The Complete Guide to Using AI as a Finance Professional in Orem in 2025

Orem finance professionals should pay attention to AI in 2025 because Utah Valley University has established an Applied Artificial Intelligence Institute and launched a practical Master's in Applied AI to live on the Orem campus - programs explicitly built to help local businesses adopt AI for data-driven decision making, ethical governance, and real-world projects like a hands-on capstone; see UVU's announcement for details UVU Applied AI Institute announcement.

For finance teams that want fast, usable skills (prompting, tooling, workplace workflows), Nucamp's 15-week AI Essentials for Work bootcamp offers targeted, job-ready training AI Essentials for Work syllabus and course details.

The practical payoff: routine spreadsheet tasks and forecasting workflows can move from weeks to minutes, freeing time for analysis and oversight rather than manual data wrangling.

“The Applied AI Institute is a significant step forward in our vision for education at UVU. We believe that everyone, regardless of their major, should engage with this transformative technology and become comfortable with it. By integrating hands-on learning experiences into our curriculum, we are empowering our students to thrive in the rapidly evolving world of work.”

For Orem finance professionals, the near-term future of AI in financial services means practical, workflow-first change rather than sci‑fi reinvention: record private investment and rapid business uptake - Stanford HAI's 2025 AI Index notes U.S. private AI investment at $109.1 billion, generative AI drawing $33.9 billion, and 78% of organizations using AI - are driving tools that speed forecasting, automate document-heavy work, and surface risk faster than traditional systems; see the Stanford HAI 2025 AI Index report Stanford HAI 2025 AI Index report.

Industry research shows three strategic priorities - operational efficiency, risk management and customer experience - that map directly onto typical Orem use cases such as faster loan file review, anomaly detection, and personalized cash‑flow advice (nCino and EY detail these trends and practical benefits) EY insights on how AI is reshaping financial services.

Two caveats matter locally: regulation is accelerating (59 U.S. agency actions in 2024) and models still struggle with complex, high‑stakes reasoning, so governance and human oversight are non‑negotiable.

One vivid reality: inference costs for GPT‑3.5‑level systems dropped over 280‑fold between late 2022 and late 2024, making capable AI tools suddenly affordable for mid‑sized finance teams looking for fast ROI and real productivity gains.

“This year it's all about the customer. We're on the precipice of an entirely new technology foundation, where the best of the best is available to any business.” - Kate Claassen, Morgan Stanley

Orem finance teams can start with practical, low-risk AI projects today - think automated invoice capture and approval, smarter transaction categorization, expense-policy enforcement, and reconciliation intelligence that trims busywork and surfaces anomalies sooner - tactical moves that mirror the national experience where 59% of accountants now use AI tools and teams report saving about 30 hours per week, roughly one full-time role's worth of effort (see CFO Selections for the study data).

These automations unlock faster FP&A cycles and live dashboards so controllers spend less time fixing spreadsheets and more time advising leadership on cash and capital decisions; CPA.com's Road to AI Implementation and GenAI toolkits are good first stops for stepwise, risk-aware adoption.

Start small with AP/expense automation or a reconciliation pilot, pair the tool with clear human review and audit trails (per Deloitte's governance guidance), and tap local upskilling via Orem training partnerships to build staff confidence - successful pilots often deliver measurable time savings within a single month, making the “so what?” unmistakable for busy finance shops.

“AI will make you a superhuman, you will become even more valuable to clients. The only problem is if you don't evolve yourself and use it.”

For most Orem finance teams the best AI-ready path is to pick an ERP that already excels at financials and integrations - NetSuite is a strong fit for small and mid-sized companies that need comprehensive accounting, billing and revenue modules with broad third‑party connectivity, while Workday is better suited to large, global organizations that prioritize human capital management and enterprise financial planning; see a detailed comparison of Workday vs NetSuite for these tradeoffs Workday vs NetSuite: an in-depth comparison.

Equally important: choose a platform that will actually benefit from embedded AI features, because AI‑enriched ERP systems are designed to optimize operating models, automate routine workflows and surface insights across finance and operations - exactly the kind of capability local teams need to turn a shoebox of receipts and ad‑hoc spreadsheets into a searchable, auditable dashboard without reinventing the stack; read more on AI in ERP trends and how these systems assist governance and process optimization AI in Enterprise Resource Planning: trends & insights.

In short: for growing Orem businesses NetSuite's breadth and customizable financial tooling usually wins; for large employers with complex workforce and planning needs Workday often makes more sense - pick the vendor whose integrations, pricing model and AI roadmap match your team's size, skills and near‑term use cases.

Get practical fast: treat an AI-enabled finance project in Orem like a sequence of small, measurable sprints - lay the technical foundation (a cloud ERP or clean data pipeline), pick a high‑impact pilot (invoice capture, reconciliation, or time‑series forecasting), and lock in governance and human review before scaling; local roadmaps and checklists can be borrowed from implementation guides like the GrowCFO implementation roadmap to structure pilots, KPIs, and RPA handoffs GrowCFO implementation roadmap.

For hiring and training, tap Utah Valley University's applied AI programs and apprenticeships as a nearby talent and partnership source, then formalize sponsorship, champions, and leadership buy‑in so the effort survives busy season UVU applied AI pathways and apprenticeships.

If the project includes an educational or workforce pipeline element, consider Utah's Innovation in Artificial Intelligence Grant Pilot Program (awards up to $1,000,000) but note application expectations - describe your Utah presence, partnerships with schools, compliance with federal/state AI policies and Utah cybersecurity/data privacy rules, and clear success metrics before you apply Utah Innovation in Artificial Intelligence Grant Pilot Program details.

The “so what?” is simple: start with a pilot that turns a shoebox of receipts into a searchable, auditable dashboard and use measured wins to expand responsibly across the finance stack.

“The Applied AI Institute is a significant step forward in our vision for education at UVU. We believe that everyone, regardless of their major, should engage with this transformative technology and become comfortable with it.”

For Orem finance teams the first real job isn't choosing an LLM, it's preparing trustworthy data: think of Dawgen's line that “data is the currency of AI” and treat accuracy, completeness, consistency, timeliness and relevance as non‑negotiable foundations for any pilot; practical steps include a fast data audit, standardizing definitions, cataloging lineage, and assigning clear ownership so month‑end numbers don't change meaning as they cross systems.

Use automated profiling and observability to catch missing or duplicate records early (and to give auditors an end‑to‑end trail), lean on fit‑for‑purpose datasets for your first AP or cash‑forecasting pilot, and bake in role‑based access, masking and monitoring to meet the growing regulatory scrutiny Crowe highlights - governance must accompany every deployment, not follow it.

For hands‑on guidance on cleaning and governing finance data, see Cube Software's primer on AI data quality and Crowe's practical AI governance guidance for financial services; both resources emphasize that explainability, continuous monitoring and clear accountability turn raw outputs into decisions leaders can trust.

“You can't be artificially intelligent if you're dumb with data.”

Building an AI-ready finance team in Orem starts with local talent and practical partnerships: lean on Utah Valley University's Applied AI pathways - from a master's to a paid applied AI apprenticeship that lets students earn college credit while they learn - as a steady hiring and internship pipeline, tap state-wide initiatives and the NVIDIA partnership that brings GPU‑accelerated resources and faculty certification to boost hands‑on training, and send controllers or analysts to short, skills‑first courses like the University of Utah's 5‑week AI Prompting certificate to get prompt engineering into day‑to‑day workflows; combining apprentices, upskilled staff, and targeted bootcamps creates a repeatable funnel for candidates who can translate models into cash‑flow forecasts and clean audits, and it makes the “so what?” tangible - newly trained hires who can automate a month of close work down to a few hours.

For hiring, prioritize project experience, evidence of responsible‑AI thinking, and programs that include real internships so new staff arrive with production‑grade habits.

“AI will continue to grow in importance, affecting every sector of Utah's economy.”

Quick wins for Orem finance teams are mostly practical, low‑risk projects that pay off fast: start with accounts‑payable automation to capture invoices, auto‑match POs and route approvals (modern pilots can cut invoice processing time by up to 80% and move work from weeks to days), follow a staged plan like the 60‑day AP Automation Challenge to scope, pilot and roll‑out, and you'll free dozens of hours a month for analysis rather than data entry; see a step‑by‑step rollout at Ascend's 60‑day guide Ascend 60-day AP automation challenge: how to go from chaos to control.

Nonprofits and grant‑centric orgs in Orem get immediate wins from donor, grant and allocation automation - Sage Intacct highlights automated bill entry, single‑line allocations and donor workflows that boost stewardship and audit readiness Sage Intacct guide to nonprofit financial automation quick wins.

Pair automation with AP best practices (centralized intake, vendor personas, shadow reporting) to reduce errors and lower per‑invoice costs (modern stacks can approach <$3 per invoice) - practical guidance and benchmarks are available from Corpay and industry AP guides Corpay AP automation best practices and benchmarks.

The “so what?”: a month of close work can shrink to a few days, turning a shoebox of invoices into an auditable, searchable cash‑flow dashboard that leaders can act on.

Measuring AI success in Orem finance projects means choosing a handful of practical KPIs - drawn from frameworks like the 34‑metric catalog of model, data and business indicators - to prove impact quickly and avoid common pitfalls such as poor data quality or mismatched targets; see the Multimodal guide "34 AI KPIs to Use in Business" 34 AI KPIs to Use in Business (Multimodal).

Start with three linked measures: model effectiveness (accuracy, precision/recall, F1), operational gains (time saved, throughput, error‑rate reduction) and business outcomes (cost savings, ROI, revenue impact); Corporate Finance Institute's finance‑focused KPI guide shows how fraud detection projects delivered concrete results - fraud losses fell ~60%, false positives dropped ~80% and the bank saw a ~5× ROI in year one - illustrating the kinds of targets Orem teams can benchmark against in "AI KPIs: How to Track and Measure AI Performance" AI KPIs: How to Track and Measure AI Performance (Corporate Finance Institute).

Guardrails matter: align KPIs with strategic goals, track data quality (completeness, timeliness, bias), and build dashboards and alerting so leaders see when models drift; organizations that use AI to reengineer KPIs are more likely to capture financial benefit, per MIT Sloan's research "The Future of Strategic Measurement" The Future of Strategic Measurement (MIT Sloan), so measure early, iterate quickly, and report both leading and lagging indicators to justify the next pilot or scale‑up.

“50% to 60% of the time, when we lost a sale, it was because the customer bought something else in the same product category.”

Orem finance teams closing out 2025 should treat governance and practical wins as two sides of the same coin: attend the Utah Data Governance Summit at UVU - event details and agenda to hear state leaders and privacy experts lay out the rules and tools that will keep local pilots auditable and compliant (Utah Data Governance Summit at UVU - event details and agenda), plan pilots that buy proven vendor solutions rather than reinventing the wheel - a recent MIT analysis found roughly 95% of generative-AI pilots stall when organizations try to go it alone, so prioritize integrations and line‑owner adoption (MIT analysis on generative-AI pilot failure rates (Fortune coverage)) - and invest in people who can run responsible pilots; short, focused training like Nucamp's 15‑week AI Essentials for Work turns day‑one curiosity into prompt‑driven productivity and practical workflows that cut manual close work into hours, not days (Nucamp AI Essentials for Work - 15‑week workplace AI syllabus & registration).

Start by locking in one measurable pilot (AP capture, reconciliation, or cash forecasting), document data lineage and review gates from day one, and use local forums and trainings to build the trusted, auditable systems Utah regulators and auditors will expect - so the next step is clear: learn the rules, choose the right partner, and train the team to turn models into repeatable business value.