For decades, the talent equation for HR leaders was straightforward, if difficult: Build versus buy. Do we invest in training our current employees for a future role, or do we go to the market to hire someone who already possesses those skills?
Today, the model is fundamentally broken. Generative AI is not just creating new jobs; it is disassembling old ones, redefining roles at the task level with unprecedented speed. The stable, linear career paths that “build versus buy” assumed are evaporating.
This disruption demands a new paradigm. According to Mark Onisk, senior managing director of talent strategy and transformation at Skillsoft, the old dichotomy is being replaced by a far more dynamic real-time decision framework: augment, automate or acquire.
“The classic build versus buy model assumed stable roles and linear capability gaps,” Onisk tells HRM Asia. “GenAI has disrupted that stability—tasks within roles are fluid, and the value frontier moves weekly. Skills intelligence reframes the decision … at the task level, because that’s where work actually happens.”
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The shift from a role focus to a task focus is the new frontier for HR. The strategic question is no longer “Who do we hire for this job?” but “For this specific task, is it best to augment our human employee with AI, fully automate the task or acquire the scarce capability from the market?”
This is the central challenge of the modern skills-based organization, and it requires a new level of skills intelligence to manage.
Cutting through the data noise
The promise of a skills-based organization is alluring, but many HR leaders find themselves drowning in data—endless taxonomies, libraries of skills and complex dashboards that describe the problem without offering a solution.
“Noise is the enemy,” Onisk emphasizes. As organizations move into the next phase of skills-based strategy, he argues that leaders must demand one critical signal from their platforms: role-level skills adjacency paired with time-to-proficiency.
In practical terms, this means answering a single, powerful question: “Given our current talent and learning modalities, what is the shortest path—by person and by team—to the capabilities we need, and how confident are we in that estimate?”
This single piece of intelligence, Onisk argues, is what makes skills data actionable. “This matters because it translates abstract taxonomies into executable plans, prioritizes scarce learning time against business outcomes and underpins budget allocation across augment, automate and acquire decisions.”
It transforms the HR function from a simple record-keeper to a strategic scenario planner. If the organization must launch a new product in Q3, leaders can see precisely which teams can be upskilled the fastest and where they must immediately turn to the market to hire.
Activating the frontline manager
No matter how advanced a skills intelligence strategy is, it will fail if it remains solely within the HR department. Its true impact is only realized when frontline managers—the people who actually oversee talent—engage with the data.
This has always been the highest hurdle. Managers are already overloaded.
“Managers are overwhelmed because most platforms push data, not decisions,” Onisk notes. The key to adoption, he explains, is to deliver insights that are both intuitive and immediately useful. “Skillsoft’s design principle is simple: one screen, one action.”
Instead of complex dashboards, this approach delivers plain-language insights on capacity risk or critical skills gaps directly into the manager’s existing workflow, such as during performance check-ins or sprint planning. These insights come with pre-populated talking points and tailored learning paths, removing the friction between insight and action.
The goal is a fundamental behavioral change in the “middle layer” of the organization.
“The behavioral shift we target is moving from reactive backfilling to proactive capability planning,” Onisk says. “From generic training requests to targeted skill bets tied to outcomes, and from annual development cycles to quarterly capability sprints.”
Success, in this mode, is not measured by platform logins. It is measured by the percentage of managers who actively set and track skills objectives alongside their regular business objectives.
The 2026 horizon: Skills-based orchestration
If the current challenge is embedding skills intelligence into manager workflows, the near future promises something far more transformative. As AI-native platforms deepen their integration of human and artificial skills mapping, the next great pivot becomes possible.
Onisk calls this “skills-based workforce orchestration.”
By 2026, he foresees AI-powered platforms that enable dynamic role design. “Roles will evolve continuously as AI absorbs tasks, and the platform will propose new role shapes and rebalance work across people and models,” he predicts.
This future includes:
- Internal capability marketplaces: Platforms will match projects to talent based not just on declared skills, but on adjacencies, availability and validated time-to-proficiency, significantly accelerating internal staffing and mobility.
- Autonomous career pathing: With human oversight, employees will receive personalized, business-aligned progression paths, while leaders see an aggregate, real-time view of the organization’s capability trajectory.
- Policy-aware automation: All recommendations will be automatically compliant with internal workforce policies and external regulations, with fully auditable decisions.
This vision represents the ultimate fulfilment of the skills-based promise. It marks a profound shift for HR, moving the function beyond its traditional role of maintaining static structures.
“The net effect is profound,” Onisk concludes. “HR shifts from maintaining structures to orchestrating a living system where capabilities—not jobs—are the atomic unit, and where AI continuously proposes the next best move for the organization and every individual within it.”
