Both things can be true at the same time. You can have a job and still feel insecure about asking for what you need.
What would make things better for you and even more productive, could be a raise, a more manageable workload, bespoke training but it could mean more flexibility, better internal communication so you feel more like a part of the team or have a clearer understanding of the larger goals.
Then there is this; you may have already taken on more responsibility, learned new systems, and helped your organization navigate yet another change. You have quantifiable reasons to ask for what you need. But your hesitation may be because the conversations around the office keeps circling around what AI can do faster or cheaper, leading you to question and doubt how much room you have to negotiate.
That is a part of the AI conversation we need to examine more closely.
We spend considerable time asking whether AI will replace people. There is another question worth asking while you are still employed: is it changing the terms you feel able to accept—or challenge?
In an October 13 speech, European Central Bank Chief Economist Philip Lane warned that the possibility of AI replacing some workers could weaken their bargaining power and moderate wage growth. He also said the ECB had not yet seen a major change in overall employment trends.[1]
That is a warning about a possible effect, not a finding that AI has already reduced everyone's pay. But it puts language around a concern that a layoff count cannot capture.
Your job can remain in place while your negotiating position changes.
What happens before a job disappears?
Imagine preparing for a conversation about compensation.
You can explain what you have delivered. You know where you have taken responsibility, prevented problems, or helped other people do their work. Then the discussion turns to automation: some of those tasks may take less time now.
There is a legitimate conversation to have about how technology changes work. The difficulty comes when faster completion becomes the whole explanation of its value.
A report can take minutes to produce. Knowing whether its conclusions make sense may still require years of experience.
A response can be generated quickly. Recognizing when it will confuse a client, overlook an exception, or create a problem elsewhere requires context.
For experienced professionals, much of that work can be difficult to see precisely because it happens before something goes wrong. You notice the missing information. You know which question to ask. You recognize when the apparently straightforward answer does not fit the situation.
If a compensation conversation counts only the time required to produce an output, it can miss the responsibility required to stand behind it.
Uncertainty can enter the negotiation
Bargaining power is partly about the alternatives available to you.
If another suitable role feels attainable, you approach a difficult conversation with a different sense of choice. If the market feels uncertain, the calculation changes. You may decide that asking for more carries a risk you cannot comfortably take.
AI can become part of that uncertainty even before anyone can demonstrate what it will replace.
That does not mean every employer is using AI to pressure staff, or that every hesitation about pay comes from technology. It means the possibility of replacement deserves attention alongside actual changes in work.
The question becomes personal: am I accepting these terms because they work for me, or because I no longer believe I have room to question them?
Your answer may be complicated. Financial commitments, family responsibilities, health, and the availability of suitable work all matter. Staying can be a considered decision. You should still be able to understand what that decision is costing you and what you are receiving in return.
Make the value of your judgment visible
One useful place to begin is with work you have already done.
Recall a situation where completing the task was only part of the responsibility. What needed interpretation? What did you notice that changed the decision? What happened because you intervened?
Be specific. “I bring twenty years of experience” tells someone how long you have worked. Explaining how you recognized a faulty assumption before a project proceeded shows what that experience contributed.
This is also a way to examine your own position. Which parts of your work are becoming easier to produce? Which still depend on your judgment? Has your responsibility changed along with the tools?
Those questions can help you prepare a clearer conversation about compensation, scope, support, or progression. They cannot guarantee the answer you want. They can help you avoid entering that conversation with your contribution reduced to a list of tasks.
Employers have a responsibility here, too
If you lead a team, consider what employees hear when you discuss AI.
Are you explaining how responsibilities will change, how people will be supported, and how their contribution will be evaluated? Or are you leaving them to interpret repeated references to savings and efficiency?
People need enough clarity to participate in change and raise reasonable concerns. Their willingness to remain employed should not be treated as agreement with every new condition.
AI may change the work. How an organization recognizes, rewards, and involves its people remains a choice.
For the professional navigating this, keeping your job is an important outcome. So is retaining the ability to speak about the conditions under which you do it.
Pay attention to what is changing in your work—and to what you have stopped feeling able to ask for.
[1] Philip R. Lane, “The AI opportunity for Europe,” European Central Bank, October 13, 2026.
The speech identifies a possible effect on bargaining power; it does not establish that AI has already caused widespread wage suppression.