AI has already affected the CIO role, and next year will be no different. In 2025, the technology will test CIOs in new ways while also elevating their role as they process the speed at which AI is being adopted—both internally and externally.

Zooming out beyond the CIO role, AI continues to shape the workforce in profound ways. According to a McKinsey survey, the rate of AI adoption is nearly double the rate of both early internet and personal computer adoption. Another promising stat: Per McKinsey, 91% of employees report using generative AI at work and are enthusiastic about its potential to enhance critical skills, from coding to creativity to complex problem-solving. In 2025, I expect that we will see two things: organizations will power even more areas of the business with AI—from finance to customer service to logistics and manufacturing—and AI-driven decision-making will permeate across the economy at an unprecedented scale.

Big predictions, big expectations. With this spike in expectations, it’s no wonder that a recent Salesforce study found that more than half of CIOs (61%) feel that they are expected to know more about AI than they currently do and 9% think they know less about AI than their peers at other organizations. And this gap in knowledge and confidence isn’t the only one that needs addressing. CIOs also need to focus on closing the data-insight gap and this is where AI-driven decision-making comes in. Let’s dive in.

CIOs Need to Play the AI Governance Long Game in 2025

Thanks to AI, more organizations can utilize the technology’s power and potential to process and analyze vast amounts of data and yield the insights needed to make informed decisions across the business. And this will continue to be vital to the decision-making process. However, CIOs must be able to address and answer the following question in 2025: How do we balance the power and potential of AI with the need to control and enforce regulatory compliance around it?

In this elevated role, CIOs will be key to managing the integration of AI systems and balancing innovation with governance bringing CIOs even closer to the business. With AI responsible for decisions that affect everything from patient outcomes in healthcare to financial forecasting, organizations must ensure that the data that fuels these systems are explainable, unbiased, and compliant with emerging regulations. This is where governance comes in.

Governance of both data and AI will be crucial for ensuring systems operate ethically and effectively, protecting both businesses and consumers in an increasingly AI-driven world. The rise of the CIO as a strategic, data-driven leader, especially in navigating the complexities of AI, underscores their importance in shaping the future of AI governance. As the automation of decision-making expands, the challenge for CIOs will be to address transparency and accountability head-on.

Here’s one example of an AI governance challenge: a Hiring Assistant agent designed to help recruiters source candidates and streamline interviews. Under the EU AI Act, this could be classified as a high-risk AI system with potential risks such as biased decision-making and the need for compliance with transparency and privacy regulations.

Now, imagine this at scale: thousands of similar AI agents deployed across heterogeneous cloud services in an enterprise, each introducing bias, operating with opaque algorithms, or mishandling sensitive data. Without proper governance, this can result in regulatory violations, reputational damage, and operational chaos. The challenge for CIOs is clear: How do you effectively govern diverse and complex AI systems while aligning them with organizational goals and regulatory requirements?

Accountability and AI: A Challenge and an Opportunity for CIOs

Organizations that prioritize transparency, accountability, and collaboration will be able to quickly capitalize on the opportunity of AI while mitigating its risks. For CIOs, the challenge and opportunity lie in achieving this balance —leveraging AI to drive business outcomes while maintaining a governance-first foundation. But what exactly does this approach look like?

First, it’s important for CIOs to understand that in 2025, internal pressures within enterprises will accelerate the move to mandatory AI governance. This shift reflects reality. With the rapid evolution of AI technologies and the growing recognition of the risks associated with their unregulated use, it’s no wonder that many experts cite AI governance as a critical need.

And just as cloud adoption and data security saw increasing regulation in the past decade, the same pattern is emerging for AI, driven by both regulatory developments and internal organizational pressures. Globally, we are already witnessing the rise of regulatory frameworks aimed at governing AI practices.

Here is how CIOs can implement transparency and accountability with AI:

1. Scale AI responsibly: Implement robust governance frameworks that are designed to align people and AI use cases around a clear accountability workflow regarding internal policies and external regulations.
2. Evaluate compliance risks effectively: The EU AI Act affects all organizations, so create and work with a risk assessment template for your AI system to help prevent risks.
3. Innovate with AI confidently and responsibly: Ensure that your organization has the highest standards of transparency, control, and trust in place. Additionally, work across your organization to develop comprehensive oversight for all AI use cases, whether powered by predictive models, gen AI models, or AI agents.

And five key areas that CIOs must lead and focus on in 2025:

• Lead AI strategy development: Craft and execute a vision for AI’s role in advancing the organization all the while balancing speed to value with governing AI.
• Champion responsible AI practices: Ensure AI is developed and deployed thoughtfully and responsibly, mitigating risks of bias and noncompliance.
• Facilitate cross-functional collaboration: Break down silos by establishing an AI leadership council that brings other executives, such as CDAOs, together to promote a unified AI strategy, while documenting AI use cases.
• Navigate regulatory landscapes: Keep current with existing, evolving, and future regulations and policies to ensure the organization stays compliant and aligned with industry standards.
• Enhance security measures: Implement robust safeguards to protect against data breaches and other AI-related safety concerns.

Companies that proactively implement governance for both data and AI as well as prioritize AI-driven decision-making will stay ahead of the curve and ensure that their CIOs are successful. In doing so, CIOs will ensure a future where transparency, accountability, and governance are the backbone of AI development and deployment. That’s something to look forward to.