As organizations rely more on digital services for every facet of their operations, the role of CIOs and CTOs has grown more complex and essential than ever. But while the evolution of IT from a supporting function to a critical business driver has created some challenges, it also opens up new avenues for innovation.
Traditionally, IT might have been limited to overseeing email servers or internal applications where downtime, though inconvenient, wasn’t catastrophic. Fast forward to today, where nearly every part of an organization depends on technology. A disruption in IT no longer affects just internal operations; it can bring the entire business to a halt, and with serious financial consequences.
This makes the job of tech executives even more difficult. They are expected to manage a vast and growing digital ecosystem while simultaneously keeping costs under control. IT environments now consist of countless tools, platforms, and systems that are often customized and intertwined, making it nearly impossible to manage these systems manually.
Considering how integral technology is to business operations, it’s crucial for organizations to shift their mindset from viewing IT as just another expense toward understanding its role as a value generator. By strategically managing complexity, CIOs and CTOs can free up resources to focus on initiatives that drive the business forward.
Breaking down silos to drive collaboration and efficiency
Many organizations still rely on a centralized model where all issues flow through a central operations center, but this structure can often create inefficiencies. Those running operations may not have the same expertise as those who built the systems, leading to delayed responses and a lack of proactive problem-solving.
One way to eliminate these traditional silos between engineering and operations teams is by leveraging automation to offload repetitive, low-value tasks. Automation allows both engineering and operations to focus on higher-priority items, improving collaboration between the teams. When you build with maintainability in mind, you eliminate unnecessary noise and allow teams to concentrate on what matters: maintaining system health, quickly resolving incidents and driving innovation and growth.
Taking a deliberate approach to automation
The path to successful automation isn’t always clear, and rushing into it can introduce new risks. When implementing automation, it’s helpful to think of it as existing on a spectrum ranging from basic, structured tasks to more advanced, AI-driven processes. For example, consider the difference between cruise control and a fully self-driving car. Both automate driving, but with varying levels of complexity and different levels of responsibility between the human and the machine. The same concept applies in IT.
Many IT teams manually run scripts to carry out routine maintenance or monitoring tasks. These are ideal candidates for automation, as they are predictable and repeatable. As your automation strategy matures, you can begin automating more complex tasks, such as noise reduction in alerting systems or using AI to assist in decision-making during incidents.
Try to approach automation in deliberate steps. Start with easy, prescriptive tasks where you can easily measure outcomes. Then you can feel confident as you introduce more advanced tools, like AI-powered algorithms for noise reduction or AI-assisted decision-making with human oversight. This helps ensure that you’re implementing automation safely. And to that point, it’s also crucial to keep an “expert in the loop” mindset. Retaining experts to monitor your automation ensures it’s working as intended and minimizes risk.
Making operational resilience a priority
Resilience in today’s digital landscape is non-negotiable. If your systems aren’t available, your customers don’t have a user experience, and the company suffers. Cyber threats are also growing more common and complex. Tech leaders should regularly evaluate the financial impact of outages and ask themselves: “What would it cost if this system went down?”
In some cases, the financial cost might be indirect — such as reputational damage — while in others, it could be a direct hit to revenue. Either way, a failure to invest in resilience can have a cascading effect across the entire organization.
One key to improving resilience is understanding the relationship between cost and availability. Systems with the highest potential impact on operations should have built-in redundancy and fail-safes, while less critical systems may require less investment. This prioritization enables tech executives to allocate resources more effectively and make decisions that balance cost with long-term reliability.
Looking ahead to the future of resilience
AI is a powerful tool for accelerating innovation, and it will continue to drive business value as it evolves. Resilience, in particular, will continue to be a key differentiator in the years to come, ensuring that companies can thrive in the face of disruptions.
The challenges facing CIOs and CTOs today are formidable, but they are not insurmountable. By focusing on managing complexity, building resilience, fostering collaboration and embracing automation and AI, tech leaders can not only navigate the digital landscape but also drive their organizations toward greater innovation and success.
