Amid the Enterprise-Wide Full-Staff AI Boom, Will CIOs End Up in the "ICU"? – eu.36kr.com

Recently, Lao Yang was invited to attend the quarterly business review meeting of a group company as an observer. The CIO of this company reported on the progress and implementation of AI solutions. The PPT was clearly generated by AI, full of futuristic tech vibes with colorful layouts, covering everything from computing power to agent platforms, and then to data governance and data middle platforms.
Suddenly the boss interrupted him: “I don’t understand any of this, you don’t need to talk about it. Just tell me, how much profit has AI brought to the company this year, and how many staff positions have been optimized?”
The conference room fell silent for a few seconds. The CIO said, “Boss, at the current stage of the company, AI is a long-term investment……..”
Before he could finish his sentence, the boss interrupted him and turned to ask the business department the same question.
The head of the business department said, “The efficiency improvement is very obvious. We can develop software by ourselves using WorkBuddy, no need to wait in the scheduling queue of the IT department.”
Speaking of which, I believe everyone has already understood, right? Doesn’t this scenario feel familiar?
As a CIO, do you also feel a sense of anxiety at this moment?
Under the enterprise-wide AI boom, will CIOs end up in the organizational “ICU”?
The ICU Lao Yang is talking about today is not the one in the hospital, but the ICU inside the organization: although the CIO is still on the payroll, still attending meetings, still signing documents, their sense of existence is only maintained by a “ventilator”.
Lao Yang believes that in the AI era, to judge whether a CIO of an enterprise is heading for the organizational ICU, you don’t need to see how much technical knowledge they have or how large their team is, just look at the following five indicators.
First, the budget is being split up
In the group’s annual digitalization budget, the AI portion has started to be allocated to business lines and approved by business leaders. Although the CIO is still in charge of the computer room, network and ERP operation and maintenance, all these are presented as cost centers; what AI needs is a growth story, but the problem is that since the business department used WorkBuddy to develop software on its own, this part of the budget no longer goes through the CIO.
Second, the project lead has been replaced
In the past, the lead of any digital system project must be the CIO. But now for AI projects, the lead could be the vice president of business, operations director, or even HRD. The CIO’s name appears in the “service support department” column, or is even bypassed entirely.
Third, the right of product selection is lost
The business department finds suppliers on its own, and only notifies the IT department to “coordinate technically” after the price is negotiated. This practice was called shadow IT ten years ago, and now it has been upgraded to business self-built agents. The CIO is the last one to know, but the first one to take responsibility.
Fourth, responsibilities are increasing instead of decreasing
Who is the first to be called to the meeting when a data leak happens, generated content has errors, an interface connection crashes the server, or data is accidentally deleted? It’s still the CIO. The problem is that management rights are flowing out, while responsibilities are being pressed in. In any case, they cannot get rid of the fate of being the “scapegoat”, and this scissor gap is the most hurtful.
Fifth, the right to speak is depreciating.
When reporting, they can’t speak the business language, and can only talk about parameters, architecture and concurrency. The boss may interrupt them in less than 30 seconds, turn to ask the business leader: “What do you think of this AI? Is it usable?”
In Lao Yang’s opinion, if a CIO hits two of the above five points, they are basically in a sub-health state. If they hit four points, they are basically on the way to the organizational ICU.
When many CIOs are pushed to this situation, their first reaction is self-doubt: Is my understanding of AI not enough? Or is the technology of my team not good enough?
In Lao Yang’s view, most of the time that’s not the case. The specific reasons are as follows:
1. The exclusive technical agency right is gone
In the past, only the IT department in the enterprise could get the system up and running, and the business department had to queue up for whatever they wanted to do. This “exclusive agency right” is the foundation of the CIO’s power and their core capital. But now business personnel can build agents by themselves with AI, pull data on their own, and launch small applications one after another in a short period of time. The barriers to software development have been broken. The biggest technical chip in the CIO’s hand suddenly becomes worthless.
2. AI is not an IT project, but a business transformation
The professional habit of CIOs is project-based: project approval, bidding, implementation, acceptance, operation and maintenance. This set of processes works well for system management, but fails when it comes to transformation. What the boss wants is business results, but what you deliver is a launch report. The two sides speak completely different languages and can’t convince each other. But then again, after so many years of digital transformation, how many enterprises have achieved real digital transformation? The reason is obvious to all.
3. The organization has not reserved a position for the CIO to “manage AI” at all
Many enterprises have established AI committees and digitalization committees, which sound very high-level, but the director is the boss, the deputy director is the head of the business department, and the CIO is only at the executive level. Meetings are still held, work is still done, but where is the decision-making power? Nowhere! But the executive ability must be absolutely top-notch!
So it is not difficult to see from the above that this is not a capability crisis at all, but a position crisis. If your position is wrong, no matter how hard you work, you are just making wedding dresses for others.
The first type: Technology-focused delivery type
Their KPI is the system launch rate. In their hands, AI is just a project: product selection, deployment, training, acceptance. They take photos on the launch day, and don’t care whether anyone uses it afterwards, because in their eyes that’s the business department’s business. When the boss asks for results, they can only produce a bunch of server and token purchase bills.
The second type: Cost steward type
They are good at bargaining, cutting maintenance costs, and saving 3% of the budget. This set of skills is an advantage in the stable period, but a fatal flaw in the transformation period. The boss does not lack people who can save money now, but lacks people who can turn AI into profits.
The third type: Passive follower type
They wait for the boss to put forward requirements, wait for the business department to come up with plans, wait for suppliers to provide PPTs. When the trend comes, they follow and shout a few slogans, and when the trend passes, they stay where they are. This kind of person is the safest, but also the most dangerous, because their replacement cost is the lowest.
Then what do CIOs who don’t end up in the ICU look like?
Lao Yang has met several of them, and their common point is: they no longer regard themselves as “people who manage systems”, but as “people who manage rules, data, risks and capabilities“. Anyone can launch a system, but only they can set the rules and manage the data.
After communicating with many CIOs, Lao Yang puts forward the following suggestions:
First, seize the definition right of AI governance first
How to classify data, which data is not allowed to leave the internal network, who reviews model access, how to verify generated content, how suppliers are admitted, the CIO should draft the rules first. Once the rules are implemented, no matter how urgent the business is, it has to go through the IT department.
Second, turn data from “assets” into “usable assets”
The phrase “data is an asset” has been shouted for many years, but most enterprises’ data is still lying idle in the server. It should be noted that the key to the success or failure of AI projects lies in three things: data, data quality, and permission system. This set of cards has always been in the CIO’s hand, but no one has ever played it seriously.
Third, shift from delivering projects to delivering capabilities
Stop reporting one project for one scenario, build an AI capability base, plus a scenario incubation mechanism. When the business department puts forward requirements, the CIO provides capabilities, and runs a prototype in the shortest possible time. In this way, what the superior sees is “efficiency”, and what the CIO gets is “irreplaceability”.
Fourth, learn to calculate accounts in the boss’s language
CIOs should not calculate how much money was spent on servers, how much money was saved on tokens, but calculate how many man-hours are saved, how much the error rate is reduced, and how customer response is shortened from hours to minutes. For the same thing, if you change the way of saying it, your position in the conference room will be completely different.
Fifth, cultivate a group of “translators”
CIOs need to cultivate a group of people who understand both business and AI. Their headcount belongs to the IT department, but they sit in the business department. These people are your eyes and hands, and the only channel for you to break through the departmental walls.
Under the enterprise-wide AI boom, will CIOs end up in the organizational “ICU”?
Lao Yang believes that some of them will, not because AI technology is too powerful, but because they are still facing the AI transformation with the mindset of managing systems.
So in your company, who is leading the AI implementation now? Is it the CIO, or the head of the business department? Feel free to share in the comment section.
This article is from WeChat official account “Xiangjiang Digital Review” (ID: benpaoshuzi), written by Lao Yang, authorized to release by 36Kr.
该文观点仅代表作者本人，36氪平台仅提供信息存储空间服务。
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