It’s Monday morning, and Jordan opens their laptop to start the weekly report. Except that the reporting tool they’ve used for three years is gone. It’s been replaced by a sleek new dashboard with unfamiliar icons and menus.
She received an email that said, “The new system is live! It’s faster and easier.” But Jordan can’t find the export button, the filters look different, and the clock is ticking on a client deadline. After 15 minutes of clicking, she gives up and calls the help desk to ask, “How do I pull last week’s numbers?”
That, my friends, is a serious training issue that IT failed miserably at. Across industries, non-technical employees are expected to adapt to a constant stream of new apps, workflows, and AI-powered features. Unfortunately, this often happens with little context or support.
Non-technical employees need training for all software even if it’s through to be intuitive and easy to use.
The result isn’t a lack of motivation; it’s friction. Research from McKinsey and other organizations continues to show that when organizations roll out technology without a people‑first enablement plan, adoption lags, errors rise, and value stalls.
This post is all about why non‑technical employees struggle with new technology and, more importantly, the specific technical problems that good training solves. The goal is to ensure that your next rollout meets the needs of employees and enables them to have a successful start with new company technology.
Why smart people struggle with new tech (and why it’s not their fault)
Nobody goes to work thinking they won’t use the new technology or do their job correctly. They may struggle, but it’s not their fault. There are several reasons why employees are unable to use new company technology.
Here are some of those reasons.
Poor rollout and thin training
Employees aren’t rejecting innovation; they’re reacting to poor execution. A 2025 workplace tech resistance report found that 1 in 7 workers have refused a new tool at some point, while over half report that rollouts create internal chaos, largely due to minimal training and clunky UX. Nearly 48% said more thorough training would make them far more willing to adopt new tools.
Human factors: uncertainty, overload, and perceived threat
System changes disrupt habits and, in some cases, threaten perceived job resources such as time, status, or competence. A 2024 article shows that resistance to digital transformation often stems from perceived resource loss and emotional responses (anxiety, frustration), not an anti‑tech mindset.
Leadership and strategy gaps
Employees are often more ready than leaders think. McKinsey’s 2025 Workplace Report finds that most companies are investing in AI, yet only 1% consider themselves mature in this area. The barrier isn’t employee readiness; it’s leadership alignment and the lack of a coherent adoption strategy.
“Transformation debt” and tool sprawl
Enterprises lose real money to digital inefficiencies when app sprawl and change fatigue accumulate faster than technical enablement is planned and executed. A 2025 WalkMe report estimates $104M per year in losses for large enterprises is due to digital friction. It also finds that programs using multiple digital adoption best practices can deliver 85% ROI on transformation investments.
Skills gaps are real and growing
According to a Gartner survey of business leaders, they expect a surge in skills needs over the next three years as AI and digital trends accelerate, making structured upskilling non-negotiable.
What this all shows is that people struggle, even smart people. They struggle to stay up-to-date with company technology and effectively apply it to their roles. And none of it is their fault; it’s typically due to a lack of training and poor planning.
The Technical Problems Training Solves
When most people think of training, they picture a webinar, a PDF, or perhaps a room with a group of people staring at an instructor. That’s pretty old-school, and in most cases, that’s not effective at all.
Effective technical enablement is different: it’s job or task-based skill building or in‑the‑flow guidance that removes friction. Here are the concrete issues it solves.
Adoption friction: “I don’t know what to click.”
Problem: New UI updates, terminology, and navigation patterns increase cognitive load, and employees won’t be able to naturally figure out the “right” way to do things, even if it seems easy to a handful of experts.
Training fix: Role‑based scenario-based simulations and walkthroughs, and in‑app guidance lower cognitive load and accelerate success and comfort with company technology. If you need proof that user guides aren’t the most effective way to train employees on software, there are studies about how employees perceive a system as more useful with modern training, such as Digital Adoption Platforms (DAPs).
Process inconsistency: “Everyone does it differently.”
Problem: Teams invent workarounds that corrupt data and kill reporting trust. Unstandardized training can even spread these bad workarounds further, exacerbating the issue.
Training fix: Standardize work and build training around those standards. Make the training available to everyone and provide additional resources that further reinforce the training and the proper use of the tool.
A checklist can create procedural consistency. Training best practices for enterprise systems emphasize workflow-aligned instruction that improves adoption and makes the training more relevant to the job.
High error rates and rework: “Why did that invoice fail validation?”
Problem: Employees are no longer familiar with how to use it correctly, which triggers errors that cascade throughout the system, causing significant issues.
Training fix: Scenario‑based practice (with immediate feedback) for tasks performed regularly, performance support for critical tasks that aren’t routinely performed, and embedded tooltips reduce errors and rework.
A common way to provide real-time support is by using contextual help with Digital Adoption Platform (DAPs). Deloitte highlights DAPs as a change strategy that provides just‑in‑time guidance to sustain adoption and competency in changing systems.
Support overload: “Tickets spiked after go‑live.”
Problem: Help desks drown in “how do I…?” tickets and calls post‑launch, driving costs and frustration, and leading to increased costs for support agents.
Training fix: Various training methods can be used to reduce help desk calls, and we’ve used them all! In‑app self‑help and targeted enablement deflect repetitive questions, while analytics identify where users struggle. Training videos are also an option and can be used as a great self-help training method.
Overlay guidance (aka contextual help) plus usage insights boosts proficiency, engagement, and IT support effectiveness.
Underutilized features: “We bought it, but no one uses it.”
Problem: Powerful capabilities remain idle because employees lack clarity on the “why” or “how” in their workflow.
Training fix: The best solution for this is before the software is even purchased or rolled out. If no one is using it, then it’s likely not addressing a genuine business need. But let’s say you’ve already got it, and if people start using it, then it will have a real business impact. How does training fix it?
Show people how it will improve their work, and then train to that solution. So tell them how they can “save 20 minutes closing a case,” and then show them how with training. McKinsey urges organizations to raise digital fluency across all roles, not just IT, to unlock value from AI‑ and software‑driven workflows.
Digital literacy gaps: “I’m scared of it because I’ve never used it.”
Problem: Digital literacy gaps are a real issue and remain a significant challenge for companies. If a group of employees is unfamiliar with technology, they will slow everything down.
Training fix: Take digital upskilling seriously and provide employees with the necessary resources to enhance their technology skills. In more general terms, this could mean giving them access to tools such as LinkedIn Learning. If there are more specific gaps, such as in company software, ensure that proper training is available and that help is accessible regardless of an employee’s skill level.
RAND found in one experiment that short, scaffolded digital literacy modules measurably improve proficiency and employment outcomes. RAND’s pilot found that daily computer use doubled and labor outcomes improved after foundational training.
What “good” looks like: a training blueprint that works for non‑technical employees
There are several simple steps your organization can take to ensure non-technical users have the support they need to enhance their work. It’s all about ensuring software has a point and that support is available.
There’s a lot more subtlety in there, though, so that’s why we’re here to provide that!
1) Start with the business problem, not the feature list.
Map the moments that matter by role (e.g., “create a compliant quote in 5 minutes”). Don’t write learning objectives, write performance objectives and make them on business terms (time saved, error avoided, risk reduced). Build targeted upskilling tied to strategic outcomes.
2) Layer training: simulate, then guide in the flow of work or provide performance support.
- Just before go‑live or even overlapping: hands‑on, role‑specific software simulations and scenarios.
- During go‑live: in‑app walkthroughs, smart tooltips, and searchable help.
- After go‑live: nudges for new features, refresher microlearning, and office hours.
Evidence shows that in‑app guidance increases intent to use and perceived usefulness, which are two precursors to sustained adoption.
3) Build confidence, not just competence.
Address the emotional side of change (loss of control, fear of mistakes).
4) Make leaders visible in the learning.
Adoption follows attention. Leaders should model the new workflows, make their decisions and the reasons behind them very public, and reward the desired behaviors. The gap is often leadership rather than employee willingness.
5) Treat training as a product: measure, iterate, and market it.
Borrow tactics from product management: track adoption, monitor where users drop off, and update training rather than making it a once-and-done activity.
6) Don’t skip foundational digital skills.
If the rollout assumes knowledge employees don’t have, adoption will stall. Ensure that employees’ base-level skills are known so that training can effectively work for all employees, rather than just those in the middle.
Measure the Business Impact (so training isn’t a cost center)
To keep the focus on results, define and publish a training scorecard for software rollouts. That training scorecard might rate aspects such as these to assess how well the training performed and to improve future efforts.
- Time‑to‑proficiency (days from first login to task completion without assistance).
- First‑week task success rate (by role/use case).
- Help desk ticket deflection (volume and categories related to the app).
- Error rates/rework (e.g., % of transactions failing validation).
- Depth of use (feature adoption beyond basic tasks).
- Perceived usefulness and confidence (pulse surveys).
Link these to business KPIs so that training serves the business rather than some obscure metric that doesn’t really mean anything. Say no thanks to butts in seats, the number of users who took training, or even the number of training assets created. Those are all useless metrics that are likely not even positive.
How A Good Training Solution Serves The Business (and example)
Imagine rolling out a new case management tool to your Customer Support team. At a high level, this process could look like this:
- Discovery: Shadow reps; identify top 10 tasks and failure modes.
- Design: Build simulation‑based training for those tasks; write in‑app guides for the exact steps; script tooltips for tricky fields.
- Launch: Self‑paced practice that takes no more than 30 minutes. A DAP surfaces task tours based on context.
- Reinforce: Weekly micro‑nudges (“30‑sec tip: merge duplicates in 2 clicks”).
- Measure: Track case resolution time, error rate, and ticket volume for the tool. Publish wins biweekly.
This approach addresses adoption friction, reduces errors, and cuts support tickets by replacing “figure it out” with “we’ll show you and provide help when you need it most.”
Deloitte’s perspective explicitly recommends this blend of training and in‑app enablement to manage and sustain change.
Wrap Up
Non‑technical employees don’t struggle with technology because they’re “not technical.” They struggle due to a lack of training and tools arriving without appropriate context, rollouts that ignore human factors, and training that stops at awareness instead of improving task-level fluency.
When you meet people in their workflow with the right practice, guidance, and leadership signals, you solve real technical problems: adoption friction, process inconsistency, errors, support overload, and feature underutilization. That’s how you turn confusion into measurable business outcomes.
If you’d like to explore providing non-technical employees who struggle with technology a path to success, schedule a free consultation. We’ve been working with organizations to help their employees grasp new company systems and work successfully in them, even if they’re starting from very little technical skills.