Last Update: 3/13/2026
Your role’s AI Resilience Score is
Median Score
Changing Fast
Evolving
Stable
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.
What does this resilience result mean?
These roles are shifting as AI becomes part of everyday workflows. Expect new responsibilities and new opportunities.
AI Resilience Report for
They solve complex computer problems by developing new technology and improving how computers work, helping make our digital world faster and smarter.
This role is evolving
This career is labeled as "Evolving" because AI is increasingly being used to handle routine tasks like writing code, which lets researchers focus on bigger challenges. While AI tools can make work faster, they can't fully replace the creativity, problem-solving, and communication skills that humans bring to the table.
Read full analysisLearn more about how you can thrive in this position
Learn more about how you can thrive in this position
This role is evolving
This career is labeled as "Evolving" because AI is increasingly being used to handle routine tasks like writing code, which lets researchers focus on bigger challenges. While AI tools can make work faster, they can't fully replace the creativity, problem-solving, and communication skills that humans bring to the table.
Read full analysisContributing Sources
We aggregate scores from multiple models and supplement with employment projections for a more accurate picture of this occupation’s resilience. Expand to view all sources.
AI Resilience
AI Resilience Model v1.0
AI Task Resilience
CareerVillage's proprietary model that estimates how resilient each occupation's tasks are to AI automation and augmentation
Microsoft's Working with AI
AI Applicability
Measures how applicable AI tools (like Bing Copilot) are to each occupation based on real usage patterns
Anthropic's Observed Exposure
AI Resilience
Based on observed patterns of how Claude is being used across occupational tasks in real conversations
Will Robots Take My Job
Automation Resilience
Estimates the probability of automation for each occupation based on research from Oxford University and other academic sources
Althoff & Reichardt
Economic Growth
Measured as "Wage bill" which is a long term projection for average wage × employment. It's the total labor income flowing to an occupation
Medium Demand
We use BLS employment projections to complement the AI-focused assessments from other sources.
Learn about this scoreGrowth Rate (2024-34):
Growth Percentile:
Annual Openings:
Annual Openings Pct:
Analysis of Current AI Resilience
Comp & Info Research Sci
Updated Quarterly • Last Update: 2/17/2026

What's changing and what's not
Right now, many routine parts of a computer science research job are being helped by AI, but key decisions still need people. For example, modern coding tools can autocomplete or even write whole functions. In fact, over half of programmers were using AI helpers by 2024 [1].
Studies find these tools can speed up coding but risk students not learning everything deeply [2]. In other words, AI is a powerful helper, not a full replacement. One report notes AI “supports many tasks, particularly those involving research, writing, and communication” but cannot fully perform an entire occupation [3].
In plain words, computers can crunch data or draft code so scientists can focus on bigger problems. As one expert says, “the future of software development isn’t about typing faster – it’s about thinking bigger while AI handles the details” [1]. Tasks that depend on human judgment and social skills – like judging if a project plan is workable, talking with team members, or deciding how to train new staff – are still mostly done by people today.

AI in the real world
AI tools are widely available, which speeds adoption in computing fields. Big companies already use code-generation AI, so researchers are likely to use them too [1]. Also, these scientists earn high pay, so using AI to boost productivity has clear financial benefits.
However, adoption may be cautious. Research work often needs creativity and deep understanding, so experts warn against relying too much on AI. One study found that when programmers let AI do the work, they finished tasks faster but learned less about the code [2].
In addition, trust and safety issues matter: leaders still want humans to check AI results in critical projects. Overall, most analysts expect AI to augment research scientists (help them work faster) rather than fully replace them [3] [2]. The human skills of problem-solving, communication, and teaching teams remain very important – AI can help with some parts, but the science job still needs a human touch.

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Median Wage
$140,910
Jobs (2024)
40,300
Growth (2024-34)
+19.7%
Annual Openings
3,200
Education
Master's degree
Experience
None
Source: Bureau of Labor Statistics, Employment Projections 2024-2034
AI-generated estimates of task resilience over the next 3 years
Participate in staffing decisions and direct training of subordinates.
Meet with managers, vendors, and others to solicit cooperation and resolve problems.
Participate in multidisciplinary projects in areas such as virtual reality, human-computer interaction, or robotics.
Analyze problems to develop solutions involving computer hardware and software.
Evaluate project plans and proposals to assess feasibility issues.
Maintain network hardware and software, direct network security measures, and monitor networks to ensure availability to system users.
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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