I entered the technology field at perhaps the most difficult moment. I was too young to benefit from the optimism of the dot-com era, but I began my career in the period that followed, when many organizations had already lost confidence in IT. I had to earn that confidence back—not through promises, but by demonstrating, project by project, that technology could create real and measurable business value.
When CIOs had the trust
The Internet was changing business, and every organization wanted to participate. Companies created technology divisions, expanded IT budgets, and elevated the CIO into a strategic position. Technology leaders were expected to understand a future that most executives could not yet see.
At the same time, everyone suddenly wanted to become a CIO.
People presented themselves as technology experts because they understood the terminology, had read the latest books, or could describe what the Internet might eventually become. Titles expanded faster than experience. Confidence was often mistaken for competence, and futuristic language was frequently accepted as strategy.
Many organizations paid the price.
Two kinds of technology leadership
Some CIOs understood what technology leadership was supposed to accomplish. They built systems that supported the organization, designed practical processes, improved workflows, connected departments, reduced repetitive work, and delivered useful answers to operational problems.
A good CIO does not merely manage computers, networks, or software. The role requires understanding how the organization operates, where information is lost, why processes fail, and how technology can improve the work performed every day.
Good technology leadership creates structure. It converts repeated decisions into rules, informal activities into reliable processes, and disconnected information into usable knowledge. It reduces friction between departments and gives the organization greater visibility, control, and capacity.
Other CIOs approached the role very differently.
Instead of solving current business problems, they became fascinated with what technology might accomplish in some distant future. They introduced expensive platforms, complex architectures, and multi-year transformation programs that were difficult to explain and even harder to complete.
Some of their proposals sounded less like operational strategies and more like ideas taken from science-fiction books. The presentations were impressive. The results frequently were not.
Projects exceeded their budgets. Implementations took years. Systems were delivered that employees did not understand, did not need, or could not use effectively. In some cases, the technology was sophisticated, but the organization was no better after it was deployed.
The CIO was not solely responsible. Vendors promised more than their products could deliver. Consulting firms sold endless transformation programs. Executives approved initiatives they did not fully understand. Organizations also expected technology to solve problems that were fundamentally managerial, procedural, or cultural.
Why the trust disappeared
Nevertheless, IT leadership absorbed much of the damage.
Companies became skeptical of CIOs who arrived with ambitious visions but few practical answers. Technology departments became associated with high costs, delayed projects, complicated terminology, and initiatives that failed to produce measurable value.
In many companies, the CIO gradually lost strategic influence. IT was reduced to infrastructure, cybersecurity, licenses, help-desk support, and system maintenance. Technology leaders went from helping design the organization to supporting decisions made elsewhere.
AI is creating the same moment
Today, artificial intelligence is creating a remarkably similar moment.
Once again, technology is being presented as something that will transform every organization. Vendors promise autonomous agents, intelligent automation, predictive decisions, and unprecedented productivity. Executives feel pressure to adopt AI quickly, often before defining the business problem they expect it to solve.
Once again, everyone appears to be an expert.
People who recently had limited involvement in technology now present themselves as AI strategists. New titles, consulting services, platforms, and transformation programs are appearing everywhere. The terminology is different, but the pattern is familiar.
AI is real. Its potential is significant. So is the potential for waste.
IT therefore has another opportunity to lead, but only if it avoids repeating the mistakes of the dot-com era.
Start with the operational problem
The starting point cannot be the technology itself.
A CIO should not begin by asking where an AI model, chatbot, or autonomous agent can be installed. The first questions should be operational:
Where is the organization losing time?
Where are employees repeating the same work?
Where are customers waiting unnecessarily?
Where are decisions delayed because information is difficult to locate?
Where are errors caused by spreadsheets, email chains, disconnected systems, or undocumented knowledge?
Where could better information produce a better decision?
Only after identifying the problem should the organization determine whether AI is the appropriate solution.
This requires CIOs to remain close to the business. They must understand how employees work, how customers are served, how decisions are made, and where processes break down. They must work directly with users and observe the difference between the documented process and what actually happens.
The objective is not to produce an impressive demonstration. It is to create something reliable enough to become part of daily operations.
A useful AI implementation may classify documents, extract information, summarize cases, identify anomalies, assist customer-service representatives, improve forecasting, or help employees locate information across multiple systems.
These applications may sound less revolutionary than autonomous organizations run by intelligent agents, but they can create immediate and measurable value.
A good CIO brings answers
That does not mean agreeing to every technology proposal. It means having the judgment to distinguish between what is technically possible, what is operationally useful, and what the organization actually needs.
Sometimes the answer is AI. Sometimes it is better integration, cleaner data, clearer rules, simpler software, or a redesigned process. Automating a poorly designed workflow does not improve it. It simply allows the organization to repeat the same mistakes faster.
A bad CIO sells the future without understanding the present.
A good CIO improves the present while preparing the organization for the future.
The difference is not determined by who uses the newest terminology or presents the most ambitious vision. It is determined by whether the company operates better after the technology is introduced.
Measure what actually improves
The CIO cannot claim success simply because a platform was purchased, a pilot was completed, or a new capability was demonstrated. Technology leadership must be measured through:
- Improved workflows
- Faster decisions
- Reduced errors
- Better service
- Lower cost
- Increased organizational capacity
The dot-com era showed what happens when companies give influence and large budgets to people who understand technology trends but not organizational reality.
The second chance
The AI era gives IT another opportunity.
If CIOs once again lead with hype, complexity, and science-fiction promises, companies will eventually withdraw their trust.
If they lead with operational knowledge, practical judgment, disciplined execution, and measurable results, technology leadership can recover the strategic role it was always intended to have.
IT has a second chance to lead.
This time, the CIO must build the organization—not sell it a fantasy.