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The AI Resilience Report helps you understand how AI is likely to impact your current or future career. Drawing on data from over 1,500 occupations, it provides a clear snapshot to support informed career decisions.
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Resilient
Last Update: 4/23/2026
Your role’s AI Resilience Score is
66.2%
Median Score
Meaningful human contribution
Measures the parts of the occupation that still require a human touch. This score averages data from up to four AI exposure datasets, focusing on the role’s resilience against automation.
Med
Long-term employer demand
Predicts the health of the job market for this role through 2034. Using Bureau of Labor Statistics data, it balances projected annual job openings (60%) with overall employment growth (40%).
Med
Sustained economic opportunity
Measures future earning potential and career flexibility. This score is a blend of total projected labor income (67%) and the role’s inherent ability to adapt to economic and technological shifts (33%).
High
This reflects the reliability of your score based on the number of data sources available for this career and how closely those sources agree on the outlook. A higher confidence means more consistent evidence from labor experts and AI models.
Most data sources align, with only minor variation. This is a well-supported result.
Contributing sources
AI Resilience Report forNatural Sciences Managers
Natural Sciences Managers are more resilient to AI impacts than most occupations, according to our analysis of 6 sources.
Natural sciences managers are considered "Resilient" to AI impact because their jobs rely heavily on human creativity, leadership, and judgment, which AI cannot fully replicate. While AI tools can help with routine tasks like creating presentations and drafting reports, the most important decisions, such as setting research goals and managing budgets, still need a human touch.
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Natural sciences managers are considered "Resilient" to AI impact because their jobs rely heavily on human creativity, leadership, and judgment, which AI cannot fully replicate. While AI tools can help with routine tasks like creating presentations and drafting reports, the most important decisions, such as setting research goals and managing budgets, still need a human touch.
Read full analysisAnalysis of Current AI Resilience
Natural Sciences Managers
Updated Quarterly • Last Update: 2/17/2026
How is AI changing Natural Sciences Managers jobs?
Natural science managers oversee work like giving presentations, writing research reports, and drafting project proposals. AI tools are starting to help with these tasks. For example, new apps like Gamma can create a polished slide deck from a few lines of text in seconds [1].
Education tech reviews report that AI-powered slide generators (e.g. Beautiful.ai, Gamma) greatly reduce the formatting work by turning an outline into a finished presentation [2]. AI can also assist with reports and proposals. Some tools can search funding databases, suggest outlines, and format grant proposals automatically [3].
In one case, an AI system even gathered data from multiple sources and wrote out regular performance reports—jobs that used to need a person [4]. In practice, these tools speed up drafting, but people still check the results. For instance, AI-generated slides often need a human to edit for accuracy and tone [1].
Other tasks see little automation. Many companies use AI to scan resumes or schedule interviews [5], but final hiring decisions and staff training remain human-led. Setting research goals and budgets is mostly done by managers, even if AI analytics give some input.
Overall, AI can speed up routine parts of a science manager’s job (like assembling facts, notes, or visuals), but human creativity, leadership, and judgment remain key for the most important decisions.
Sources
How fast is AI adoption growing for Natural Sciences Managers?
Whether science teams adopt AI quickly depends on costs, trust, and need. On one hand, many AI tools are cheap or free and promise big gains. Surveys show executives expect AI to boost productivity and cut costs (some forecast ~20% savings [6]).
This makes labs want to try AI for writing, data work, or administration. On the other hand, putting AI into a lab can be expensive and risky. Managers must pay for software, data security, and staff training.
They also worry about mistakes or bias. People in hiring and research often insist on a human touch; experts warn that relying on AI too much in jobs like interviewing can hurt fairness and morale [5]. In the end, science groups will likely use AI for routine chores soon, but humans will keep the final say on strategy, budgets, and creative problem-solving.
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More Career Info
Career: Natural Sciences Managers
They lead and coordinate the work of scientists by planning projects, organizing research, and making sure everything runs smoothly and on time.
Parent Careers
Employment & Wage Data
Median Wage
$161,180
Jobs (2024)
104,300
Growth (2024-34)
+3.7%
Annual Openings
8,500
Education
Bachelor's degree
Experience
5 years or more
Source: Bureau of Labor Statistics, Employment Projections 2024-2034
Task-Level AI Resilience Scores
AI-generated estimates of task resilience over the next 3 years
1
Determine scientific or technical goals within broad outlines provided by top management and make detailed plans to accomplish these goals.
2
Plan or direct research, development, or production activities.
3
Advise or assist in obtaining patents or meeting other legal requirements.
4
Confer with scientists, engineers, regulators, or others to plan or review projects or to provide technical assistance.
5
Prepare and administer budgets, approve and review expenditures, and prepare financial reports.
6
Develop or implement policies, standards, or procedures for the architectural, scientific, or technical work performed to ensure regulatory compliance or operations enhancement.
7
Develop client relationships and communicate with clients to explain proposals, present research findings, establish specifications, or discuss project status.
Tasks are ranked by their AI resilience, with the most resilient tasks shown first. Core tasks are essential functions of this occupation, while supplemental tasks provide additional context.
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