The news: Airline group Lufthansa plans to cut 4,000 roles by 2030 to boost profitability as it leans into AI adoption.
The Germany-based company said most layoffs will be limited to administrative roles as it evaluates what work won’t be necessary in the future. Lufthansa had 101,709 employees in 2024 and generated €37.6 billion ($40.7 billion) in revenues.
Part of a bigger trend: Lufthansa isn’t the only company slashing roles to avoid redundancies as AI adoption heats up. This trend reflects companies’ interest in both increasing efficiency through automation and reducing spending on employees to free up capital for AI investments.
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Salesforce CEO Marc Benioff said AI has helped the company cut about 4,000 customer service roles.
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Duolingo is scaling back reliance on human workers by not using contractors for tasks AI is capable of and only hiring when automation isn’t possible.
What it means: AI is offering the ability to enhance profits and productivity while raising concerns about employee vulnerability and the loss of human oversight and contributions. One-third of sales and marketing professionals anticipate a reorganization or redefinition of team roles due to AI adoption, per Intescia, and 26% plan to reduce their staff and marketing budgets.
The risks: When it comes to reducing marketing roles, the field is already cutting back on opportunities for young talent, which could compound staffing issues amid mass layoffs.
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- Using AI in place of human workers could lead to the loss of institutional knowledge as experienced employees exit, along with an erosion of the creative diversity on teams.
- It also risks reliance on opaque algorithms, potential bias in decision-making, and reputational damage if mistakes happen without adequate oversight.
Our take: While layoffs due to AI adoption are perhaps inevitable as companies chase profits, massive staff reductions can hurt both team morale and diversity of skills and perspectives on marketing teams.
Identifying areas where AI is making work redundant and redeploying or retraining employees to higher-value tasks—rather than hacking away at worker numbers—can preserve institutional knowledge and build trust in the technology’s use across an organization.