The 2026 CIO agenda: What IT trends are CIOs really focused on? Part 1 of 8

Every year, we go through the same exercise. We predict which IT trends will dominate the year ahead, which technologies organizations must adopt, and finally, what will happen if they do not. That final question often triggers a latent sense of FOMO, or fear of missing out. As a result, these topics inevitably surface in the boardroom. Not without reason, the attention quickly shifts to the Chief Information Officer, who is ultimately accountable for IT. 

This is not an easy position to be in. A trend or technology does not arrive neatly on January 1, nor does it disappear on December 31. In addition, most organizations do not start from a greenfield situation. They are usually long-established companies that have relied on a wide range of technologies, platforms, frameworks and tools for many years. Over time, these environments have changed significantly. This change is driven by external requirements such as regulation and financing, by new technologies and IT concepts, and by the organization’s persistent demand for additional functionality. 

Regardless of industry, every CIO or senior IT executive faces the same fundamental business drivers. Cost pressure must be reduced. Complexity must be minimized. Execution speed must increase, preferably delivering results yesterday. Consequently, the tension between maintaining operational stability and driving innovation continues to grow. 

Below are the eight IT trends that are top of mind for CIOs in 2026. While they are not necessarily new, remember that trends evolve continuously, which means their relevance increases or decreases over time. In this series, we will look at the trends one by one in greater detail. For each trend, you’ll read what it is, what it means for IT, and what the strategic implications are for the CIO role. We’ll also see what this requires in terms of leadership and organizational maturity. 

The eight IT trends for 2026 

1. AI is no longer an innovation topic; it is a governance issue 

2. Autonomous teams without orchestration architecture create organized chaos 

3. Platform-first strategies: complexity is IT’s largest invisible cost 

4. Confidential computing is no longer a legal discussion; it is an architectural choice 

5. Citizen development is inevitable; chaos is optional 

6. Ecosystems: IT value increasingly exists outside the organization 

7. The convergence of low-code and high-code 

8. You cannot build a digital strategy on analog foundations 

   
   

The impact of these trends varies by organization. Factors such as regulation, industry, company size, board-level digital ambition, and the current state of the core IT landscape all play a role. Let’s unpack trend number one. 

1. AI is no longer an innovation topic; it is a governance issue 

Artificial intelligence has reached the peak of the hype cycle and has clearly moved beyond experimentation. Nearly every organization now runs pilots, proofs of concept or even production workloads using AI. Moreover, AI is mature enough to cause real damage when mismanaged. Therefore, it can no longer be treated as a side project or a novelty but must be governed and embedded in the core IT landscape. 

As a result, the central question for CIOs has changed. The discussion is no longer about whether AI can deliver value. Instead, it focuses on accountability for outcomes, costs, risks and ethical implications. 

In practice, AI is used for customer service bots, automated document processing, fraud detection and AI-supported decision-making in operations. Notably, many of these initiatives originate from the bottom up: Business units adopt SaaS solutions with embedded AI, teams experiment with generative models and employees use public AI tools to improve productivity. 

Challenge 

A CIO faces a serious issue when there is no complete overview of AI usage, when AI-related costs are difficult to explain, and when ownership of data quality and model outcomes is unclear. This often becomes visible through the late involvement of Legal, Compliance or Audit, or through board-level questions about risk that cannot be answered clearly. 

For IT, this situation creates a loss of credibility, reputational risk and uncontrolled cost growth. At that point, AI is no longer an innovation topic but a governance problem. 

Action 

In the short to medium term, organizations must rationalize AI initiatives, establish clear ownership of data and models, and implement AI governance, ethics and security. Over the longer term, AI should be embedded in core business processes, supported by mature MLOps practices and cost management. 

From an architectural perspective, this requires enterprise-wide data and AI architectures along with platforms that clearly separate experimentation from production. 

From a leadership standpoint, this demands a shift from an experimentation mindset to portfolio discipline. Stopping initiatives is also a leadership decision. The CIO becomes accountable for AI value realization rather than AI innovation alone. 

Check out trend number 2

Want to chat about your CIO agenda? Get in touch

Niels van Lieshout

Principal Director Technology

T: +31 650657444

E: niels.vanlieshout@igh.com