How AI Is Helping Government Companies in Philadelphia Cut Costs and Improve Efficiency

Pennsylvania's bold experiments show why AI matters for Philadelphia's city halls: a year‑long pilot that gave 175 state employees across 14 agencies access to ChatGPT Enterprise cost $108,000 yet returned an average time savings of 95 minutes per day - nearly eight extra work hours a week - freeing staff to focus on higher‑value tasks like policy analysis or speeding up permit reviews (Pennsylvania AI pilot report by Technical.ly).

The commonwealth's push - backed by partnerships with Carnegie Mellon and infrastructure investments that helped land a $20B AWS build - puts Pennsylvania among the top three states for AI readiness (Pennsylvania AI readiness summary by DCED), but leaders stress training and guardrails first.

For municipal teams that want practical, workplace-focused skills, a structured pathway like Nucamp's 15‑week AI Essentials for Work syllabus and registration bootcamp can convert pilot wins into durable, responsibly governed programs.

“This pilot program showed that when used thoughtfully, generative AI can help employees save time, streamline processes, and improve services for Pennsylvanians.”

Pennsylvania has moved quickly from pilot to policy, folding lessons from a year‑long ChatGPT Enterprise trial into statewide governance that aims to make AI useful and safe for city and county teams across the commonwealth; Executive Order 2023‑19 created a Generative AI Governing Board and baked core principles like transparency, equity, adaptability, and privacy into agency practice (Pennsylvania Executive Order 2023‑19 generative AI policy).

The results so far help explain why Code for America ranks Pennsylvania among the top three states for government AI readiness - training programs, a partnership with Carnegie Mellon, and major infrastructure investments (including a $20B AWS build) give agencies the tools to pilot responsibly and scale what works (Pennsylvania top‑three AI readiness report).

Those statewide moves have nudged local governments to experiment too; reporting shows municipal and county offices are planning pilots and policies, all while sticking to human‑in‑the‑loop rules that require verification of AI outputs - because a single vivid metric from the pilot still resonates: participants saved an average of 95 minutes per day, nearly eight extra work hours a week, freeing staff for higher‑value public service (local rollout and pilot coverage of the Pennsylvania ChatGPT trial).

“Gen AI is one of the most significant technological developments of our time. It will likely lead to a new era, just as the agricultural revolution and industrial revolution did in this country over the last century or so,” Gov. Josh Shapiro said.

Philadelphia's local pilots are already stretching from sanitation to public safety, showing how focused AI tools can unclog backlogs and surface problems faster: a University of Pennsylvania–trained system that scans surveillance footage could have flagged the Tacony Creek Park dump earlier - where more than 4,000 tires accumulated into piles up to 30 feet deep and 100 feet wide - and would cost roughly $100,000 a year compared with millions spent on cleanup (see the Data & Innovation analysis "AI Can Help Clean Philadelphia Up and Give Workers a Better Deal" on illegal dumping and Tacony Creek Park: Data & Innovation analysis: AI Can Help Clean Philadelphia Up and Give Workers a Better Deal); at the same time, neighboring jurisdictions are piloting document‑processing AI to free human reviewers for higher‑value work - Pittsburgh's Housing Authority approved a $160,392 yearlong Bob.ai contract to scan recertification packets and flag completeness, aiming to cut processing time and backlog by a large margin while keeping final decisions with staff (see the PublicSource coverage of the Pittsburgh HACP AI pilot for voucher recertifications: PublicSource: Pittsburgh Housing Authority AI pilot for voucher recertifications).

These examples underscore a practical lesson for Philadelphia: start with narrowly scoped pilots that save staff time, protect workers, and pair fast wins with strict human‑in‑the‑loop rules so AI helps solve visible problems without becoming a replacement for human judgment.

“The AI will not be in charge, not making decisions.”

Philadelphia agencies can turn AI into practical, day‑to‑day tools that shave hours off routine work and surface problems before they balloon: city vehicles outfitted with sensors can map potholes and prioritize repairs, the Streets Department pilot complements that approach, and transit cameras helped SEPTA find 36,000 lane and stop obstructions over a 70‑day test so officials could target enforcement and service fixes (PhillyMag survey of Philadelphia AI pilots and local AI use cases); beyond cameras and sensors, AI chatbots and document tools have proven to cut staff time on public inquiries, FOIA workflows and routine drafting, while accessibility checks and redaction suggestions help teams scale services without sacrificing accuracy (AI Center for Government practical use cases for chatbots, FOIA, and document automation).

Start small, pick narrow problems, and pair pilots with clear safeguards and disclosure rules - the kind of readiness, governance and data‑management practices outlined in Pennsylvania's usage guidance - to capture fast wins without trading away public trust (Pennsylvania AI usage guidelines for government readiness and governance).

“AI is really helping us respond faster, work smarter, and - very significantly - serve more people.”

Policy in Pennsylvania has moved from pilot experiments to a clear governance playbook: Executive Order 2023‑19 creates a Generative AI Governing Board, requires agencies to align AI use with their missions, and embeds core principles - transparency, equity, adaptability, and privacy - along with training mandates and an emphasis on employee empowerment and public trust (Pennsylvania Executive Order 2023‑19 details and guidance); the Shapiro administration paired that framework with university partnerships and a first‑in‑the‑nation ChatGPT pilot that participants said saved an average of 105 minutes a day, showing how governance plus training can turn efficiency gains into public‑service capacity rather than automatic automation (One‑year review of Pennsylvania's generative AI Executive Order).

For Philadelphia agencies, the lesson is practical: adopt mission‑aligned, human‑in‑the‑loop rules, invest in workforce training, and use transparent procurement and oversight so AI lowers costs and speeds service without sacrificing accountability.

“We need to lean into innovation and adapt to the changing tech environment while we continue to educate ourselves about new technology. That's why last year, I signed an Executive Order to govern the use of generative artificial intelligence and take advantage of the opportunities this new technology presents to ensure our Commonwealth approaches generative AI responsibly and ethically.”

Philadelphia agencies looking to buy AI tools can take advantage of a statewide push to cut red tape and use procurement as a governance lever: the Commonwealth has pared down time‑consuming questionnaires and reorganized IT purchasing to favor smaller, agile contracts and multi‑award buys so cities can contract incrementally and invite local startups to compete (Pennsylvania streamlines IT procurement (StateScoop)); CODE PA and DGS now promote “break it into small deliverables” procurements, an Invitation to Qualify (ITQ) to pre‑qualify vendors, and a 75% reduction in procurement questions to speed buys for digital services (How Pennsylvania is modernising IT procurement (Procurement Magazine)).

Contract language can also bake in oversight - require explainability, limited trade‑secret waivers, human‑in‑the‑loop safeguards, and audit rights - to protect residents while still unlocking vendor innovation, and those reforms sit alongside major state investments (including a $20B hyperscaler campus and workforce grants) that make Pennsylvania an attractive market for AI vendors (Pennsylvania AI and investment overview (DCED)).

For Philadelphia, the practical playbook is clear: use streamlined, modular contracts to pilot narrowly scoped AI solutions, fund workforce training up front, and write procurement clauses that preserve transparency and human judgment so efficiency gains don't come at the expense of public trust.

“AI will never replace our workers. Instead, we're equipping them with the best tools to do what they do best: get stuff done for Pennsylvanians.”

Start small, learn fast, and scale only after guardrails are in place: Philadelphia agencies should pick one tightly scoped pilot (for example, a single document workflow or one service queue), pair it with a clear governance sponsor, and use the three readiness pillars Code for America highlights - Leadership & Governance, AI Capacity Building, and Technical Infrastructure - to structure the rollout (Code for America Government AI Landscape Assessment).

Invest up front in workforce training through existing partnerships - Carnegie Mellon and InnovateUS are already helping build PA's AI capacity - and lean on the Office of Administration's infrastructure and the state's ChatGPT Enterprise pilot as operational playbooks so pilots become durable programs, not one‑off experiments (Pennsylvania AI readiness analysis by City & State PA).

Run short cycles with human‑in‑the‑loop checks, measure outcomes, and scale incrementally: treat the first pilot like a one‑block test that proves the pattern before extending citywide, using metrics tied to time saved, accuracy, and public‑trust safeguards.

“This analysis demonstrates what many of us know to be true: states are leading the way when it comes to adopting AI to make government more efficient and effective.”

As Philadelphia scales pilots from cameras to chatbots, the city must squarely confront real risks: deepfakes that can impersonate people even on video calls and fuel sextortion and romance scams, widespread privacy and identity risks when facial “faceprints” are stored or breached, and racial bias that can make misidentification far more likely for Black and Asian residents - studies show error rates can be orders of magnitude higher for some groups - while AI‑powered body cameras and public surveillance raise fresh oversight and civil‑liberties questions (Philadelphia residents on AI risks and deepfakes; scholarly proposals for facial‑recognition oversight; privacy and data‑security risks of facial recognition).

Practical mitigation for Philadelphia: limit use cases to narrowly defined, high‑value problems; require human‑in‑the‑loop review and mandatory training before any operational deployment; publish transparency reports, community notices and accountability audits; run demographic bias tests and refuse systems that can't meet fairness thresholds; and adopt targeted legal safeguards - warrants or court approval for sensitive law‑enforcement uses, clear consent rules for biometric collection, and enforceable vendor audit rights - so efficiency gains don't come at the cost of trust or civil rights.

“It'll keep benefitting us the way that it does now, but if you ever let something have too much power, you never know what can happen.”

Measuring impact starts with picking the right KPIs and publishing them where residents and managers can see progress: Philly Stat 360's recent expansion adds seven public performance metrics - from SWEEP citations and BEE investigations to Open Data and Digital Inclusion - that turn operational signals into targets city teams can act on (Philly Stat 360's seven new performance metrics).

Pairing those public metrics with a balanced KPI framework - financial, operational, service and citizen measures - helps agencies set SMART targets and avoid “data for data's sake” (see practical KPI lists and guidance for governments in the industry government KPI examples and reporting guidance).

Small, visible experiments can prove value quickly: the AchieveIt case shows how targeted data analysis (waiving summer adoption fees) unclogged shelter capacity and reduced costs, a reminder that modest policy tweaks driven by KPIs can yield outsized savings and better service (AchieveIt case study and KPI guidance).

When targets are public, tied to time‑saved or backlog reductions, and monitored on a dashboard, Philadelphia can convert pilots into measurable, scalable savings while maintaining transparency and accountability.

“Sometimes, the problems that we're trying to solve … are very complex, but if you can have those very clear‑minded, simple goals, and get laser‑focused and do those things really well, that's where you see the greatest outcomes in terms of improvements to service delivery.”

Philadelphia and statewide leaders should move from pilots to a repeatable playbook: codify narrow, mission‑aligned pilots with human‑in‑the‑loop checks, require transparency and third‑party audits or certifications (HITRUST, ISO/IEC 42001, NIST frameworks are useful references), and make workforce readiness nonnegotiable - legal teams must verify AI outputs under the Pennsylvania Bar's ethics guidance, while IT and procurement adopt modular contracts and clear audit rights; practical steps include standing up a cross‑functional AI governance council, publishing simple transparency reports, and treating the first pilot like a one‑block test that proves the pattern before scaling.

Protecting privacy and compliance matters from day one: follow the data‑compliance strategies laid out for Philadelphia organizations to avoid risky data exposure and biased outcomes, and pair that with a clear accountability leader and risk‑based thresholds so pilots deliver the kinds of time‑savings the state saw in its ChatGPT trial.

Finally, invest in role‑specific training so staff can use AI safely - an accessible option is the 15‑week AI Essentials for Work pathway that teaches practical prompts, workplace use cases, and hands‑on safeguards to convert pilot wins into durable service improvements (Philadelphia data compliance guidance for AI, Pennsylvania Bar Association AI ethics opinion on AI, AI Essentials for Work syllabus and registration).

“No one should be confident they understand the future trajectory of generative AI innovation, or where the opportunities for innovation lie.”