Skill development examples: 16 employee skills to prepare your changing workforce

Tick, tick, tock: Three running clocks are making workforce skill development a more urgent challenge.

• The AI clock is changing how tasks are performed inside jobs.

• The market clock is reshaping which skills are valuable, scarce, and developing.

• The internal clock is tracking how quickly an organization can see change coming, understand its people's current skills, and develop the ones they need next.

These pressures are creating a talent velocity problem, a term LinkedIn uses in its 2026 Talent Report to describe an organization's ability to see internal skills, build or acquire what it needs, and mobilize talent in real time. The research found that 86% of organizations lack adequate talent velocity, and 89% are concerned about their ability to deliver the right skills at the right time for the right work.

When workplaces and the broader world are changing so quickly, how can HR and learning and development (L&D) teams effectively build the right skills, especially when they lack visibility into gaps?

Below, we explore the three pressures making it harder to anticipate changing skill needs, then share 16 soft, hard, and human skill development examples to help your workforce stay competitive as roles, technology, and business priorities evolve.

Three pressures making skills harder to see and develop

The AI clock: Work is rapidly changing

The AI clock is changing how work is completed across roles, and it’s a constantly moving target. PwC's 2026 Global AI Jobs Barometer found that for AI-exposed jobs, skills are changing more than twice as fast as jobs considered the least AI-exposed.

AI is introducing opportunity and efficiency, but also risk and uncertainty. It isn’t enough to add “AI literacy” to your organization’s skills development plan or approach AI as a new set of technical skills to master.

Instead, you must understand how AI changes individual roles, which tasks should shift to technology, and which technical and human capabilities become more important in an AI-augmented workplace.

When change is constant, you need visibility and workforce intelligence to make sense of what’s really happening across your teams and make confident decisions.

The market clock: The competition for skills keeps moving

Market demand for different skills is changing just as fast, due to a combination of AI, demographic changes, customer expectations, new regulations, and emerging industries. It’s creating constant pressure to predict which skills to develop today to support a not-yet-materialized future.

Without the right skills intelligence, forecasting how valuable different capabilities will be is hard and full of surprises. For example, the Cornerstone 2026 Skills Economy Report found that the demand for AI and machine learning skills rose 245% while once-stable skills declined, like customer service, which fell 18 ranking spots.

What was less expected, although more obvious in retrospect, were the other human skills that grew in demand: emotional intelligence was up 95% from 2023, resilience and flexibility up 42%, and leadership and social influence up 28%. It seems the robots aren’t yet replacing what matters.

When the global skills market moves in real-time, static job frameworks and annual workforce plans cannot keep pace. That’s why Cornerstone Workforce Intelligence, powered by the Cornerstone People Graph™, layers external labor market signals on top of internal workforce data, to show what skills are becoming scarce, expensive, or strategically important before those pressures become obvious internally.

The internal clock: Talent systems have to keep up

Many HR and L&D leaders probably hear our third clock in their sleep: How quickly and effectively can an organization turn all this change into processes and structures to support growth?

It’s not easy. Job architecture, role requirements, skills profiles, development plans, and workforce data all need to reflect the changing workforce. Yet Gartner found that 48% of HR leaders say demand for new skills is evolving faster than their existing talent structures and processes can support.

At the root, skills visibility takes the brunt of impact. Leaders may know broadly that they need more AI fluency, cybersecurity expertise, leadership capability, or data skills, but those gut feelings aren’t actionable.

Instead, HR leaders must answer:

• What skills will we need?

• Which roles need the skill?

• What does good look like in those roles?

• Who already has the capability?

• Who is close enough to develop it?

• Where would closing the gap create the most value?

These answers help to turn skills visibility into a living, evolving workforce development strategy.

Our three clocks show that there’s no universal skills list to future-proof your business. Some skills will decrease in priority over time, while other capabilities will prove especially durable as work changes.

DHL Group uses AI-powered skills insights to embrace change

As the world's leading logistics company, DHL Group needed to help its people keep up with the rapid pace of change by aligning the skills they had with what the business would need in the future.

Using Cornerstone AI-powered workforce software, DHL Group surfaced skill gaps and made it easier for employees to see internal career opportunities, the skills needed to reach them, and suggested development to get there. By giving people a vision for future growth within the company, DHL Group expected to cut external recruiting resources by more than 10%, saving millions while strengthening internal mobility and employee engagement.

16 skill development examples for today's workforce

Arun Chandrasekaran, Distinguished VP Analyst at Gartner, explains, "The real challenge for executive leaders isn't just automating tasks. It's reinventing talent strategy around agility, continuous learning, and human-machine collaboration.”

The following soft, hard, and human skills represent our best bet on talent management capabilities to build within your workforce as roles, technology, market conditions, and business needs change.

Soft skill development examples

Soft skills shape how people organize work, communicate, collaborate, and interact with others. They’re highly transferable between roles and influence important business outcomes, like customer satisfaction, employee retention, and the quality of external partnerships.

1. Communication

Good communication only becomes more vital as roles change, technology automates tasks, and work crosses teams and functions. Your people need to become comfortable sharing context, surfacing risks, clarifying decisions, and sending timely updates before work stalls. They also need to learn how to present and influence peers, stakeholders, and external audiences with different levels of expertise.

Develop communication skills by tailoring learning to the individual’s role and work context. Start by giving people clear guidance on how common scenarios should be handled, then use role-play, manager feedback, and review of real interactions to help people practice applying those standards until strong communication becomes second nature.

2. Time and priority management

Even the best workplaces experience priority whiplash.

When priorities change faster than capacity, people may struggle to keep up. Without time and priority management skills, the gut reaction is to try to do it all, which only causes people to lose sight of what’s actually important.

Meaningful productivity is all about making good tradeoffs, not trying to fit more tasks into each day. People need to recognize which work creates the most value, what can wait, and when a shifting business need requires them to change course. They also need to be comfortable and clear about when they should make these decisions and when to bring in a manager for guidance.

This skill is developed through communication, process, practice, and feedback. Give your people realistic situations with competing deadlines, constrained resources, and changing requirements. Empower them to make the prioritization decision, explain the tradeoff to stakeholders, and review afterward whether they made the right call or what they should have done instead.

3. Collaboration

Your people need to be comfortable working across teams, disciplines, geographies, and external partners. They must have the confidence to plan coordinated initiatives, bring in expertise, hold everyone accountable, and reach a desired result together.

Teach collaboration skills by putting people on cross-functional projects to expose them to different ways of working, keeping everyone on task, and delivering shared outcomes. Ask participants to clarify ownership, surface dependencies early, get feedback early and often, and reflect on what to do differently in the future.

4. Customer service and relationship skills

AI may take over the repetitive and manual support triaging, but your teams still need to be able to resolve higher-value conflicts, support customers, and deepen relationships. A 2026 Gartner survey found that customers pushed back when AI acted as a barrier to reaching a person, with 87% saying companies using generative AI for customer service must offer access to a human agent.

Use role-playing, simulated customer calls, and peer feedback to practice these skills. Create scenarios built around real moments of friction, such as an objection, escalation, policy exception, or dissatisfied customer. Focus on whether the person can listen for the underlying need, explain options clearly, make a sound judgment, and preserve trust, even when the answer isn't what the customer wants.

5. Conflict resolution

There’s no escaping occasional conflict, but your people must have the ability to work through disagreements without avoiding them or letting them get in the way of work. The rapid pace of change can heighten emotions and increase the frequency of disagreement over priorities, resources, responsibilities, and next steps.

Teach your people that there is rarely a “right answer”; there’s only the next best decision. People can practice separating facts from assumptions, identifying what each side needs, surfacing the real disagreement, finding a workable resolution, and standing behind it as a team, even when everyone is not in perfect agreement.

6. Negotiation and influence

Many organizations take the point of view that everyone’s in sales. After all, whether a team member is nurturing a client relationship, building an exciting new app feature, or ensuring partners and vendors get paid on time, everyone contributes to how other people experience and perceive the company.

The ability to influence and negotiate is a lasting skill. It uncorks potential in your organization, ensuring that any great idea can get the support it needs across customers, partners, finance, operations, or leadership to move forward.

Build negotiation skills through virtual or instructor-led courses on core concepts, such as uncovering underlying interests, addressing hesitations, and building a compelling response. Then put those concepts into practice with role-play simulations and feedback.

Hard skill development examples

When you think about workforce skills, hard skills are what often comes to mind. Hard skills are technical, measurable, or role-specific capabilities people need to perform particular work.

As tools and roles change, the lifespan of many technical skills is getting shorter. Gartner predicts that by 2030, the half-life of technical skills will drop from eight years to as little as two, so continually building and applying new ones is important.

7. Data literacy and analysis

Data literacy was already crucial in our tech-centered workplaces, but AI and automation have amplified this skill requirement.

Your people need to understand how to interpret and analyze data to make better decisions. That means understanding what metrics represent, knowing which are meaningful, recognizing weak or incomplete evidence, and connecting analysis to the next action. Skills to maintain data health are just as important, particularly as AI agents use data to trigger autonomous tasks.

Make data literacy and analysis training practical with workshops reviewing the team's real dashboards to teach them what each metric means, how to interpret the bigger picture, and examples of reasonable inferences to make. Incorporate data governance and data quality training to demonstrate how clean, accurate inputs enable confident decision-making and ensure AI agents and automations work reliably.

8. Using AI effectively

AI fluency needs to go well beyond writing a good prompt. More and more, your people will be building and managing AI-powered workflows, agents, and automations, which means choosing the right use cases, giving systems clear context and instructions, testing outputs before anything goes live, and monitoring performance once it's running.

People need to learn how to evaluate AI output by checking accuracy, spotting gaps or fabrications, and knowing when a result needs human review. They’ll also need to make regular judgement calls about where humans should stay in control, since an unchecked automation can repeat the same mistake at scale. Microsoft's 2026 Work Trend Index found that AI users rank quality control of AI output (50%) and critical thinking (46%) as the two human skills becoming more important as AI takes on more work.

AI effectiveness requires both practice and dedicated training time. Set up hands-on labs and sandbox environments to let people build and stress-test AI solutions on real tasks, then peer-review each other's builds before anything touches live work.

Additionally, provide scenario-based exercises that deliberately include realistic AI errors to teach people what to look for, and then peer reviews to compare what each person caught.

9. Project management

No surprise here. When organizations are constantly implementing new technology, entering markets, redesigning processes, or launching products, project management is everything.

Project management skills teach people to set clear priorities, ensure deadlines are met, avoid costly mistakes, and keep momentum steady. Fortunately, project management training is well defined, with recognized certification paths, such as project management professional (PMP) or Agile fundamentals.

Make sure the curriculum reflects how AI is changing project work, like AI-assisted planning and risk forecasting, automated reporting, and managing tasks handed off to AI agents. Then give people controlled stretch projects to practice what they’ve learned. An internal talent marketplace can help people find those projects beyond their own team.

10. Cybersecurity awareness

Cybersecurity isn't just the IT team's job anymore. Every person with a login, a company phone, or access to an AI tool is part of the organization’s attack surface. Verizon's 2026 Data Breach Investigations Report found that people played a role in 62% of breaches, whether through a simple mistake or falling for a scam.

AI is raising the stakes on both sides. Attackers are using it to write more convincing phishing messages, impersonate trusted voices, and move faster. Strong cybersecurity awareness means recognizing suspicious requests across email, text, and voice, knowing which AI tools and data are approved, and reporting problems quickly instead of hoping they go away.

Give people regular cybersecurity training and show what threats look like with phishing simulations for email, text messages, and voice calls. Pair these with role-specific microlearning on approved AI tools and data handling, so people know what they can and cannot do to avoid scams.

11. Role-specific technical skills

Sounds like a no-brainer, but as roles change at breakneck speed, your people need to regularly refresh the skills that make up their daily work, whether that's cloud architecture, financial modeling, clinical systems, or a completely new capability based on an emerging technology.

There are a ton of ways to train people on role-specific technical skills, from live simulations and hands-on labs to sandbox environments, supervised practice, and certifications. Whatever the format, the training needs to be continuous, tracked, and auditable in regulated industries like healthcare, financial services, and manufacturing. Measure success by whether people can perform the task on the job, not just whether they finished the course.

Human skill development examples

Human skills are all about nuance. They rely heavily on judgment, interpretation, adaptability, empathy, and creativity. Human skills become more important when work involves uncertainty, competing priorities, or situations where there’s no clear right answer.

12. Critical thinking, judgment, and problem-solving

As work gets more complex, your people must make more frequent judgment calls. Technology adds to this need, creating more data, recommendations, or automated actions that require human review and discernment.

Before acting, people need to ask: Can I trust this information? What's missing? Which assumptions matter most? And what's the right call given the circumstances?

Give learners real or simulated problems with more than one potential cause or incomplete or conflicting evidence. Require them to define the problem, explain their reasoning, test assumptions, gather missing information, consider multiple solutions, and evaluate what happened after they acted.

13. Emotional intelligence

Your teams will constantly navigate new expectations, changing responsibilities, uncertainty, feedback, frustration, and competing pressures. Emotional intelligence helps them recognize those dynamics and respond productively.

Self-awareness can be hard to build, but leading by example, coaching, observation, and feedback are all valuable devices here. People can review a difficult conversation, identify what they missed in the moment, consider how their own reaction influenced the outcome, and practice a different response for the next interaction.

14. Adaptability and resilience

Adaptability helps people cope and learn new ways of working when responsibilities, tools, and priorities change. Resilience, meanwhile, helps them learn from setbacks and redirect their efforts in constructive ways.

Job rotations, short-term gigs, and stretch assignments build adaptability by taking people outside of their norm. Then incorporate project retrospectives and peer learning cohorts to help people turn setbacks into learning, and measure whether they can absorb feedback, adjust their approach, and become productive under new conditions.

15. Creativity and innovation

Your organization can't adapt to new market conditions by always sticking with yesterday's processes. You need people who can question whether an existing approach still makes sense and imagine alternatives.

Creativity grows when your people have permission to brainstorm and test ideas. Take a recurring problem and give teams the opportunity to come up with different approaches to solve it, run a small experiment, and use the results to improve the next version. Share both failures and successes, so your team learns that failure and iteration are an acceptable part of the process.

16. Business acumen and cross-functional thinking

Building business acumen is how you develop your next wave of leaders, giving people the big-picture understanding they need to grow into new roles and make more independent decisions.

As appropriate, help teams understand business priorities and how their work and choices affect goals, customers, revenue, cost, risk, operations, and other teams.

Use job shadowing, rotations, cross-functional projects, customer exposure, and reviews of real business metrics to build that perspective. Simulate real-life scenarios, so people can see how their decisions impact different metrics, without real consequences.

Leadership skill development examples

On top of our 16 fundamental skills, existing and emerging leaders need additional capabilities to guide others through constant change.

• Developing talent: Understanding the skills each person has and will need, holding regular development conversations, and supporting growth into new roles.

• Coaching and feedback: Learning how to provide specific, timely feedback and answer questions to help team members improve, including constructive criticism.

• Delegation: Assigning work to the right person; setting clear processes, outcomes and constraints; providing autonomy; and resisting the urge to “just do it myself.”

• Building trust: Being transparent about decisions, following through on commitments, and creating an open door for people to raise concerns.

• Leading through change: Explaining why change is happening, listening to concerns, spotting where adoption breaks down, and modeling the new behavior.

• Redesigning work for AI: Deciding how work gets divided between people and AI and giving people the time and workflows to properly use the tools.

• Strategic thinking: Combining external signals and internal data to guide decisions and ensure short-term goals are advancing long-term priorities.

Leadership programs, mentorship, cohort-based learning, executive coaching, and stretch assignments are all helpful ways to build these capabilities.

Mérieux Université expands digital learning across its global workforce

Until 2019, Mérieux Université, which trains people across a global public health group, delivered most of its programs in person.

To keep pace with change, Mérieux Université embraced a flexible mix of hybrid and on-demand digital formats built on Cornerstone, including a deep content library, themed playlists, and continuing education initiatives like "Keep Learning."

Licenses grew from 1,000 to 3,500 in three years, and nearly 3,000 people now log in on their own to build new skills. Mérieux Université is now exploring immersive formats like VR training to keep engagement high and give people more ways to develop their skills.

How to close the visibility gap and build a skill development strategy

1. Connect skill development to a business outcome

To build a skills development program that actually moves the needle, you first must clearly define the business goal you’re supporting, such as reducing safety incidents or improving internal mobility.

These larger outcomes should ladder down to specific goals with business metrics tied to them, not just participation metrics, like course completions. For example, if your desired outcome is to improve internal mobility, the business goal might be to fill 30% of open manager roles with internal candidates within a year – specific, measurable, and time-bound.

Once defined, capture your current state to establish a baseline for measuring return on investment later.

2. Build visibility into the skills needed now and next

Use business strategy and role requirements to understand internal demand. Consider how AI and automation are already changing tasks, and use external labor market data to see which skills are rising, declining, or becoming scarce. Many organizations skip this step: Gartner found that only 31% of recruiting teams use labor market data to inform their talent strategy.

Don't try to define everything at once; start with a few business-critical skills that you want more of in your organization.

3. Understand current skills and identify priority gaps

Next, compare what the organization needs with the capability people already have.

You likely have a lot of data here: Skills profiles, employee self-assessments, manager input, performance information, learning history, credentials, project experience, and evidence from actual work all come together to start forming a picture of what you have and what you need.

From there, identify meaningful gaps at the individual, team, and organizational level, based on those business goals you’re trying to achieve. Then, consider where untapped or adjacent capability may already be available. For example, someone in customer support with strong data skills may be a closer fit for an analyst role than anyone realizes.

Round out the picture by bringing your people into the conversation. Ask them what skills they want to build, and then connect those aspirations to role expectations and business needs.

Cornerstone Workforce Intelligence, powered by the Cornerstone People Graph™, can make this whole process a lot less overwhelming. It maps the skills your people have against what each role requires to surface internal gaps, then layers in external labor market data to show which skills are rising, declining, or becoming harder to find. From there, Cornerstone Learning Solutions can recommend personalized learning paths, removing a lot of the guesswork.

4. Turn priority gaps into role-based development goals

Next, turn those skill priorities into specific development goals for your people.

An individual development plan should turn a broad goal like "improve data literacy" into something measurable, such as regularly reporting on a particular dashboard and recommending next steps based on the data. Again, goals should be specific, measurable, and time-bound, so the team member actively works to develop that skill.

Managers make or break this step. As the ones holding development conversations, they should regularly check in on skill development and progress toward goals, and incorporate skills as part of performance reviews.

5. Develop and validate skills through learning, people, and work

Combine formal learning with social learning and on-the-job practice. That can include content, mentoring, coaching, communities of practice, simulations, projects, gigs, feedback, and opportunities to apply the skill in everyday work.

Then validate that the skill has actually developed through manager observation, peer feedback, skills assessments, credentials, or proof that the person can perform the task on the job.

6. Measure capability, prove ROI, and recalibrate

Track whether the capability has improved, and importantly, whether it’s influencing the business outcome defined in step one.

Where possible, translate the improvement into financial value and compare it to the cost of the development program to tell a more useful ROI story.

Finally, review the signals, update role requirements and priorities, and adjust the development strategy accordingly.

Our three clocks will keep running and skill development plans will evolve in response, so treat development programs as a living strategy and revisit them every quarter.

Simplify skill development with Cornerstone Workforce AI™

Strategic skill development helps your people and organization stay ready and confident as the work around them changes. It helps you surface those skill gaps that go unnoticed until they’re critical and shows your people that you’re invested in their continuous growth.

Ultimately, skill development is an ongoing discipline built into how people work, grow, and interact, not a one-and-done initiative.

Cornerstone Workforce AI™ helps organizations of all sizes turn continuous development into a regular practice. Cornerstone Skills Architect infers capabilities from the work and learning people actually do, and keeps job architecture current as roles evolve. The platform can also recommend which tasks in each role are ready for AI, coach managers through performance conversations, and help people explore internal opportunities that fit their skills.

Frequently asked questions about skill development

What is a skill development example?

A skill development example shows both the capability someone wants to improve and how they will practice it. For instance, someone developing conflict resolution might practice a realistic workplace disagreement through role-play, get feedback from a manager, and then apply the techniques during real team conversations.

What's the difference between upskilling and reskilling?

Upskilling develops capabilities that help someone grow or perform better in their current role. Reskilling prepares someone to perform substantially different work or move into another role. Both work best when development connects to a clear role or business need rather than learning for its own sake.

How should organizations measure skill development?

Use multiple signals, including real-world application. Assessments and proficiency ratings can show progress, but also look at application: manager or peer feedback, project results, observed behavior, performance data, and business outcomes.