By: Chris Partlow, Senior Director of Technology, KellyOCG
While AI often takes the blame for headline-grabbing job cuts, it is also spurring the quiet emergence of new jobs. Beneath the hype, much of the real AI-driven transformation takes place in specific functional areas at the ground level, where the makeup of work itself is being dissected, reassembled, and elevated.
Only 10 – 15% of jobs are vulnerable to replacement over the next five years. This involves a high number of positions but doesn’t account for the full impact of AI within an organization. While most roles are unlikely to be fully eliminated, the tasks and skills required to perform them are rapidly evolving.
Business leaders and hiring managers must now ask, “Which tasks within every job are candidates for AI-powered transformation, and what does that mean for our people?” As a result, organizations are not only reorganizing roles but also the asks associated with and, ultimately, the hiring models needed to sustain this organizational change into the future.
Key findings stand out:
Traditional roles are fragmenting into combinations of responsibilities that neither legacy job descriptions nor four-year degrees capture. The term “new-collar” worker refers to talent that exhibits not only a practical combination of technical, manual, and soft skills but also a strong capacity to learn new skills that may not be taught in most higher education institutions.
Developing a strategy to engage “new-collar” talent means looking beyond traditional candidate pools, including those upskilled through bootcamps, certifications, or on-the-job learning. This approach yields a more resilient workforce, prepared to step into newly defined roles as AI continues to reshape the work landscape.
When tasks within roles shift rapidly, organizations can draw on granular data about in-demand skills, available talent, and overall hiring patterns to determine how to structure the job and target the right talent. It enables hiring teams to determine whether the required skills are available internally or if they need to look outside.
As the work evolves, an organization may use data-driven insights to help recreate jobs and organize how work is executed from the ground up. That same data can also reveal the work model for the talent you need, whether a contractor, a permanent hire, or a mix of the two, depending on the situation.
A talent solutions partner can prove valuable in this decision-making if they have the technology ecosystem and expertise to deliver visibility and practical insight.
As new tasks replace or augment old ones, the internal workforce must keep pace. This doesn’t always require sweeping reskilling efforts. Adjustments can be made by reconfiguring teams, cross-training, and encouraging lateral moves based on specific strengths. Companies that develop clear models for ongoing skill development and match learning opportunities with anticipated task needs are positioned to adapt quickly, minimizing disruption as AI adoption advances.
AI-driven skills will continue to evolve rapidly, and many organizations need workers who can acquire new skills and solve problems. This skilled workforce is important across all sectors, but securing talent remains a challenge.
Companies seek the most efficient way to stay connected to the talent they need. They are applying a mix of skills-based hiring approaches, tapping into internal employee talent, leveraging contractors, and reaching beyond traditional definitions of work. Focus on the task, and the outcome becomes clear.