The Complete Guide to Using AI in the Financial Services Industry in Columbus in 2025

Columbus sits at the intersection of Midwest finance and rising AI capability, making 2025 a pivotal year for banks, credit unions, and fintechs that need practical strategies for customer trust and compliance; local initiatives like the Fisher College's Fisher College AI in Business Conference and the statewide Ohio AI Summit for Ohio AI leaders foreground Human-in-the-Loop design, governance, and workforce change while national studies - such as the Bread Financial report on AI and financial services - show 52% of consumers already use AI tools but 65% still want human intervention, underscoring why Columbus firms must pair automation with explainability and human oversight; practical upskilling matters too - Nucamp AI Essentials for Work registration (15 weeks, early-bird $3,582) teaches prompt-writing and workplace AI skills to help teams move from pilots to reliable, compliant deployment.

"Younger generations are increasingly leveraging AI tools for financial decisions, particularly in areas like budgeting and fraud detection, as shown in our findings," said Jessica Calaway, Senior Manager, Thought Leadership & Consumer Insights at Bread Financial.

AI in financial services is the set of algorithms and models that automate detection, scoring, and personalization; Human-in-the-Loop (HITL) AI layers structured human oversight on top of those models so decisions remain explainable, auditable, and context-aware - critical for Columbus firms balancing automation with customer trust and regulatory scrutiny.

HITL intentionally routes edge cases, fairness checks, and high‑value judgments to trained staff so models augment expertise rather than replace it, reducing costly false positives in fraud workflows and protecting reputations.

Local resources make HITL practical: the Fisher College's inaugural Fisher College AI in Business Conference on HITL design and governance centers HITL design, governance, and interdisciplinary dialogue, while Fisher Executive Education (Fisher Executive Education AI programs and AI Prompt Engineering short courses) offers short, actionable courses - most notably a two‑day

AI Prompt Engineering

module - that let frontline teams learn prompt structure and oversight patterns in days, not months, so pilots move to reliable, auditable operations faster.

Ohio's 2025 AI industry outlook centers on a rapid build‑out of local cloud and generative‑AI capacity that makes Columbus a realistic production environment for banks, credit unions, and fintechs: Amazon Web Services' planned $10 billion expansion in Ohio - including a first Fayette County site estimated at $5 billion and the potential for up to eight new sites by 2030 - adds on‑shore compute and data‑center capacity specifically designed to run AI/ML and foundation models, while creating hundreds of AWS roles and supporting thousands of supply‑chain jobs (see the Columbus Chamber summary); at the same time, AWS's financial‑services and generative‑AI offerings (Amazon Nova, Bedrock, managed models and agents) give institutions turnkey paths from pilot to production.

The practical “so what?” is simple: more local compute and vendor services reduce latency, help keep sensitive data in‑state for governance and compliance, and make real‑time use cases - faster fraud detection, low‑latency portfolio analytics, and interactive customer assistants - operationally and economically feasible for Columbus firms that pair HITL controls with scalable cloud platforms.

Watch three linked trends this year: hyperscale data‑center expansion, managed generative‑AI platforms, and workforce investments that turn pilots into auditable, compliant services.

“As reliance on digital services continues to grow, so does the importance of data centers; they are critical to today's modern economy.” - Ohio Governor Mike DeWine

The near‑term future of AI in Columbus finance blends agentic, production‑grade models with Human‑in‑the‑Loop (HITL) governance: industry analyses forecast agentic AI that autonomously handles complex tasks - fraud triage, continuous compliance monitoring, and end‑to‑end accounting workflows - while local academic and policy activity is building the oversight and talent pipelines Columbus needs to deploy those agents responsibly; see Valere's roadmap for “Agentic AI” in finance and accounting for clear use cases and implementation priorities (Valere Labs: Agentic AI use cases and implementation priorities for finance and accounting).

Practical signals matter: Fisher College's inaugural HITL‑focused Fisher College AI in Business Conference (HITL focus) and statewide convenings are pushing explainability, governance, and workforce reskilling as prerequisites for scaling pilots to production.

The so‑what: with Ohio institutions embedding AI fluency into curricula and hosting governance‑centered forums, Columbus firms can adopt autonomous finance agents to cut manual reconciliation and detect fraud in near‑real time - provided they pair models with HITL checks and robust data architecture to keep audits and regulators satisfied.

"Artificial intelligence is transforming the way we live, work, teach and learn. In the not-so-distant future, every job, in every industry, is going to be impacted in some way by AI. Ohio State has an opportunity and responsibility to prepare students to not just keep up, but lead in this workforce of the future."

Columbus financial firms are already applying AI across the same practical fronts seen nationally - real‑time fraud detection, automated credit scoring and underwriting, 24/7 chatbot support, document OCR and KYC automation, and personalized budgeting and robo‑advice - turning pilots into production where low latency and local cloud capacity matter; national surveys show 52% of consumers already use AI tools and 7 in 10 expect AI to play a large role in finance, yet 65% still want human intervention, so local teams must combine automation with Human‑in‑the‑Loop controls to preserve trust and compliance (see the Bread Financial consumer AI use and trust study and RTS Labs' catalog of banking use cases).

The practical payoff is measurable: firms can cut fraud‑review cycles dramatically (industry reports cite drops from roughly 90 minutes of manual work to under 30 minutes with generative AI), scale always‑on support, and speed loan decisions - but only if models are governed, explainable, and routed to humans for edge cases and fairness checks, a requirement emphasized by regional HITL training and governance programs in Columbus.

"Younger generations are increasingly leveraging AI tools for financial decisions, particularly in areas like budgeting and fraud detection, as shown in our findings," said Jessica Calaway, Senior Manager, Thought Leadership & Consumer Insights at Bread Financial.

Columbus and greater Ohio are now focal points for hyperscale AI infrastructure investments that directly affect financial services: Amazon Web Services announced an additional $10 billion to expand data centers across the state (including a Fayette County site estimated at $5 billion and the potential for up to eight new sites by 2030), a commitment that brings on‑shore, AI‑ready compute and promises “hundreds of new, well‑paying jobs” and stronger local cloud capacity for low‑latency fraud detection and analytics (AWS $10B investment plan in Greater Ohio - Governor DeWine announcement); alongside AWS, large projects from Cologix (a reported $7 billion AI campus in Johnstown), Microsoft (about $1 billion across new Ohio campuses), and Google (roughly $2.3 billion in expansions) are reshaping Central Ohio into an AI infrastructure hub that makes production deployments - not just pilots - economically viable for banks, credit unions, and fintechs seeking compliant, low‑latency services (Central Ohio emerging as a leading data-center hub - data center investment summary).

The practical takeaway: these coordinated investments mean local firms can access hyperscale compute, reduced latency, and a growing talent pipeline without moving sensitive workloads out of state, accelerating secure HITL deployments for real‑time financial use cases.

“As reliance on digital services continues to grow, so does the importance of data centers; they are critical to today's modern economy.” - Governor Mike DeWine

Columbus financial firms must treat AI like any other regulated business tool: regulators expect existing supervision, recordkeeping, data‑privacy, and communications rules to govern AI use, so firms should embed AI into Written Supervisory Procedures, document model lineage, and tighten third‑party vendor oversight to avoid “AI washing” or misleading marketing claims - guidance summarized in Smarsh's review of what FINRA and the SEC expect (Smarsh review of FINRA and SEC AI governance expectations); federal reporting also shows regulators are applying existing frameworks to AI oversight and urging stronger model‑risk and third‑party controls (GAO report on AI use and oversight in financial services).

Practical steps for Columbus teams include inventorying all models (internal and vendor), prioritizing explainability for high‑impact use cases (credit, trading, fraud), routing edge cases to Human‑in‑the‑Loop reviewers, and automating documentation and monitoring so audits and exam responses are faster and defensible - the “so what” being concrete: an auditable AI inventory plus WSP alignment converts regulatory attention into a repeatable compliance process rather than ad‑hoc risk.

“You need to know what's happening with the information that you feed into that tool.” - Andrew Mount, Counsel, Eversheds Sutherland

Columbus firms can close the AI skills gap by combining short, focused executive courses with campus talent and industry convenings: The Fisher College's HITL‑focused Fisher College AI in Business Conference Oct 2–3, 2025 and Fisher Executive Education's suite of Fisher Executive Education AI programs including AI Prompt Engineering and Leading Change in the Age of AI (notably a two‑day “AI Prompt Engineering” module and online “Leading Change in the Age of AI”) give frontline managers practical prompt, oversight, and change‑management skills while Connections 2025's workforce sessions in May highlight industry–education hiring pipelines and skills‑based credentials for Columbus employers (Connections 2025: AI and the Workforce Evolution workforce sessions summary).

Pairing those short courses with Ohio State's deep student pipeline (Fisher serves over 10,000 business students) and local networking events creates an actionable pathway: train a cross‑functional HITL review squad with a 48‑hour prompt‑engineering sprint, then rotate them through conference roundtables to align governance, hiring, and vendor oversight - so what: that compact, repeatable loop turns ambiguous “AI readiness” into measurable capacity for model review, explainability checks, and redeployment across fraud, underwriting, and customer‑facing workflows.

Move from experiment to repeatable service by treating pilots like mini‑programs: pick one high‑value, low‑blast‑radius workflow (fraud triage or KYC), define clear KPIs (false‑positive reduction, time‑to‑decision, audit readiness), and run a short Human‑in‑the‑Loop pilot that pairs an automated agent with a trained review squad - seed that squad with a 48‑hour prompt‑engineering sprint to codify review rules and escalation paths.

Use production‑ready cloud building blocks (Amazon Bedrock, SageMaker, agent orchestration) and embed responsible‑AI guardrails and model lineage from day one so vendor services scale without creating compliance gaps (see PwC's guidance on building industry‑ready AI on AWS).

Measure early outcomes: PwC's May 2025 survey finds 66% of adopters report measurable productivity and 88% of executives plan bigger AI budgets, signals that concrete gains unlock funding to scale.

When KPIs are met, automate monitoring, version controls, and vendor oversight, then orchestrate agents across adjacent workflows to compound value while keeping humans in the loop for edge cases and audits.

“We're proud to be AWS's launch partner - bringing mathematically validated safeguards into real-world AI use cases across sectors like pharma, utilities, and cloud compliance.” - Matt Wood, CTIO PwC

Columbus financial leaders should treat 2025 as a sprint: register teams for Fisher College's HITL convening to align governance and vendor oversight, run a focused 48‑hour prompt‑engineering sprint to seed a cross‑functional Human‑in‑the‑Loop review squad, and pair that squad's playbook with a narrow production pilot (fraud triage or KYC) on a local hyperscale cloud node to keep sensitive workloads in‑state - this sequence turns abstract AI plans into auditable services while reducing latency and exam risk; practical next steps are clear: secure seats at the Fisher AI in Business Conference (Fisher AI in Business Conference - Fisher College of Business), enroll frontline staff in a workplace AI course such as Nucamp AI Essentials for Work (15‑week workplace AI course) to build prompt and oversight skills, and prioritize one measurable KPI (false‑positive rate or time‑to‑decision) for the pilot so leadership can fund rapid scale when results appear - one specific payoff: a trained HITL squad plus local cloud capacity converts pilot wins into compliant, low‑latency services that regulators and customers can trust.

"Younger generations are increasingly leveraging AI tools for financial decisions, particularly in areas like budgeting and fraud detection, as shown in our findings," said Jessica Calaway, Senior Manager, Thought Leadership & Consumer Insights at Bread Financial.