Will AI Replace Customer Service Jobs in Orem? Here’s What to Do in 2025

Orem's customer-service workforce is already feeling the ripple effects of a statewide surge in AI adoption: Utah ranks high for AI job postings and policy activity, and experts warn the pace is fast enough to reshape entry-level work in the near term.

A stark alert from industry leaders - highlighted in a KSLTV report on AI reshaping entry-level jobs that quotes Anthropic CEO Dario Amodei on the possibility that AI could replace up to half of entry-level roles - contrasts with local data showing Utah employers actively seeking AI skills (KSLTV report on AI reshaping entry-level jobs: KSLTV report on AI reshaping entry-level jobs, KSL NewsRadio coverage of Utah AI job postings: KSL NewsRadio coverage of Utah AI job postings).

That mix - rapid automation risk plus strong hiring for AI-capable roles - makes targeted reskilling a practical next step for Orem reps, and local bootcamps like Nucamp's AI Essentials for Work are already designed to teach usable AI tools and prompt-writing skills in a work-focused 15-week format.

Learn more about the AI Essentials for Work bootcamp: AI Essentials for Work bootcamp - 15-week practical AI skills for the workplace.

“Most jobs that are going to involve AI are going to be augmented by AI rather than replaced by AI,” said Utah's Office for AI Policy director Zachary Boyd.

AI is rewiring the national labor market at a pace that matters for Orem: the World Economic Forum's 2025 findings forecast that AI and automation will reshape roughly 86% of businesses by 2030, creating about 170 million new roles while displacing 92 million, and leaving nearly 39% of today's skill sets outdated - a speed that makes short, practical reskilling urgent for frontline workers (WEF report: How AI Will Reshape 86% of Businesses by 2030 - World Economic Forum summary).

The mechanics matter: industries with rich, structured customer-data - like customer support - can see AI adoption rates near 60–70%, with vendors already using call, email and ticket logs to cut handling costs (IBM cites a 23.5% reduction), so a single 500-person call center could plausibly re-emerge as 50 AI-oversight specialists plus a leaner frontline team.

For Orem reps that means local employers will favor people who can pair human judgment with tools; practical, role-focused training and tool-lists (see Nucamp AI Essentials for Work syllabus: AI Essentials for Work syllabus - Nucamp) are the fastest way to stay competitive, because the time window to pivot is shorter than many expect.

“As we enter 2025, the landscape of work continues to evolve at a rapid pace. Transformational breakthroughs, particularly in Gen AI, are reshaping industries and tasks across all sectors.” - Saadia Zahidi

Customer-service roles in Orem are especially exposed in the near term because the tasks employers most want to automate - routine FAQs, account updates, ticket logging and simple troubleshooting - make up a large share of local front-line work, and both global trend reports and sector analyses point to fast adoption: the World Economic Forum notes that 40% of employers expect to reduce staff where AI can automate tasks (World Economic Forum Future of Jobs reporting), while call-center specialists show conversational AI, real‑time transcription and automated post-call work replacing high-volume chores (How AI Will Transform Call Center Agent Roles).

That combination - high local AI hiring activity, powerful off‑the‑shelf chatbots, and the structural nature of customer‑service work - means employers can cut costs quickly, shrinking entry‑level headcount and turning many junior shifts into a few specialist oversight jobs; the result risks closing the traditional ladder into mid-career roles unless Orem workers retool fast.

AI could eliminate half of entry-level white-collar jobs within the next five years.

For Orem customer‑service teams, AI will most reliably take over high‑volume, rules‑based work - think automated FAQ replies, smart ticket triage and routing, email drafting, call transcription and post‑call summaries, and knowledge‑base optimization - tasks that vendors now deploy to cut handling time and deflect routine volume (see Nextiva's roundup of AI in customer service for concrete examples: Nextiva examples of AI in customer service: chatbots, triage, and agent assist).

Tools that classify intent and surface context can shave meaningful seconds off each interaction - Zendesk reports intelligent triage and in‑context intelligence can save about 45 seconds per issue - so a busy Orem helpdesk might see rush‑hour queues slim down as bots filter the easy stuff (Zendesk report on intelligent triage and smart assist).

What AI can't do well for local reps is the human work: empathy, complex judgement, relationship building, handling edge cases or compliance‑sensitive health and financial disputes - areas where a person's nuance matters - and industry guides stress designing AI to augment, not replace, agents (Kustomer's guide on balancing AI and human support helps explain why: Kustomer guide to AI-assisted human support).

The practical takeaway for Orem: automate the repetitive backbone to free humans for the high‑stakes, emotional, and strategic moments - picture a bot answering a midnight “where's my order?” so a trained rep can take the next call that needs a steady voice.

Orem's local mix - retail stores, hotels and restaurants, health clinics, and a growing tech and education scene - already shows how differently AI lands in each sector: retail is moving fast toward hyper‑personalization, real‑time inventory and AI chat support that can handle routine returns or upsells, while hospitality and leisure face pressure to use dynamic pricing and automated guest‑assistants as travelers hunt cheaper options; healthcare sees NLP and documentation automation that trim clinician paperwork but raise disclosure and compliance questions under Utah's updated AI rules.

On the tech side, Orem businesses and learning centers are adopting practical tooling - think smart scheduling and integrated booking systems that reclaim hours of admin time and reduce no‑shows - so local customer‑service reps who learn to operate and oversee these systems gain value.

The takeaway: in Orem a bot that answers routine midnight “where's my order?” queries can free a trained human to resolve the next high‑stakes call, but employers and reps must navigate both operational change and Utah's disclosure rules to keep trust intact.

Upskilling in Orem should start local and practical: take foundational digital classes (like United Way of Utah County's free, hands‑on 10‑week computer course that even awards a free desktop after completion) to lock down email, calendars and job-search basics, then layer role-focused training - short, applied courses and tool lists that teach prompt-writing, ticket‑triage workflows and the “top AI tools” used in customer support - so reps move from being replaced to being indispensable as AI supervisors; state programs are supporting that shift too, with the Utah DTS AI program promoting workforce training, data governance and safe AI adoption for public and private sectors.

Combine community classes, employer-supported on-the-job AI coaching, and targeted bootcamps or guides (see Nucamp AI Essentials for Work practical AI guides and syllabus) to build a stackable, resume-ready skillset - this mix of basic digital literacy, scenario-based generative‑AI practice, and system-oversight know‑how is the fastest route to keep a steady paycheck and a clearer career ladder in Orem.

“As issues can vary from customer to customer, customer service reps will need to remain agile when assisting customers. By using generative AI to train unique scenarios that could occur in real situations, reps will be more adept at handling whatever customer issue comes their way.”

Orem's job map is already shifting from routine front‑line roles toward a cluster of AI‑adjacent positions that local employers are actively recruiting for: applied AI engineers, machine‑learning and NLP specialists, data scientists and AI product managers all top the list of emerging openings, while cloud, cybersecurity and IT support keep underlying systems secure and scalable (see Utah Job Market 2025: Employment Trends and In‑Demand Skills: Utah Job Market 2025: Employment Trends and In‑Demand Skills).

Higher‑education pathways and paid apprenticeships are responding - Utah Valley University now highlights applied AI degrees, certificates and an applied‑AI apprenticeship that literally pays students to learn while earning college credit, a practical bridge into these new careers (UVU applied AI programs and apprenticeship).

Employers across the state are posting more roles that require AI know‑how (Utah ranked among the top states for AI job postings), so Orem reps who stack prompt‑writing, data literacy and soft skills can pivot into oversight, analytics or product roles that often come with six‑figure pay potential and stronger long‑term demand (KSL NewsRadio: Utah AI job postings and trends), turning a local cost‑cutting pivot into a real opportunity to move up the ladder - and into work that centers design, judgment and ethics rather than repetitive tasks.

“Most jobs that are going to involve AI are going to be augmented by AI rather than replaced by AI,” said Utah's Office for AI Policy director Zachary Boyd.

Six months is the practical window for Orem customer‑service reps to move from anxious to actionable: start with a role‑specific 30‑60‑90 roadmap that uses AI to diagnose skill gaps, set clear milestones and deliver adaptive practice (see Disco guide to 30‑60‑90 upskilling plans with AI for step‑by‑step structure and milestone ideas: Disco guide to creating 30‑60‑90 upskilling plans with AI); month two to four, rotate through jobs - ticket triage, escalation handling and quality review - so reps gain hands‑on exposure to the tasks AI will touch and managers can spot transferable strengths (use SHRM job‑rotation playbook to design safe, company‑sponsored rotations that preserve service continuity: SHRM guide: how to implement a job rotation program); and months four to six, lock in targeted learning channels and manager dashboards - follow Utah's DTS model of curated training and manager “channels” (Pluralsight Skills/Flow) to close gaps and redeploy people into oversight roles where judgment matters (Utah upskilling program case study: Utah combats employee turnover with IT upskilling).

Build quick wins (one new AI prompt library, one rotation slot, one manager checkpoint per month) so progress is visible - picture a rep who spends two weeks in triage and returns able to oversee an AI‑filtered queue with steady confidence.

“These companies do a great job recruiting our employees,” Hussey, head of Utah's DTS, says.

Long-term career strategy for Orem workers over the next 1–5 years is about stacking human strengths with practical AI oversight: start by deepening creative problem‑solving, emotional intelligence and complex judgment - areas KUTV notes that “remain where humans outperform AI” - while adding applied AI know‑how so reps can move from routine chores to supervising systems that handle them; local low unemployment and employer pressure to fill gaps mean AI will often be used to boost per‑employee output rather than simply cut headcount, so plan pathways that pair on‑the‑job rotations with short, role‑focused learning (see the Complete Guide to Using AI as a Customer Service Professional in Orem for tool‑and‑workflow tactics).

Over five years, prioritize certification in practical AI prompts and ticket‑triage oversight, cultivate cross‑functional fluency (product, compliance, ops), and insist on employer‑backed apprenticeships or apprenticeships that pay while teaching system governance - this positions workers to capture the value AI creates instead of being sidelined by it, turning automation into a ladder rather than a cliff.

“I will be working alongside humans to provide assistance and support and will not be replacing any existing jobs.”

Orem employers and HR teams should treat AI as a strategic tool, not a quick headcount fix: start by building a clear AI roadmap that ties automation targets to business KPIs and retraining plans, follow Utah's emerging policy playbook for safe deployment, and invest in bite‑sized, job‑embedded reskilling so frontline reps learn oversight and prompt‑writing as part of their shift schedule.

Use the Utah Office of Artificial Intelligence Policy's guidance to set governance, informed‑consent and data‑handling rules that protect customers and reduce compliance risk (Utah Office of Artificial Intelligence Policy guidance on responsible AI use), align training to measurable business outcomes per reskilling best practices (start with the Harvard Business Review framework to link learning to future roles: Harvard Business Review - Reskilling in the Age of AI), and partner with practical providers so employees gain usable skills quickly - for example, Nucamp's 15‑week AI Essentials for Work course teaches the prompt‑writing and tool workflows that let reps supervise automation rather than be replaced by it (Nucamp AI Essentials for Work - 15‑week bootcamp).

Add short rotations, manager dashboards, and employer-sponsored stipends so learning is visible; the goal is a workforce that boosts per‑employee output with AI while preserving the human judgment customers still need.

“Most jobs that are going to involve AI are going to be augmented by AI rather than replaced by AI,” said Zachary Boyd.