Dermatologists

Counsel patients on topics such as the need for annual dermatologic screenings, sun protection, skin cancer awareness, or skin and lymph node self-examinations.

AI: Fully automatable - AI systems can reliably provide evidence-based, personalized counseling and educational materials on screening, sun protection, and self-examination, enabling full automation of routine patient education.

Record patients' health histories.

AI: Fully automatable - Advanced NLP, speech-to-text, and structured intake systems can accurately capture and record patient health histories from interviews and EHR data.

Diagnose and treat pigmented lesions such as common acquired nevi, congenital nevi, dysplastic nevi, Spitz nevi, blue nevi, or melanoma.

AI: Partial - AI can assist with image-based diagnosis and triage of pigmented lesions, yet it cannot fully replace clinical examination, biopsy procedures, and hands-on treatment decisions that carry medico-legal responsibility.

Conduct complete skin examinations.

AI: Partial - AI can assist with image-based remote skin assessments but cannot perform the hands-on inspection and palpation required for a complete in-person skin examination.

Diagnose and treat skin conditions such as acne, dandruff, athlete's foot, moles, psoriasis, or skin cancer.

AI: Partial - AI can aid image-based diagnosis and recommend treatments for many common dermatologic conditions but cannot fully replace clinician judgment or perform confirmatory invasive diagnostics required for some conditions like melanoma.

Prescribe hormonal agents or topical treatments such as contraceptives, spironolactone, antiandrogens, oral corticosteroids, retinoids, benzoyl peroxide, or antibiotics.

AI: Partial - AI can recommend hormonal and topical treatment options and dosing based on guidelines, but cannot legally or safely execute autonomous prescribing and monitoring without clinician oversight.

Recommend diagnostic tests based on patients' histories and physical examination findings.

AI: Partial - Clinical decision-support AI can generate evidence-based diagnostic test recommendations from history and exam data, but those recommendations require clinician interpretation and contextualization.

Provide dermatologic consultation to other health professionals.

AI: Partial - AI can synthesize data and literature to produce consult recommendations for other clinicians, but comprehensive dermatologic consultation relies on specialist judgment and responsibility that AI cannot fully assume.

Read current literature, talk with colleagues, and participate in professional organizations or conferences to keep abreast of developments in dermatology.

AI: Partial - AI can continuously scan, summarize, and surface relevant literature and conference outputs to keep clinicians informed, but it cannot fully replicate human professional networking, discussion, and active participation in organizations.

Instruct interns or residents in diagnosis and treatment of dermatological diseases.

AI: Partial - AI can generate teaching materials, simulate cases, and provide diagnostic feedback to trainees, but cannot fully replace human mentorship, bedside teaching, and professional supervision.

Refer patients to other specialists, as needed.

AI: Partial - AI can analyze records and guidelines to identify and recommend specialist referrals and draft referral orders, but cannot fully replace clinician judgment, patient communication, and legal/administrative sign-off.

Conduct or order diagnostic tests such as chest radiographs (x-rays), microbiologic tests, or endocrinologic tests.

AI: Partial - AI can recommend and in many systems auto-generate orders for diagnostic tests based on data and protocols, but cannot perform specimen collection or imaging studies and often requires clinician authorization.

Conduct clinical or basic research.

AI: Partial - AI can automate literature review, data analysis, hypothesis generation, and some experiment planning, but cannot independently carry out all aspects of clinical trials, patient interactions, or wet‑lab benchwork without human oversight.

Evaluate patients to determine eligibility for cosmetic procedures such as liposuction, laser resurfacing, or microdermabrasion.

AI: Partial - AI can screen photos, histories, and risk factors to assess candidacy for cosmetic procedures and flag contraindications, but cannot replace in‑person physical exam, aesthetic judgment, and final informed consent.

Perform incisional biopsies to diagnose melanoma.

AI: Not automatable - AI lacks the physical capability and procedural skill to perform incisional biopsies, which require hands-on surgical technique and immediate clinical decision-making.

Perform skin surgery to improve appearance, make early diagnoses, or control diseases such as skin cancer.

AI: Not automatable - Skin surgery requires manual dexterity, intraoperative judgment, and postoperative care that AI cannot physically perform or fully assume responsibility for.

Provide liposuction treatment to patients.

AI: Not automatable - Liposuction is an invasive surgical procedure requiring complex manual technique and real‑time surgical decision‑making that AI cannot autonomously perform in clinical practice in 2025.

Provide dermabrasion or laser abrasion to treat atrophic scars, elevated scars, or other skin conditions.

AI: Not automatable - Dermabrasion and laser procedures require precise hands‑on operation, patient management, and intra‑procedural judgment that cannot be fully automated by AI in routine care as of 2025.

Provide therapies such as intralesional steroids, chemical peels, or comodo removal to treat age spots, sun damage, rough skin, discolored skin, or oily skin.

AI: Not automatable - These are hands‑on procedural therapies requiring manual dexterity, tactile feedback, and intra‑procedure judgment that AI systems cannot autonomously perform in routine clinical practice as of 2025.