Top 5 Jobs in Government That Are Most at Risk from AI in Buffalo - And How to Adapt

Buffalo government workers should pay attention because AI adoption in state and local agencies has jumped from 13% five years ago to about 45% today, yet a New York State audit found agencies “lack an effective AI governance framework” and ITS's January 2024 AI policy leaves gaps on testing for bias and transparency - creating risks for accuracy, fairness, and routine workflows across Buffalo's public services (OSC, Apr 2025).

EY's survey also names training and upskilling as a top AI priority, so practical, work-focused courses that teach tool use, prompt-writing, and responsible implementation - like Nucamp's 15-week AI Essentials for Work - offer a concrete path for staff to protect service quality and stay relevant as agencies modernize.

Read the New York audit, the EY survey, or explore the AI Essentials course for next steps.

“AI offers a powerful opportunity to achieve greater efficiency in a resource-constrained environment.… The real opportunity lies in agencies proactively embedding governance and security measures from the outset of their AI journey to fuel, rather than hinder, efficiency gains.” - EY press release

Rankings combined three evidence-driven signals to show which Buffalo public-sector roles face the greatest near-term disruption: the proportion of daily work that is routine and transaction-based, whether an agency has active automation or modernization projects, and the level of state investment or funded pilots that can scale AI tools.

Sources included New York's FY26 AI strategy - highlighting a $90 million boost to the Empire AI consortium and statewide upskilling initiatives - used to gauge upstream capacity and training availability (New York Empire AI expansion and FY26 investments); explicit modernization contracts and automation plans - such as the DMV overhaul that will automate paper forms covering roughly 70% of DMV business - to measure operational exposure (New York DMV technology overhaul introducing automation); and targeted funding calls for decision tools in child welfare to identify pilot projects that replace intake work (OCFS funding for automated child protective intake tools).

Job risk scores weighted transaction volume most heavily - so a clerk processing thousands of repetitive forms ranks higher than a coordinator with judgment-heavy duties - while local use cases and training availability calibrated practical adaptation paths.

“Whoever leads in the AI revolution will lead the next generation of innovation and progress, and we're making sure New York State is on the front lines. With these bold initiatives, we are making sure our state leads the nation in both innovation and accountability. New York is not just keeping pace with the AI revolution – we are setting the standard for how it should be done.” - Governor Kathy Hochul

Records clerks and data‑entry staff in Buffalo face high near‑term exposure because modernization efforts target the repetitive, form‑filled workflows those roles handle: New York's multi‑year DMV overhaul will replace and consolidate legacy systems that account for roughly 70 percent of DMV business volume, explicitly introducing automation and eliminating paper forms (New York DMV technology overhaul press release).

Practical RPA pilots show how fast routine work can disappear - The New York Foundling recovered about 100,000 staff hours annually by automating manual data entry across systems (RPA at The New York Foundling case study) - which means bulk clerical throughput in Buffalo agencies could be replaced or redefined within a few years.

The operational takeaway: clerks should pivot from keystroke tasks to bot supervision, exception triage, and data quality assurance, and agencies should co‑design pilots that retrain staff into RPA operators or audit specialists rather than defaulting to layoffs; local use cases like automated fraud detection for benefits show where those hybrid roles will matter most (Automated fraud detection and AI use cases in Buffalo government).

“As a former County Clerk, I know first-hand the importance of the DMV in providing critical services to New Yorkers. These investments are a major step forward in the DMV's strategic modernization as we look to create a quicker, easier and more convenient experience for everyone.” - Governor Kathy Hochul

Eligibility processors and benefits‑case processors in Buffalo face high near‑term exposure because New York already uses automated decision‑making for functions like awarding public benefits, and the new Legislative Oversight of Automated Decision‑making in Government (LOADinG) Act changes how agencies can deploy those tools - requiring public disclosure of AI use, direct human review, approval before deployment, biannual reports to the governor, and an explicit prohibition on replacing government workers (New York LOADinG Act overview on StateScoop).

Practically, that means routine, rule‑based approvals are the most likely to be automated, while human roles will shift toward exception triage, bias and audit review, and supervising RPA/AI workflows.

One concrete takeaway: the required two‑year reporting creates a public record agencies and unions can use to argue for funded retraining instead of layoffs. Local pilots - like automated fraud detection that flags anomalous claims and surfaces investigative leads - illustrate a clear transition path from high‑volume processing to case‑audit and bot‑supervision roles (automated fraud detection for public benefits case management).

Entry-level IT programmers and routine support specialists in Buffalo sit at medium–high risk because the day-to-day tasks that define many junior roles - boilerplate coding, unit-test generation, ticket triage, and routine debugging - are precisely what modern AI assistants accelerate or automate: generative tools already produce roughly 30% of new code at large firms and speed common developer tasks dramatically (BCG report on AI-assisted coding), while reporting from The New York Times documents graduates struggling to convert applications into starter jobs as employers lean on AI for screening and simple development work (New York Times coverage of graduates' job struggles with AI).

The practical consequence for Buffalo: fewer pure “write-this-code” apprenticeships and more demand for people who can validate AI output, perform security and edge-case testing, and orchestrate agentic workflows - skills taught by local upskilling programs and university partnerships that transform juniors into AI‑savvy reviewers (Buffalo AI training and upskilling programs for government IT).

So what: to keep a career ladder, junior hires must prove they can safely edit, audit, and integrate AI-generated code, not just produce it.

“Those positions that are most likely to be automated are the entry-level positions that [recent grads] would be seeking.” - Matthew Martin, U.S. senior economist at Oxford Economics

Project coordinators and operational analysts in Buffalo sit at a medium risk because the routine pieces of their day - status updates, meeting recaps, scheduling, basic risk flags, and portfolio-level visibility - are exactly what AI project assistants and automation now handle, while the judgment‑heavy work of stakeholder alignment and exception triage stays human; HBR argues AI will give leaders a smartphone view of entire portfolios, and Airtable documents common use cases like automated status updates, meeting summaries, and smarter resource allocation that shrink tedious admin time (Harvard Business Review: How AI Will Transform Project Management, Airtable guide to AI for project management).

The practical response for Buffalo staff: run controlled pilots, own the what‑if analysis and model validation, and reframe roles toward interpreting forecasts and managing stakeholder tradeoffs - skills that pay off: Epicflow clients reported on‑time delivery rising from 18% to 80% and lead time cut by 50%, a concrete signal that coordinators who master AI validation and scenario testing will be the people who keep projects on track rather than be sidelined by automation (Epicflow case study and analysis of AI in project management).

“One of the features I like most in Epicflow is the AI-driven What-If Analysis, which gives us the ability to see the future. I can see what will happen if we proceed the way things are happening now... The What-If Analysis provides us with this opportunity so that I may act now and prevent bottlenecks before they appear.”

HR clerks who run payroll, enforce wage rules, and manage compliance in Buffalo face a medium risk: many tasks are rule‑based and automatable, but recent New York proposals and guidance make outright replacement difficult and shift work toward governance, notice, and audit functions.

The proposed New York State AI employment law requires independent bias audits, public disclosure of results, and employee notice - plus the right for candidates to request alternative evaluations - which preserves a human role in compensation and promotion decisions (Summary of the New York State AI employment law bill).

Electronic monitoring may be allowed for administering wages and benefits, but only if it is the least invasive option and workers are informed, so payroll teams will likely spend more time validating tool outputs, documenting data‑handling practices, and coordinating audits; violations carry fines and enforcement risk (see analysis of S07623) (S07623 bill analysis and implications for employers).

Practical next steps for HR staff: learn bias‑audit basics, own transparency notices, and train on tool‑validation workflows using local upskilling options that target government roles (Buffalo AI training and upskilling programs for government HR) - a concrete payoff is protecting jobs by becoming the department's required compliance and human‑review experts rather than passive users of opaque systems.

“Taken together, the use of these tools would be restricted and employers would not be able to solely use technology to make certain employment decisions.”

Next steps for Buffalo government workers are practical and immediate: treat the new state rules and rising cyber risk as a call to learn the exact skills that will keep jobs local - validating model outputs, supervising RPA, running bias audits, and documenting chain‑of‑custody - rather than competing with a black‑box tool.

Start by using state guidance and training resources for secure deployment (NYS Office of Information Technology Services cybersecurity and IT resources) and review new reporting and mandatory training requirements that change how localities respond to incidents (Coverage of New York's 2025 cyber law and local reporting requirements).

For a concrete, employer‑friendly upskilling path, consider Nucamp's 15‑week AI Essentials for Work (early‑bird $3,582) to learn prompt craft, tool validation, and job‑based AI workflows so staff move from data‑entry risk into bot‑supervision and governance roles - actionable skills that make a clerical role resilient within months, not years (AI Essentials for Work registration and syllabus).

“As global conflicts escalate and cyber threats evolve, so must our response, and we are taking a whole of government approach in doing so. Requiring timely incident reporting and providing annual cybersecurity training for government employees will build a stronger digital shield for every community across the State and ensure they get the support they need when it matters most.” - Gov. Kathy Hochul