The tools to get ahead of AI disruption already exist — we just need to use them differently

Dozens of proposals have emerged to address what is fast becoming a GDP-level problem. Some ideas are sweeping; others are tactical. What unites them: urgency. AI is already reshaping jobs inside offices, hospitals, factories, and warehouses. Headlines about AI-linked layoffs confirm the transformation is already underway.

Time is running out — and the answer isn’t to wait while new systems are built. It’s to redirect the systems we already have in tandem.

The United States does not lack workforce funding. More than $250 billion flows annually through federal workforce-development programs. Employers spend tens of billions more on education benefits and corporate learning. We just need to use these funds better.

What employers can do now

Tuition-assistance programs are the most immediate place to start. Too often treated as retention perks, they can be deployed far more strategically in this AI moment. Redirecting even a portion of those funds toward stackable credentials and adjacent skill pathways can help employees move into new roles before their current ones are automated or redefined.

State workforce and unemployment programs can also create room for retraining. In many cases, employers can reduce worker hours while employees maintain partial income support and use that time for training. Used well, these mechanisms let companies reskill their workforce without forcing employees to choose between a paycheck and a future — and workers can be redeployed into new roles quickly, minimizing time spent unemployed.

What states can do now

States have powerful levers available. Through governors’ reserve funds and incumbent worker training funds under the Workforce Innovation and Opportunity Act (WIOA), states can support workers who are still employed but increasingly vulnerable to AI-driven disruption — workers who are often overlooked by systems designed primarily for the unemployed.

When states braid these funding streams together with employer investments, public dollars go further and reskilling can happen at scale. Adaptation becomes a shared effort, not an individual burden.

Birmingham, Alabama, proves this model works. A federal grant there aligned public funding with real hiring demand from a healthcare employer and job placement. Workers without clinical experience are moving into family-sustaining roles tied directly to actual job openings — not just credentials. 

Other countries are moving with similar urgency. Singapore’s SkillsFuture program prioritizes job-aligned, employer-backed training that supports lifelong employability rather than short-term course completion. The lesson from these examples is consistent: adaptation is smoother when action comes before a crisis.

We must act before disruption becomes displacement

This is not an argument against long-term reform, new commissions, or public-private partnerships — those are essential. But today’s workers cannot afford to wait for every part of that agenda to fall into place. The practical path is to start now, using existing infrastructure, building pilots that deliver near-term results while informing broader reform over time.

The most immediate steps are clear:

• Employers should treat education benefits and learning programs as transformation tools, not perks.
• States should deploy incumbent worker support using tools already at their disposal.
• Local leaders should replicate demand-driven models that connect training to real jobs.

AI is advancing on its own timeline. Business and government still have agency over how this transition unfolds. The question is not whether the tools are perfect. It’s whether we will use them before disruption becomes displacement.

The opinions expressed in Fortune.com commentary pieces are solely the views of their authors and do not necessarily reflect the opinions and beliefs of Fortune.