Editorial
Research Report
The State of the Digital Workplace
For decades, workforce planning followed a familiar playbook. When gaps appeared, leaders had two options: train people or hire new ones. Those levers still matter — but they no longer tell the whole story.
Technology cycles have compressed, AI is changing not just which jobs exist but how work gets done, and the people doing that work are navigating constant uncertainty without a clear picture of where they stand.
What’s striking isn’t that employees are resisting change. Most aren’t. They’re hesitating because they’re unsure their skills still matter, they don’t feel ready for what’s coming and they’re not convinced leadership has a real plan. When that confidence breaks down, performance breaks with it.
Leaders need to stop thinking about talent as roles to fill and start thinking about it as a living set of capabilities — capabilities that need to be understood, developed and used continuously. Workforce strategy can’t be reactive anymore. It has to be deliberate, grounded in data and tied to business outcomes.
When capability gaps appear, leaders have four choices. Build, buy, borrow or bot. Each has a place. What separates the organizations that get this right is how intentionally — and how honestly — they make those choices.
Build: Make Development a Business Discipline
The strongest organizations start with what they already have. Developing internally isn’t just cheaper. It’s usually the smarter move. Done well, it protects institutional knowledge, keeps people around and produces a workforce that can adjust as priorities shift.
The trap is treating development as a program rather than a system. Offering courses isn’t the same as building capability. Real progress means connecting skill development to the actual business strategy — being specific about which skills matter, why they matter and how you’ll know if it’s working.
That requires visibility. Leaders need a clear, shared picture of what capabilities exist across the organization today and how those map to where the business is going. Without that, development efforts scatter and don’t compound.
Technical skills — data, digital fluency, AI — are non-negotiable. But they’re not enough. Judgment, communication, collaboration determine whether technology creates value or just noise. The organizations that invest in both are the ones that turn disruption into an edge.
Treat building talent like any other business discipline — with structured reviews, succession planning and real accountability — and it becomes the foundation everything else sits on.
Buy: Hire for Capability, Not Credentials
Sometimes you can’t build fast enough. Market shifts, new technologies, competitive pressure create immediate gaps that require outside expertise. Strategic hiring still matters. But it works best when it’s precise.
Too often, hiring decisions chase job titles rather than capabilities. A better approach asks what someone can actually do, not just where they’ve been. Skills-based hiring opens up broader talent pools and surfaces candidates who can contribute quickly when things are moving fast.
Getting onboarding right matters as much as getting selection right. New hires do their best work when expectations are clear from day one — what success looks like, how they’ll be evaluated, how they fit with the team already there. With that kind of clarity, external talent accelerates things. Without it, it creates dependency.
Hiring shouldn’t substitute for development. But when it’s tied to a broader skills strategy, it’s a sharp tool for bringing in new capability without losing sight of long-term goals.
Borrow: Bring in Outside Expertise Without Losing Ground
Not every capability needs to live inside the organization permanently. Contractors, consultants and partners can provide speed and specialized knowledge — especially during major transitions.
Whether borrowed talent delivers depends almost entirely on how it’s integrated. External experts working in isolation rarely move the needle. The engagements that work are the ones where internal teams are collaborating alongside outside partners — and build their own capability in the process.
That takes deliberate leadership. Clear goals. Shared ways of working. Honest communication. Skills get someone in the door; trust and collaboration determine what they actually contribute.
Done right, borrowed talent delivers immediate results and leaves the organization stronger than they found it.
Bot: Let Technology Do What It’s Good At
AI has moved past the experimentation phase. Automation and intelligent tools are embedded in everyday workflows, handling tasks that used to eat up time people could spend on harder problems. The question isn’t whether to use AI anymore — it’s how to use it well.
The organizations getting the most out of it treat AI as a partner, not a replacement. Technology is fast, scalable and good at patterns. People are good at context, judgment and problems without clean answers. Value shows up where those two come together.
That’s where workforce readiness becomes decisive. Employees need to understand what AI can do, what it should do and where human judgment still has to be in the room. Leaders set those boundaries. They’re responsible for making sure technology decisions align with organizational values — not just business priorities.
AI doesn’t reduce the need for a skills strategy. It raises the stakes for one. A workforce that isn’t prepared to work alongside intelligent systems will leave a lot of that investment on the table.
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Making the Choices Work Together
In practice, most organizations aren’t choosing one of these strategies — they’re running several at once. The real question isn’t which lever to pull. It’s whether the decisions are connected.
Take a mid-size financial services firm rolling out AI-assisted underwriting. Early skills assessments surface three realities quickly: underwriters know the business but lack confidence using the new tools; the data team has technical expertise but limited underwriting context; and two planned external hires no longer make sense in the new model.
That’s build, buy and bot showing up at the same time — whether leaders label it that way or not. What makes those choices workable is having clear skills insight underneath them.
The response is coordinated. Underwriters move into a targeted upskilling pathway focused on the specific workflows AI will change. The data team is paired with senior underwriters for structured knowledge transfer, closing context gaps without new headcount. External hiring is redirected toward a single specialist who helps both teams build capability, then steps back. The AI tool is rolled out in phases, starting with teams whose readiness assessments show they can use it safely and effectively.
None of those decisions work on their own. The upskilling only makes sense if you know which workflows are changing. The hiring shift only works if you can see where the real gap is. The phased rollout only holds if you have a readiness signal you actually trust.
This is what skills management looks like in practice. It’s not a dashboard or an annual survey. It’s the operating logic that connects build, buy, borrow and bot into a system — so when conditions change, and they will, leaders aren’t guessing. They’re adjusting from a clear understanding of where their workforce is ready and where it isn’t.
Editor's Note: How else is workforce planning adjusting for AI?
- Humans and AI Agents: Planning the Org Chart of Tomorrow — Why AI agents belong on your org chart — and how to incorporate them.
- Your AI Workflows Will Outlast the Leaders Who Approved Them — AI agents don't create accountability problems, they inherit them. When autonomous systems outlast the teams that built them, ownership disappears.
- From Tool to Teammate: How AI Is Rewiring People Strategy and What HR Can Do to Adjust — HR leaders see AI transforming work beyond automation — reshaping teams, culture and people strategy. The future is “human-engaged” work, not human-replaced.
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