Jefferies has issued a sector-level assessment that concludes artificial intelligence will not affect all business services equally. The brokerage identifies waste management companies as likely beneficiaries and traditional staffing firms as vulnerable to structural disruption.
The report notes that AI's capacity to automate repetitive processes and refine operations is most consequential for industries built on information workflows and administrative tasks. In those areas, software-driven tools can substitute for human intermediaries. By contrast, sectors anchored to physical infrastructure - where regulatory constraints and capital intensity matter - are less exposed to wholesale displacement by software.
In Jefferies' view, the waste sector exemplifies the latter category. The industry’s intrinsic advantages - owned or permitted landfills, established collection routes and similar hard assets - are difficult to duplicate. These assets depend on regulatory approvals and sizable capital investment, characteristics that create durable barriers to entry. AI can still add value within waste operations, the report says, by making routing more efficient, improving pricing and fuel management, and enhancing safety practices. However, those technological gains are framed as performance enhancers rather than replacements for the sector’s underlying asset base.
Another factor that strengthens the waste industry’s position is the accumulation of proprietary data generated through daily operations. Jefferies argues that large, proprietary datasets derived from routine activity can deepen competitive moats and support margin improvement over time as firms apply AI to extract more value from existing processes.
By contrast, Jefferies highlights traditional staffing businesses as cases where core functions are increasingly automatable. The report lists activities such as resume screening, candidate matching, interview scheduling and routine assessments as examples of tasks that AI tools are already handling. As these functions move to automated systems, the need for staffing intermediaries could diminish.
Jefferies further warns that AI may shrink demand for particular labor categories, specifically entry-level white-collar roles concentrated in administrative and back-office functions. If AI reduces demand in those segments, the report suggests staffing firms could face pressure on both growth and margins.
The brokerage also underscores that companies possessing extensive proprietary datasets and established platforms are positioned to capture disproportionate gains as AI adoption proceeds. High-quality, firm-owned data is identified as a critical input for training effective AI models; where those data assets exist, firms can potentially translate AI into competitive advantage.
Finally, Jefferies cautions that markets have broadly rushed to incorporate expectations of AI-driven disruption, producing volatility that may obscure which industries and companies will actually realize durable value from the technology. That dynamic complicates investment decisions even as the firm points to structural factors that separate likely beneficiaries from those at risk.