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

Pennsylvania's move to expand AI in government after a successful ChatGPT Enterprise pilot is changing the math for many Philadelphia public‑sector jobs: the year‑long trial with 175 state employees saved an average of 95 minutes per day by automating writing assistance, research, brainstorming and summarizing, proving that routine, form‑based work - from permit reviews to housing recertifications - can be greatly sped up or centralized, which is why a Code for America analysis ranks Pennsylvania among the top three states for AI readiness.

Local pilots and big infrastructure bets mean more tools will arrive with guardrails and training, so frontline workers who learn to verify AI outputs and craft effective prompts - skills taught in Nucamp's AI Essentials for Work bootcamp - will be best positioned to adapt.

“You have to treat it almost like it's a summer intern, right? You have to double check its work.” - Cole Gessner, Block Center for Technology and Society

To pinpoint the five Philadelphia government roles most exposed to automation risk, the research team started with Pennsylvania's hands‑on evidence: the year‑long ChatGPT Enterprise pilot that involved 175 employees and showed broad wins for writing assistance, research, summarization and routine communications, with participants reporting positive experiences and an average time savings of 95 minutes per day - nearly two hours reclaimed for verification and follow‑up work - so jobs built around repetitive, form‑driven tasks rose to the top.

Selection criteria blended three practical filters drawn from the pilot and state readiness work: (1) task routineness and high volume (permit reviews, recertifications, templated correspondence), (2) direct alignment with documented pilot use cases and local trials (for example, housing recertification pilots and DEP permitting experiments), and (3) governance risk - whether existing policy requires human review or forbids AI decision‑making.

Roles scoring high on all three - caseworkers processing forms, housing processors, permit technicians, administrative clerks and communications staff - were flagged as at‑risk but also as priority candidates for upskilling, informed by the pilot findings in the Pennsylvania report and reporting on the state's broader rollout and readiness efforts.

“You have to treat it almost like it's a summer intern, right? You have to double check its work.” - Cole Gessner

Caseworkers at the Philadelphia Department of Human Services sit squarely at the intersection of routine paperwork and high‑stakes human judgment - processing recertifications, verifying documents, and drafting templated notices - so they're among the roles most exposed when AI can reliably handle repetitive drafting, extraction and summarization; the statewide pilot's big time savings and broader research on automation show why streamlining those tasks could shave hours from a caseworker's day but also shift the workload toward verification and client contact.

That potential productivity gain comes with hard guardrails: the Pennsylvania Bar Association's Joint Formal Opinion stresses duties of competence, confidentiality and citation verification when AI touches casework, and public‑sector practitioners are urged to lean on centralized resources and governance frameworks found in the Digital Government Hub to design audits, bias checks and disclosure practices.

Where properly governed automation - like document extraction to accelerate applications - meets human oversight, outcomes can improve (for example, reducing HACP recertification backlog and speeding access to benefits), but only if agencies pair tooling with training, clear rules for data handling, and explicit roles for caseworkers to double‑check AI outputs before residents feel the consequences.

Housing Authority processors are a clear near‑term example of how routine, document‑heavy workflows in Pennsylvania government can be reshaped: the Housing Authority of the City of Pittsburgh (HACP) is finalizing a one‑year, roughly $160,392 pilot with Bob.ai to scan recertification packets for about 5,100 voucher tenants, flag completed files and cut the manual choke points that leave families waiting - local reporting projects processing times could fall by 30–50% and backlogs by as much as 75%.

The vendor frames its tools as “AI assistants” that do preliminary work - organizing attachments, spotting missing signatures and generating backend reports - while human specialists keep decision authority; HACP has already paired the Bob.ai contract with a Google Gemini trial for 60 staffers and modest hiring (five new housing specialists) to stabilize caseloads.

For Philadelphia agencies with similar voucher or recertification rhythms, the lesson is familiar: well‑governed automation can shrink paperwork and free staff for the human side of housing work, but only if contracts, oversight and transparent reporting guard against bias and preserve the final human review step - otherwise the promise of cutting weeks from waitlists risks becoming a glitchy short‑cut.

Read reporting from Pittsburgh's Public Source and see Bob.ai's PHA solutions for more on the pilot.

“The AI will not be in charge, not making decisions.” - Caster Binion, HACP Executive Director

Permit technicians face one of the sharpest shifts because Pennsylvania's permitting experiments change who does the line‑by‑line work: DEP's new SPEED program lets applicants hire DEP‑approved professionals to fast‑track reviews (applicants pay the review fees while DEP keeps final sign‑off), and PADEP's construction stormwater pilot moved to a concurrent completeness and technical review that can cut average processing time from about 171 business days to roughly 98 - shrinking what used to be a five‑to‑six‑month slog to closer to three‑to‑four months.

That combination - external reviewers, clearer processing timelines, and tools like the Permit Tracker - means routine checklisting, spotting missing attachments and drafting deficiency letters are prime candidates for automation or centralization, which can free technicians for higher‑value oversight but also puts a premium on skills in verification, audit trails and clear disclosure practices; see reporting on DEP's SPEED rollout and the PADEP NPDES pilot for the mechanics, and consider public‑sector drafting safeguards for how to enforce fact‑checking before sending decisions out.

Administrative clerks - the backbone of office workflows who turn inboxes, template letters and dense reports into clear next steps - are squarely in the pilot's crosshairs: Pennsylvania's ChatGPT Enterprise trial (175 employees across 14 agencies) found that “administrative tasks like writing emails, summarizing documents” regularly benefited from generative AI, producing an average time savings of 95 minutes per day and freeing clerks to focus on verification, case follow‑up and customer service rather than repetitive drafting; read the pilot summary for the full findings and guidance on rolling this out responsibly.

That same state guidance stresses guardrails - training before use, bans on feeding private data into models, and a rule that AI must not make final decisions - so the realistic “so what?” is simple: one extra hour per day can be redirected to double‑checking outputs, catching bias, and helping a resident in crisis rather than wrestling with paperwork, but only if agencies pair tools with clear policies and hands‑on verification practices described in the lessons report.

“You have to treat (AI) almost like it's a summer intern, right? You have to double check its work.” - Cole Gessner

Communications specialists in Pennsylvania's state and local offices are squarely in the crosshairs because Google's Gemini is built to draft, localize and package messages inside the tools teams already use - Gmail, Docs, Sheets and Slides - so a single prompt can produce a press release, talking points and social captions in the time it takes to finish a coffee; that efficiency can free staff for verification, stakeholder outreach and rapid crisis response, but it also raises the stakes for fact‑checking, disclosure and edit controls.

Agencies interested in vetted, secure deployments can consider Google's enterprise path - see the new Gemini for Government OneGov offering - and make use of the Workspace guidance and prompt resources that show role‑specific workflows for communications teams.

Early state pilots demonstrate noticeable productivity and quality gains, which means communications roles will shift toward smarter prompt design, auditing AI outputs, and preserving the human voice and accountability that residents expect.

“Gemini has saved me so much time that I was spending in my workday, doing tasks that were not using my skills.” - Gemini pilot participant

Pennsylvania's approach shows the practical balance every city must strike: pilot widely, but lock in training, oversight and clear limits so automation speeds work without replacing human judgment - Governor Shapiro's Executive Order 2023‑19 built a Generative AI Governing Board and other structures to do exactly that, and the year‑long ChatGPT Enterprise pilot (175 employees across 14 agencies) returned an average time savings of 95 minutes per day, a vivid reminder that “efficiency” can become extra time for verification and service if rules are strong.

That mix - mandatory training, bans on feeding private data to models, and a rule that AI cannot make final decisions - means Philadelphia agencies can safely pilot document extraction for recertifications or AI‑assisted drafting for permits while preserving final human sign‑off.

The sensible “so what?” is that these roles shift toward verification, audit trails and better prompt design; targeted upskilling programs like Nucamp AI Essentials for Work bootcamp (15 Weeks) can prepare staff to check outputs, design prompts, and keep resident outcomes front and center as tools scale across the Commonwealth.

“You have to treat (AI) almost like it's a summer intern, right? You have to double check its work.” - Cole Gessner, Block Center for Technology and Society