Stable

Last Update: 3/13/2026

Your role’s AI Resilience Score is

78.5%

Median Score

Changing Fast

Evolving

Stable

Our confidence in this score:
Medium-high

What does this resilience result mean?

These roles are expected to remain steady over time, with AI supporting rather than replacing the core work.

AI Resilience Report for

Neurologists

They help people with brain and nerve issues by diagnosing problems and providing treatments to improve their conditions.

This role is stable

A career in neurology is considered "Stable" because AI tools mainly assist with tasks like reading brain scans, but they don't replace the essential human roles. Neurologists are still crucial for making final diagnoses, planning treatments, and providing personal care, which require human judgment and empathy.

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Learn more about how you can thrive in this position

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Chat with Coach
Latest news
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Analysis
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This role is stable

A career in neurology is considered "Stable" because AI tools mainly assist with tasks like reading brain scans, but they don't replace the essential human roles. Neurologists are still crucial for making final diagnoses, planning treatments, and providing personal care, which require human judgment and empathy.

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Contributing 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

Learn about this score
Evolving iconEvolving

68.8%

68.8%

Microsoft's Working with AI

AI Applicability

Learn about this score
Evolving iconEvolving

58.6%

58.6%

Will Robots Take My Job

Automation Resilience

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Stable iconStable

96.6%

96.6%

Althoff & Reichardt

Economic Growth

Learn about this score
Stable iconStable

88.1%

88.1%

Low Demand

Labor Market Outlook

We use BLS employment projections to complement the AI-focused assessments from other sources.

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Growth Rate (2024-34):

5.4%

Growth Percentile:

76.1%

Annual Openings:

300

Annual Openings Pct:

2.2%

Analysis of Current AI Resilience

Neurologists

Updated Quarterly • Last Update: 2/17/2026

Analysis
Suggested Actions
State of Automation

What's changing and what's not

In neurology today, AI mostly helps with brain scans and data, not replacing doctors. For example, researchers report that machine learning has had “notable success” finding problems in MRI/CT brain images [1]. AI tools can quickly flag stroke or bleeding on scans, cutting critical minutes off diagnosis and treatment [1].

Other programs are being built to spot early signs of dementia or Parkinson’s disease on MRI, which could aid neurologists with diagnosis [1]. Even though these tools help read images, doctors still make the final call. By contrast, we found no reports of AI fully ordering things like physical therapy or social support; those tasks need human judgment.

One review notes that AI can “optimize rehabilitation” through smart analytics and robots, but only as an assistant – the neurologist and therapy team set the plan [1]. Lab tests too are mostly interpreted by people. In research, AI can crunch data or measure brain volumes, but human scientists still design studies and care for patients [1].

In short, AI augments neurologists by speeding routine imaging and analysis, while tasks involving personal care and complex decision-making remain largely human-led [1] [1].

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AI Adoption

AI in the real world

Neurology’s use of AI is growing but mixed. In areas like stroke imaging, FDA-cleared AI apps already exist and can quickly flag clots, so hospitals are adopting these tools [1]. Easy availability of such AI (and evidence of better outcomes) encourages rapid use.

However, many barriers slow other AI. Building AI for doctors is expensive and requires big data and staff training – hospitals must weigh those costs against already-high doctor wages. Also, medicine is high-stakes and regulated, so doctors move cautiously.

Experts stress that clinicians must learn how to interpret AI outputs and trust verified systems [1] [1]. In practice, AI is adopted faster for tasks with clear benefits (like quick scan reads) and harder for things needing nuanced care. Overall, AI tools are real and helpful in neurology (so-called “augmented intelligence”), but human skills like examining patients, communicating, and ethical judgment remain essential [1] [1].

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More Career Info

Task-Level AI Resilience Scores

AI-generated estimates of task resilience over the next 3 years

1

90% ResilienceCore Task

Participate in continuing education activities to maintain and expand competence.

2

90% ResilienceCore Task

Refer patients to other health care practitioners as necessary.

3

90% ResilienceCore Task

Advise other physicians on the treatment of neurological problems.

4

90% ResilienceCore Task

Prescribe or administer medications, such as anti-epileptic drugs, and monitor patients for behavioral and cognitive side effects.

5

90% ResilienceCore Task

Inform patients or families of neurological diagnoses and prognoses, or benefits, risks and costs of various treatment plans.

6

90% ResilienceCore Task

Perform or interpret the outcomes of procedures or diagnostic tests such as lumbar punctures, electroencephalography, electromyography, and nerve conduction velocity tests.

7

85% ResilienceCore Task

Provide training to medical students or staff members.

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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