Will AI Replace Finance Jobs in Lincoln? Here’s What to Do in 2025

As AI reshapes underwriting, claims and dealmaking across the U.S., finance teams in Lincoln, Nebraska face pressure from two forces: national adopters deploying human-in-the-loop models to speed decisions and the broader AI-driven investment cycle that's keeping information-technology spending elevated.

National insurers like Lincoln Financial are already using explainable AI to surface timely claims insights (and reported an average 91% claimant satisfaction after early pilots) - a practical sign that routine workflows will be automated while analysts focus on exceptions and client relationships (Lincoln Financial explainable AI claims expansion and pilot results).

Advisors and local banks should expect similar efficiency gains and displacement risk described in industry perspectives on the “AI Economy” (Lincoln International perspective: Entering the Age of the AI Economy); practical upskilling matters now - a 15-week, work-focused program can teach prompt-writing and tool use employers will value (Nucamp AI Essentials for Work bootcamp - practical AI skills for the workplace).

“We are focused on investing in innovations and the latest capabilities to drive the best claim outcomes for our customers... Implementing this new technology helps our claims specialists efficiently focus on the right claims at the right time - all so that we can make the best determinations for our claimants.” - Christen White, SVP, Lincoln Financial Group Protection Claims and Operations

AI is already shifting day-to-day finance work in Lincoln from manual entry to exception management: local teams are adopting accounts-payable automation that uses OCR to capture invoices, supplier portals to reduce inquiries, and ERP connectors to route approvals - tools shown to cut AP cycle times dramatically (for many teams, invoice processing drops from roughly 9.2 days to about 3.1 days) and to automate as much as 90% of routine AP tasks (Lincoln accounts payable automation solutions).

Vendors of invoice OCR report over 90% accuracy on typed invoices and faster matching to purchase orders, which combined with campus moves to centralized procure-to-pay and SAP-based accounts receivable systems at the University of Nebraska–Lincoln means fewer clerical touchpoints and cleaner audit trails (OCR invoice processing guide and best practices, UNL university-wide procure-to-pay and AR resources).

So what: Lincoln finance staff who stop retyping invoices gain time for vendor strategy, cash-flow forecasting, and handling exceptions - turning a back-office bottleneck into a strategic control point.

“Quicker approval of invoices” is recurringly cited by users as the highest benefit of an automated system, closely followed by cost.

Entry-level and highly routinized finance roles in Lincoln - think data-entry, basic reconciliation, and the classic junior-analyst grind - are most at risk, with some estimates saying up to two‑thirds of those positions could be automated and large firms already considering steep cuts in junior hiring (entry-level finance jobs at risk from AI automation, junior analysts disrupted on Wall Street by AI).

The practical “so what?” for Lincoln: headcount saved on repetitive work will be redeployed to higher-value areas - AI adoption, vendor and model governance, and exception handling - roles explicitly being posted by national insurers (for example, Lincoln Financial's Sr.

Consultant, AI Enablement & Adoption and Sr. Analyst, IT Security Risk Assessment openings signal demand for product‑owner and third‑party risk skills, with advertised pay ranges above typical entry-level salaries) (Lincoln Financial Sr. Consultant, AI Enablement & Adoption job posting).

For Lincoln finance professionals, the fastest path to job security is shifting from repetitive processing to AI oversight, governance, and client-facing analysis that machines can't credibly own.

“In its current state, AI won't eliminate entry-level Wall Street jobs, but it will reduce the number of heads required to accomplish the same task.” - Michael Ashley Schulman

Even as AI automates routine underwriting and reconciliation, humans in Lincoln still matter because machines lack accountability, context awareness, and legal standing - gaps Nebraska lawmakers and institutions are actively wrestling with.

State hearings show regulators don't have settled rules (interim studies and stalled bills illustrate the uncertainty), and the Nebraska Accountability and Disclosure Commission warned it is “not tasked with trying to judge the truth or falsity” of campaign claims and estimated it would need to hire an AI expert at roughly $140,000 to handle new responsibilities (Nebraska Examiner: lawmakers probe AI regulation).

University of Nebraska guidance makes the practical point that users - not models - are responsible for accuracy, bias mitigation, and data protection, and warns against placing sensitive or federally funded data into open tools (UNL AI resources and best practices).

National coverage also flags three systemic risks - privacy/surveillance, embedded bias, and thin oversight - that mean trained humans must steer model use, validate outputs, and defend decisions to clients and regulators (Harvard: ethical concerns as AI drives decisions).

So what: Lincoln finance teams that pair AI with clear human ownership and audit trails will avoid regulatory surprises and keep client trust when models err.

“The NADC is not tasked with trying to judge the truth or falsity of claims made in the heat of a campaign.” - David Hunter, NADC executive director

A practical 2025 upskilling roadmap for Lincoln finance professionals starts with applied Python and data-analysis classes, moves to short bootcamps for real projects, and finishes with credentialed study that employers can verify: begin with an instructor-led or on-demand Introduction to Python to master cleaning and automating spreadsheets (Business Computer Skills Python Level 1 course in Lincoln, NE), then take a focused Data Analysis Using Python course or a five-day intensive boot camp to build a portfolio reconciliation or cash-flow automation project (The Academy Introduction to Programming Using Python boot camp in Lincoln offers immersive, job-focused sessions), and layer in formal credentials or credit-bearing coursework - UNL's Software Development minor accepts 15 credit hours and maps directly to employer expectations.

Timeline: 1–3 months for intro courses, another 1–2 months for applied data analysis or a boot camp, then ongoing certification or academic credits; so what: finishing a Level 3 data-analysis module produces a concrete script or dashboard to demonstrate immediate ROI to hiring managers and local banks.

Lincoln employers can restructure hiring in 2025 by shifting headcount away from repetitive processing and toward oversight, product‑ownership, and client-facing advisory: rewrite job descriptions to require AI literacy, prompt-writing, and vendor/model governance; shorten time-to-value for new hires with rotation programs that move juniors into reviewer and exception-management roles within a few years (mirroring PwC's retooled junior training for the AI era) - and embed partnerships with local training providers to supply ready-to-work talent skilled in the exact tools used on day one (PwC retools junior training for the AI era, partner with local bootcamps and tool-focused programs).

So what: advertising fewer pure-data-entry roles and creating 12–18 month “AI reviewer” career ladders lets firms keep institutional knowledge while making saved capacity available for advisory work and governance.

“If accountants and firms do not continue to adopt new technology, the failure to stay current or on the cutting-edge could actually prevent them from achieving their growth goals.” - Jamerlyn Brown, principal communications manager at Intuit

Local finance teams can test AI with three low-risk pilots that produce tangible ROI: (1) an accounts‑payable OCR pilot with a single vendor class to validate accuracy and downstream exception rates (use vendor automation playbooks from industry coverage to design baseline metrics) - ideal to free staff for vendor strategy and exception handling (accounts-payable AI OCR pilot for faster financial close); (2) an FP&A forecasting pilot that pulls sales and marketing signals into an AI model to deliver weekly, scenario‑ready forecasts so leaders can act faster (run the model alongside current forecasts for one quarter to measure error reduction and decision speed, following guidance from modern forecasting sessions) (AI forecasting and predictive analytics for smarter financial planning); and (3) a behaviorally informed intervention pilot modeled on the University of Nebraska–Lincoln's “Messages from a Future You” research - collect a few hundred anonymized local employee or small‑business customer trajectories, cluster them, and deliver tailored nudges for on‑time payments, training completion, or cash‑flow behaviors to test lift in the real world (UNL AI-based intervention pilot that trained interventions on ~300 students).

Run each as a time‑boxed experiment, predefine success metrics (cycle time, forecast error, on‑time rate), and require human‑in‑the‑loop signoff so wins translate into durable process change.

“The existing approaches mainly target academic improvement based on just academic performance alone.” - Mohammad Hasan

Target career paths in Lincoln should balance finance fundamentals with AI oversight: pursue FP&A (Analyst → Senior → Manager → Director) to build forecasting and business‑partnering skills, while adding a parallel track in AI governance/product‑ownership and model risk so local employers trust human review of automated outputs; practical proof points matter, so bring a small portfolio (a Level‑3 data‑analysis script or dashboard) and show cross‑functional wins.

Local openings illustrate demand - Lincoln Financial's Corporate FP&A posting lists Omaha as an alternate location and a $69,000–$124,600 pay range, underscoring that mid‑level FP&A plus hybrid flexibility is marketable (Lincoln Financial Corporate FP&A job posting).

Use the FP&A career framework to plan promotions and certifications - expect 1–3 years to reach analyst level and 3–5 to senior roles - and network deliberately: build internal relationships (many FP&A hires come from promotions), join local bootcamp cohorts that run employer‑project work, and attend UNL or industry meetups to convert familiarity into interviews (FP&A salary and career path guide).

So what: candidates who pair a measurable analytics portfolio with governance fluency will win higher‑paying, hybrid roles in 2025 Lincoln.

Quick actions for Lincoln finance pros: master prompt engineering now - practice clear, repeatable prompts for board reporting, variance analysis, and scenario planning (see a finance-focused Prompt Engineering for Finance: Guide for Finance Teams); pair that with applied Python skills to automate reconciliations and generate reusable scripts (start with a practical primer like Python Basics for Finance Professionals - book); enroll in a short, instructor-led Python for finance class to build a one-page portfolio script (see compact Training The Street Python for Finance offerings); run a 4–8 week, human-in-the-loop pilot (AP OCR or forecast‑model review) with predefined success metrics; update job descriptions and resumes to list “prompt engineering,” “AI oversight,” and “Python automation” as core skills; and join local bootcamp cohorts or UNL meetups to convert projects into interview evidence - so what: with near-universal AI pilots expected across U.S. finance teams within a few years, these steps turn displacement risk into a fast path to higher‑value, audit-ready roles.

The short answer for Lincoln in 2025: jobs won't vanish so much as repivot - private-market resilience (the Lincoln Private Market Index rose 2.5% in Q2 2025) and active insurer pilots show continued demand for skilled finance work, but that work will skew to oversight, exception handling, and client‑facing analysis rather than repetitive entry; national examples of explainable, human‑in‑the‑loop AI that produced a 91% claimant satisfaction rate at Lincoln Financial make the path clear: pair AI with human accountability and governance to keep local roles relevant (Lincoln Private Market Index (Q2 2025) report, Lincoln Financial explainable AI claims expansion press release).

Practical next steps: move quickly from automation experiments to formal reviewer and model‑risk lanes and close skill gaps with short, applied programs like Nucamp AI Essentials for Work - 15-week applied bootcamp so saved headcount converts to higher‑value advisory and governance roles.

“We are focused on investing in innovations and the latest capabilities to drive the best claim outcomes for our customers... Implementing this new technology helps our claims specialists efficiently focus on the right claims at the right time - all so that we can make the best determinations for our claimants.” - Christen White, SVP, Lincoln Financial Group Protection Claims and Operations