Certification details change. Always confirm final pricing, availability, and credential terms on the official provider page linked in the sources below before you pay for anything.
What the numbers say about this work
Government occupation data for the role this maps to — Data Scientists (SOC 15-2051). This is planning context for the occupation, not a salary or a job this role guarantees you.
Median pay (occupation)
$120,230 / yr · $67,240 to $199,130 (10th–90th percentile)
The national median hides a wide geographic spread. Below is the occupation’s median in some of the highest-paying and largest-employment metros, adjusted for local prices — regional price-level context, not take-home pay or a salary this role guarantees you.
The tasks the U.S. Department of Labor’s O*NET lists most central to this occupation — role-fit evidence to weigh against your background, not a measure of employer demand.
Analyze, manipulate, or process large sets of data using statistical software.
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
Clean and manipulate raw data using statistical software.
Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
Create graphs, charts, or other visualizations to convey the results of data analysis using specialized software.
The skills and certifications most often named in a balanced sample of 772 public job postings from at least 72 employers and 4 source families. Treat it as a to-learn list — it is dated hiring language, not total demand, personal hiring odds, or salary.
Most-named skills
Machine learning 440
Python 382
LLM 313
PyTorch 134
AWS 132
OpenAI 130
SQL 126
API 108
Problem solving 107
Okta 92
Asana 90
GCP 85
Certifications named
CCNA 1
Security+ 1
Compare what employers ask across roles → Qualitative employer-language sample only; do not use as official demand, market-size, salary, or certification ROI evidence.
Evidence stack
How we know this
Evidence chips, posture, citations, and blocked-claim boundary.
3 visible citations
Claim-source mapcitation infrastructure
Visible linkage between page claims, source rows, citation IDs, freshness, and review state.
Source posturesource governance
Whether a page has current, partial, stale, missing, or blocked source coverage.
Freshness rulesource governance
How recently the source must be checked before a claim or page can render as current.
Blocked-claim policyeditorial governance
Transparent explanation of claims RoleMath refuses to make without exact support.
What this page will never claim
Exam pass rates
Job placement rates
Any job guarantee
A salary figure attributed to this certification
A salary prediction for you personally
Return on investment or a payback period
View table fallback
Section
Value
Source layer
Caveat
Posture
no_certification_source_links
source posture
Draft status; source posture must pass before public launch.
Visible citation count
3
claim source map
Citation count does not imply page is public-ready.
Certification decision support
Certifications mapped to AI Specialist
Certifications mapped to this role from cited OEM target-role data and the RoleMath role mapping, ordered by relationship strength and then Difficulty Score. This is planning context — not a guarantee, not an employer requirement, and not a claim that any one certification is best for everyone. Your fit depends on your background; pay/outlook context is occupation-level on the role page.
Start here signalCisco AI Technical PractitionerWe have not recorded a stated experience requirement for Cisco AI Technical Practitioner, so how hard it is depends entirely on what you already know.
Entry and starting signals
2 mapped
Credentials that map to this role as starting points or foundation signals.
CompTIA DataAI is advanced and better suited after data science experience.Official source
Experience expected is what the vendor publishes about the background it asks for or recommends — never a pass rate, and never a RoleMath rating of how hard an exam is. Certification mappings are planning context, not employer requirements, job guarantees, salary claims, or ROI claims.
BLS wage context
National salary context
BLS wage range with explicit occupation-level caveat.
Occupation-level onlyNot a certification salary, personal prediction, ROI, placement, or guarantee.
10th percentile
$67,240
Median
$120,230
90th percentile
$199,130
BLS wage dataSOC mapping caveatSource posture
View salary table fallback
Measure
Value
Source layer
Caveat
10th percentile
$67,240
bls occupation context
U.S. national occupation-level wage context only.
Median
$120,230
bls occupation context
Not a certification salary or personal prediction.
90th percentile
$199,130
bls occupation context
Requires SOC mapping caveat; use metro pages for local wages.
Transition evidence
Transition map
Node-edge transition map with relationship-confidence guardrail.
Relevance, not promise
Current pageHow to become an AI Specialist
O*NET/BLS role context only; not a guaranteed progression.
O*NET role evidence
Related roleAI Specialist
Role mapping is source context, not a hiring or salary guarantee.
O*NET role evidence
Credential optionCisco AI Technical Practitioner
Credential facts come from official/vendor sources; employer use varies.
Official certification source
Relationship evidencefoundation, priority 4/5
Relationship confidence explains relevance only; it is not outcome proof.
Role-cert relationship evidence
Next actionCompare fit, cost, study time, and local labor context
Personalized sequencing requires intake answers and review.
Role-cert relationship evidence
O*NET role evidence
Tasks, skills, knowledge, work activities, job zone, and role-fit inputs.
Official certification source
Exam name, credential level, exam objectives, prerequisites, renewal, official resources.
Role-cert relationship evidence
Why a certification is related to a role, skill, task, or transition stage.
Employer language sample
Title variants, wording, common tools, and resume/quiz phrasing.
Does not support: Salary, demand, certification requirement, individual fit guarantee, ROI, placement, pass rate, job guarantee, Employer requirement proof, guaranteed hiring advantage, salary increase, probability of hire, certification requirement unless officially stated.
Not claimed here
Exam pass rates
Job placement rates
Any job guarantee
A salary figure attributed to this certification
A salary prediction for you personally
Return on investment or a payback period
View transition table fallback
Node
Value
Source layer
Caveat
Current page
How to become an AI Specialist
onet role feature
O*NET/BLS role context only; not a guaranteed progression.
Related role
AI Specialist
onet role feature
Role mapping is source context, not a hiring or salary guarantee.
Credential option
Cisco AI Technical Practitioner
oem credential fact
Credential facts come from official/vendor sources; employer use varies.
Relationship evidence
foundation, priority 4/5
role cert relationship
Relationship confidence explains relevance only; it is not outcome proof.
Next action
Compare fit, cost, study time, and local labor context
role cert relationship
Personalized sequencing requires intake answers and review.
Answer blocks
Common Questions
What certifications do I need to become a AI Specialist?
Certifications commonly mapped to a AI Specialist role, ordered by mapped relationship strength and then difficulty: Cisco AI Technical Practitioner; CompTIA Data+ — with advanced credentials such as CompTIA DataAI as later steps.
Entry options, closest role match first: Cisco AI Technical Practitioner (Cisco; Difficulty Score 20/100, Foundational; exam ~$150); CompTIA Data+ (CompTIA; Difficulty Score 30/100, Foundational; exam ~$264). Advanced or later-step credentials: CompTIA DataAI (CompTIA; Difficulty Score 85/100, Expert; exam ~$544).
Citations:Sources shown on this page: 3 citations. Each mapped certification's official source is linked in the decision table on this page.
Use the RoleMath planner to adapt this sequence to your background, budget, and timeline. No provider can pay to change what this page says.
What is the easiest certification to start a AI Specialist career?
The lowest-difficulty cited certification mapped to a AI Specialist path is Cisco AI Technical Practitioner (RoleMath Difficulty Score 20/100, Foundational, exam ~$150). It is a starting signal, not a guarantee of a role.
Entry options, closest role match first: Cisco AI Technical Practitioner (Cisco; Difficulty Score 20/100, Foundational; exam ~$150); CompTIA Data+ (CompTIA; Difficulty Score 30/100, Foundational; exam ~$264).
Citations:Sources shown on this page: 3 citations. Each mapped certification's official source is linked in the decision table on this page.
Use the RoleMath planner to adapt this sequence to your background, budget, and timeline. No provider can pay to change what this page says.
How much do AI Specialist certifications cost and how hard are they?
Cited AI Specialist certification exam fees range roughly $150–$544, spanning from Foundational entry options to Expert credentials on the RoleMath Difficulty Score. Pay and outlook are reported at the occupation level on the AI Specialist page, never per certification.
Entry options, closest role match first: Cisco AI Technical Practitioner (Cisco; Difficulty Score 20/100, Foundational; exam ~$150); CompTIA Data+ (CompTIA; Difficulty Score 30/100, Foundational; exam ~$264).
Citations:Sources shown on this page: 3 citations. Each mapped certification's official source is linked in the decision table on this page.
Use the RoleMath planner to adapt this sequence to your background, budget, and timeline. No provider can pay to change what this page says.
Quick Verdict
"AI specialist" is an emerging, not-yet-standardized role - for labor-market context RoleMath maps it to the BLS occupation Data Scientists (SOC 15-2051), which reports a $120,230 median wage (2025, occupation context, not a guarantee). A realistic path emphasizes data literacy first; foundational credentials like CompTIA Data+ support that, but no single exam makes you an "AI specialist."
Cited Detail
"AI specialist" isn't a settled job title with its own BLS occupation, so we map it to Data Scientists (SOC 15-2051) for context until AI-specific data exists - treat every figure as occupation-level evidence, not a guarantee. This reads as an early-to-mid role, not entry-level. On credentials: CompTIA Data+ (DA0-002) supports data literacy but isn't an "AI specialist" credential; Cisco AI Technical Practitioner (810-110) can support AI fluency but isn't a standalone AI job credential; CompTIA DataAI (DY0-001) is advanced, better after data-science experience - CompTIA recommends 5+ years in data science or a similar role (a recommendation, not a requirement). Realistic sequence: foundations -> applied data work -> AI-specific depth (planning context, not a promise). Outlook: BLS projects Data Scientists to grow 33.5% over 2024-2034, ~23,400 openings/yr - a multi-year occupation-level projection, not specific to the emerging "AI specialist" label.
AI & this career
What we can — and can’t — tell you about AI and this role
Cited context only: an occupation-level outlook, descriptive usage data, an employer-language sample, and attributed research — kept separate. No RoleMath AI score, no automation timeline, no job-loss prediction.How we source this →
A forecast, not a guarantee; occupation-level, not about you - and BLS does not model rapid AI adoption, so this is never an AI prediction.
How AI shows up in the work
Descriptive usage, not demand or loss
For this O*NET detail, the May 2026 usage sample reports 52.57% of Claude conversations augmenting the person's work and 47.43% automating a task. Anthropic · checked Anthropic Economic Index dataset, CC-BY.
Across all occupations the same dataset splits 51.4% augmentation / 48.6% automation (May 2026) — shown so a single role’s number is never read as an outlier.
Descriptive Claude usage data, not employment demand, not job loss, and not a personal forecast; CC-BY attribution required.
Employer language · sample
What a posting sample mentions
a sample of 440 postings (as of 2026-07-09) mentions these AI-related terms
Employer-language sample only; not official demand, market-size, salary, or certification ROI evidence.
Published research · attributed
What independent research says (not RoleMath’s claim)
Eloundou et al. estimate that about 80% of U.S. workers have at least 10% of their work tasks exposed to large language model capabilities (Science 2024). American Association for the Advancement of Science · checked exposure = task overlap, not job loss.
Eloundou et al. estimate that about 19% of U.S. workers have at least 50% of their work tasks exposed to large language model capabilities (Science 2024). American Association for the Advancement of Science · checked exposure = task overlap, not job loss.
Eloundou et al. explicitly disclaim any forecast of AI adoption or timing, describing their measure as capability overlap with tasks rather than a prediction of job loss (Science 2024). American Association for the Advancement of Science · checked exposure = task overlap, not job loss.
OECD and the AIOE research find that AI exposure and automation risk often run in opposite directions, with the most-exposed high-skill occupations tending to be the least at risk of automation. Organisation for Economic Co-operation and Development · checked exposure = task overlap, not job loss.
Felten, Raj and Seamans construct an occupation-level AI Occupational Exposure index by linking AI capabilities to O*NET occupational abilities (Strategic Management Journal). Strategic Management Journal (Wiley) · checked exposure = task overlap, not job loss.
Stanford Digital Economy Lab researchers find a roughly 16% relative decline in employment for workers ages 22-25 in the most AI-exposed occupations, based on high-frequency ADP payroll data (Canaries in the Coal Mine, working paper). Stanford Digital Economy Lab · checked correlational usage data, not proof.
The ILO notes that AI-exposure indicators measure potential task overlap and cannot by themselves establish job loss (Workers' exposure to AI). International Labour Organization · checked exposure = task overlap, not job loss.
The Anthropic Economic Index reports no measured systematic rise in unemployment attributable to AI in its usage data. Anthropic · checked correlational usage data, not proof.
Tier A research stays attributed and separate from BLS outlook and employer-language samples.
Where to go next
These pages draw on the same sourced data, and are the closest to what you just read.
This table lists the page’s core content records and when they were checked. Claim-specific citations appear beside the relevant text and may not be repeated here.
ID
Supports
Source
Checked
CIT-01
Supports occupation-level wage context for AI Specialist.