CIOnet: What Works, What Doesn’t - Lessons from CIOs
Accelerating Digital Transformation Requires More Than Technology
Digital transformation has been a boardroom priority for years, yet many organizations are discovering that the real challenge is only now beginning. As companies move beyond cloud migrations, ERP renewals, and process digitization, a new phase is emerging—one defined by data-driven operations, platform thinking, and the integration of AI and autonomous capabilities into everyday work.
Recent panel discussions among CIOs, organised by CIOnet, revealed a clear shift in perspective. The conversation is no longer about whether to transform, but about how to do it effectively at scale. Three themes consistently surfaced:
- the importance of a solid foundation,
- the need for measurable value creation,
- and the growing realisation that organisational readiness—not technology—ultimately determines the pace.
The central conclusion was unambiguous: digital transformation is not an IT program. It is an enterprise-wide change that succeeds only when technology, leadership, governance, and people evolve together.
Without leadership alignment, transformation stalls
One of the strongest recurring lessons was that large-scale transformation efforts depend on full executive alignment. It cannot be driven solely by IT or a central transformation office. The entire leadership team must commit to the direction, understand the trade-offs, and actively support the execution.
In practice, this is where many initiatives falter. One participant, who has led multiple global carve-outs and transformations, emphasized the importance of radical transparency from the outset. Organizations must be honest about complexity, risks, and disruption. Attempting to soften the message or delay difficult decisions often leads to loss of trust and momentum.
Simplicity plays a crucial role here. Many organizations instinctively carry over legacy complexity into new environments. Exceptions, local variations, and historical systems may appear convenient in the short term, but they inevitably create long-term friction. Several participants warned against this approach, stressing that copying legacy systems into a new architecture is one of the most common—and costly—mistakes.
A strong foundation goes beyond technology
The concept of “foundation” featured prominently, but it was consistently framed as more than infrastructure or applications. A true foundation consists of data, workflows, governance, ownership, and decision-making structures. Technology is only one component.
This became evident in the case of an industrial company operating in a highly competitive and shrinking market. Instead of investing in a next-generation ERP system, the organization chose to prioritize a data platform that could support operational excellence, commercial performance, and quality improvements.
That decision proved critical. Transformation programs quickly became heavy users of the data layer because it provided actionable insights rather than system upgrades for their own sake. The lesson is clear: technology investments must be directly tied to business objectives. Modernization alone does not guarantee value.
Another participant reinforced this from a financial perspective. Transformations often begin with ambitious growth projections, but success ultimately depends on realizing value over time. The “hockey stick” curve may look promising, but the real challenge lies in delivering sustained returns after implementation.
Data without purpose becomes a liability
A recurring pitfall highlighted during the discussions was the accumulation of data without a clear strategy for its use. Many organizations invest heavily in data collection and storage, yet fail to define ownership, governance, or value creation mechanisms.
One example described a company that gathered vast amounts of data—technically impressive, but economically unsustainable. Storage and management costs continued to rise, while no clear monetization or application strategy was in place. The result was a growing burden rather than a strategic asset.
The analogy used was simple: an attic filled with items that might be useful one day, but currently prevent the space from being used effectively. For CIOs, the implication is straightforward. Data becomes valuable only when it is governed, owned, and actively used to drive decisions or outcomes.
Productization requires breaking the “everything is unique” mindset
An interesting perspective came from an organization operating in complex, project-based environments. While each project is perceived as unique, many underlying processes and solutions are highly repeatable. The challenge lies in recognizing and extracting those reusable elements.
The approach described was incremental: start small, simplify a specific component, productize it, and gradually build a broader proposition around it. Importantly, the value does not lie in the tool itself, but in the combination of digital capability and domain expertise.
A compelling example involved a digital platform for public participation in infrastructure projects. Traditional community meetings often led to confusion and emotional debates, as technical drawings were difficult for non-experts to interpret. By introducing a visual, interactive platform, stakeholders could better understand proposed changes, provide feedback, and even explore variations within predefined boundaries.
This illustrates how digital products can transform not just efficiency, but also communication and decision-making.
Buy versus build is a strategic decision, not a technical one
The discussions also highlighted the importance of making explicit choices between buying and building solutions early in the transformation process. This decision directly affects control over intellectual property, flexibility, and long-term complexity.
Organizations must determine where they want to differentiate and where standard solutions are sufficient. A common mistake is to carry forward legacy components simply because they are familiar, resulting in hybrid environments that are difficult to manage and scale.
Clarity at the outset enables more focused investments and reduces the risk of accumulating technical debt.
AI and agentic transformation depend on organizational readiness
While AI and agentic capabilities were key topics, the tone of the discussions was notably pragmatic. The potential is widely recognized, but there is growing awareness that technology can outpace the organization’s ability to adopt it. In one industrial setting, advanced AI capabilities had already been deployed, including agents that support operators in real-time troubleshooting and predictive maintenance. Technically, these solutions performed well. However, the organization struggled to fully utilize them due to limited understanding and skills.
The response was deliberate: pause further technical development and focus on building capabilities. Training programs were introduced at all levels, from executive leadership to operational staff, with structured curricula for data and AI skills.
The lesson is significant. Agentic transformation is not simply about deploying new tools; it requires a fundamental shift in how people work, make decisions, and interact with technology. IT and business must converge around ownership
Another key insight was the need to redefine ownership between IT and the business. Digital capabilities often remain within the IT domain, while business teams act as passive recipients. This model is increasingly ineffective. One participant from the financial sector described how a digital interaction capability only succeeded because it was co-developed with business teams and integrated into existing processes such as marketing and customer engagement. Treating it as a standalone IT solution would have limited its impact. At the same time, regulatory requirements and governance structures can complicate ownership. Stricter controls on data access, for example, may unintentionally reduce agility by limiting what business users can do independently. Balancing control with flexibility is therefore essential.
The core takeaway: agentic increases the urgency of getting the basics right
The overarching conclusion from the discussions was clear. Emerging AI and agentic capabilities do not eliminate the need for a strong foundation—they intensify it. Organizations must accelerate their efforts to establish robust data structures, clear governance, and aligned operating models. At the same time, they must invest in people, ensuring that skills and capabilities evolve alongside technology.
For CIOs, this creates a dual challenge. On one hand, there is pressure to innovate and demonstrate tangible progress with new technologies. On the other, sustainable success depends on discipline: simplifying architectures, making early strategic choices, focusing on value, and prioritizing organizational readiness.
Digital transformation, therefore, is not a rapid technological upgrade. It is a continuous organizational journey. Leaders who recognize this are better positioned to turn acceleration into lasting impact rather than increased complexity.