If AI-related duties have become a recurring part of your job, make the case for a raise by showing how your role has changed, what results you can verify, and how your pay compares with relevant roles. Using AI at work alone does not establish a reason for a raise, and no universal percentage applies to added AI responsibilities.
Build the case around how your job has changed
Start with the difference between your role before and after the AI work became part of it. Focus on responsibilities, judgment, and accountability—not simply the tools you use. The U.S. Department of Labor’s TEAMS Salary Negotiation Participant Guide 2026 recommends preparing your skills, experience, and added value to support your compensation request.
- Before: Record the duties you were originally hired to perform.
- Added or changed work: List recurring AI-related tasks, such as evaluating outputs, integrating tools into a workflow, or identifying when a result needs correction.
- Responsibility: Note decisions you make, what you review, and what outcomes or risks you are accountable for.
- Trade-offs: Clarify whether the new work adds to your workload or has replaced other duties.
One-off experimentation is different from sustained responsibility. Describe the work that has become an expected part of your role and how it affects its scope.
Document outcomes without inflating them
Keep a brief, dated log of examples that show what your expanded responsibilities contribute. Useful evidence may include time saved, increased throughput, improved service or quality, less rework, or a risk you identified. Use figures only when you can explain how they were measured; label estimates as estimates and avoid claiming that a result came from AI if other changes contributed.
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- Capture the date, task, and your role in the outcome.
- Record the evidence behind any number, such as a report, an agreed measurement, or a comparison with a documented baseline.
- Distinguish direct results from expected benefits or informal feedback.
- Use only material you are permitted to share. Do not paste confidential company information into an external AI service.
Find pay comparisons that fit your work
Use compensation data as context, not as a personalized promise. The U.S. Bureau of Labor Statistics’ OEWS salary-negotiation guidance describes May 2025 estimates covering about 830 occupations, with wage averages and distributions and data by occupation, state or area, and industry. The BLS notes that occupation, location, industry, experience, and education matter when interpreting wages.
Choose the closest occupation and level of responsibility, then compare the geography and industry where you work. If the AI work has changed your duties substantially, explain why the original job title or a published occupational category may not capture your current scope. Where several comparisons are credible, show why each is relevant rather than relying on the highest figure. Consider total compensation—not just base pay—and account for differences in benefits, bonus, or other terms.
The BLS says that understanding wage distributions by occupation, industry, and location can be valuable when requesting a raise. Its National Compensation Survey data-usage page also describes uses that include setting compensation rates for work with different duties and responsibilities and examining wage distributions. These sources can inform a conversation, but they do not reveal your employer’s pay band or dictate what your specific raise should be.
Choose a clear request
Decide what adjustment you are asking for before the meeting. Base a specific amount or range on your role, relevant pay comparisons, documented contribution, and total compensation—not on a broad claim that AI skills always command a premium. Be ready to explain how you arrived at the request and to discuss the full package.
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1Repair Windows errors before they cause bigger problems2Scan for outdated or missing drivers - takes under a minute3Clear out junk files and repair common Windows errorsResearch on AI pay does not supply a raise formula for this situation. A January 2025 IZA discussion paper by Konstantinos Pouliakas and Giulia Santangelo examined AI developers in 29 European countries and reported an average wage premium relative to comparable workers, including an unexplained component. That population and geography differ from an employee who has added AI tasks to an existing role; the result is not a target percentage for your negotiation. The paper is Are Artificial Intelligence (AI) Skills a Reward or a Gamble?
Make the conversation concise and specific
Ask for a meeting with your manager or the person who handles compensation. Explain the change in scope, give a few well-supported examples, state the adjustment you seek, and invite a discussion about process and timing. Adapt this framework to your circumstances:
“Over the past [period], my role has expanded to include [specific recurring AI-related responsibilities]. I’m accountable for [review, decisions, or outcomes]. Examples include [verified result and evidence]. I’d like to discuss adjusting my compensation to reflect this scope. Based on [relevant role, location, and industry comparisons] and these results, I’m seeking [specific amount or range]. What would be the right process and timing to review this?”
If your manager cannot approve an adjustment immediately, ask what measurable expectations would support one, who makes the decision, and when you can revisit it. This creates a clearer next step, but it does not guarantee a future increase.
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Prepare for questions and alternatives
Rehearse answers to likely questions: what changed, how the outcomes were measured, why the comparisons fit, and what you are requesting. If the employer cannot change base pay now, you can ask whether another term or a shorter review period is possible. Consider alternatives in relation to your priorities and the employer’s process; do not treat them as equivalent to a salary increase.
The Department of Labor guide suggests using AI to draft salary scripts, anticipate questions, practice scenarios, compare offers, and review salary data. Treat it as a rehearsal aid, not an authority: verify figures and claims against the original sources. Harvard Law School’s Program on Negotiation warns that AI can introduce errors and implicit biases in its guidance on using AI for salary negotiations.
What negotiation studies can—and cannot—tell you
A 2025 NBER working paper by Zoë B. Cullen, Bobak Pakzad-Hurson, and Ricardo Perez-Truglia reports two field experiments involving over 3,100 U.S. tech-sector job seekers. Light-touch encouragement increased negotiation attempts and compensation gains, while discounted coaching did not significantly affect attempts. The study concerns job seekers, not current employees asking for a raise after taking on AI work; it does not predict your outcome. See NBER Working Paper 33903.
Negotiation advice and pay rules vary by country, employer, and compensation process. The wage sources cited here are U.S.-oriented; use local data and guidance if you work elsewhere.
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