steps needed to fully realize the value of the tools. Many spent massive budgets during the initial AI hype, but struggled to see a return on investment. While top-performing companies generate more than 10x ROI on their AI investments, 61% of companies surveyed by McKinsey still reporting no financial impact at the company level, stuck in expensive pilot purgatory.

The pitfalls of unqualified adoption

Beyond fundamental governance risks, many organizations struggle to deliver value because they fail to address the essential human element of successful adoption. This rush to implement new technologies without upskilling teams to understand how these tools work and how to use them efficiently and effectively is a major driver of lack of value. The full value of AI processes cannot be achieved if teams do not have the knowledge to take advantage of AI’s opportunities and manage its risks.

The recent report from the Massachusetts Institute of Technology GenAI Divide: state of AI in business The report reveals that despite $30-40 billion in corporate investments, 95% of organizations see no return on their AI initiatives. If companies continue to invest budgets in AI without having the foundation to take advantage of the technology, this will continue to create an unsustainable infrastructure for AI spending that will likely fail in the near future.

Achieving Successful AI Adoption

To break free from this “pilot purgatory” and transform AI from a budget drain into an exponential investment, organizations must establish real-time, integrated internal controls and ensure full auditability of every AI action. This will build trust and transparency with AI models, ultimately enabling teams to extract more value from the technology, validate results, and report anomalies as they occur.

In financial services, where accuracy is paramount, creating a layer of control over explainable AI (XAI) will help ensure that the data and how automation is carried out is reliable and based on reliable information. XAI will be key to the success of AI integrations because it provides an unbreakable chain of thought and a clear audit trail. These build trust with finance and accounting teams and protect them from costly financial risks.

Sustainable AI Infrastructure Strategy

To move to a truly sustainable AI infrastructure, organizations must follow these key strategies:

• Agentic AI Employees: Organizations should design agentic AI to act as a digital extension of their most seasoned professionals. To achieve this, finance leaders must train AI with the same materials and resources that an organization would use to train a new hire. This includes formalizing frameworks on best practices, segmenting controls over what AI can and cannot access, and implementing a continuous feedback loop where humans can continually validate, refine, and train the agent to ensure its outcomes align with the business. This will help the organization’s agents evolve and better generate insights and responses based on everything the team knows.

• Staged AI integrations: By gradually introducing AI in targeted, manageable increments, organizations can achieve rapid results that justify additional investment. This approach will also help leaders and teams align on the tools, building the confidence to master them and achieve greater value while minimizing the risk of inaccurate results.

• XAI: By prioritizing XAI, organizations can ensure real-time auditability and internal controls of their AI deployments. They can see the reasoning behind each outcome, allowing every action to be fully traceable. This not only avoids the risk of regulatory fines and reputational damage, but also helps organizations reduce inconsistencies, leading to better measurable results.

The ultimate gain of verifiable AI

As companies plan their AI integrations for the next year, following these strategies can help organizations achieve full executive alignment on their AI investments and gain trust and transparency with executives in every AI action. Ultimately, this can help leaders turn their AI spending into a justified, exponential investment that supports the overall mission of the company. The finance and accounting teams that can successfully establish the governance foundation for their AI integrations will be the ones that build the long-term sustainability of their investments. This commitment to auditable governance will enable organizations to confidently scale trusted agentic AI across the enterprise, paving the way for empowered finance functions and competitive advantage.

ABOUT THE AUTHOR:

Tammy Coley is a visionary accounting leader with a deep understanding of how accounting processes interface with modern technology. As Director of Transformation at Black lineshe brings this insight and experience to clients as they transform their financial and accounting operations through the use of the company’s cloud software tools.

Formerly Executive Director of Corporate Accounting and Internal Controls Governance at Cox Communications, a broadband communications leader and long-time BlackLine customer, Tammy brings deep industry and product experience to BlackLine. By implementing a continuous accounting model, Tammy transformed the monthly accounting cycle at Cox by generating more timely financial statements with greater consistency and accuracy while reducing costs. Prior to Cox, she began her career in public accounting at Ernst & Young. She also spent 12 years in progressive roles, including controller, at Sloan Financial Group.

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