Last week, we asked a simple question with serious implications: Which types of decisions should always require human judgment, even as AI tools become more advanced?
- Employee hire or dismissal: 0%
- Award or disqualify bids: 0%
- Budget or funding approvals: 0%
- All of the above: 100%
That result was surprising. And also telling.
Because when forced to choose, leaders did not want partial automation. They wanted responsibility. They wanted humans in the loop everywhere it mattered.
Here is why that instinct is right and why each of these decision areas must remain human led, even as AI becomes more capable.
Employee Hire or Dismissal
Hiring and firing decisions shape lives, careers, and livelihoods. AI can screen resumes, identify patterns, and surface risk signals, but it cannot fully account for context. It does not understand gaps caused by caregiving, military service, illness, or bureaucratic error. It does not feel the downstream impact of a false negative or an unjust dismissal.
More importantly, accountability matters. When a hiring decision is challenged, the answer cannot be “the model decided.” Federal leaders must be able to explain why a person was selected or removed, in plain language, grounded in human judgment. AI can inform these decisions, but the authority must rest with a person who is willing and able to own the outcome.
This is not about mistrusting technology. It is about protecting dignity, fairness, and due process in systems that directly affect people’s lives.
Award or Disqualify Bids
Procurement decisions sit at the intersection of trust, competition, and public dollars. AI can help analyze proposals, flag compliance issues, and detect anomalies. But awarding or disqualifying a bid is not just a technical exercise. It is a judgment call with legal, economic, and reputational consequences.
Models learn from historical data. Procurement history often reflects legacy vendors, entrenched relationships, and past biases. Left unchecked, AI can reinforce those patterns under the guise of efficiency. A human must be there to question the output, recognize when something feels off, and intervene when fairness or intent is at risk.
In federal contracting, transparency is non negotiable. Human oversight ensures decisions can be defended, audited, and trusted by all parties involved.
Budget or Funding Approvals
Budgets are not spreadsheets. They are expressions of priority, risk tolerance, and public obligation. AI can forecast, optimize, and simulate scenarios, but it cannot weigh political realities, emerging threats, or moral tradeoffs.
Funding decisions often involve choosing between competing goods. Efficiency versus equity. Speed versus resilience. Short term gains versus long term stability. These are value judgments, not optimization problems. They require leaders to consider consequences that may not be visible in the data.
Keeping humans in the loop ensures that budget decisions remain aligned with mission intent and public responsibility, not just numerical outputs.
Why “All of the Above” Was the Only Acceptable Answer
The 100 percent response tells us something important. Even as leaders embrace AI, they instinctively know where the line is. They know that some decisions are too consequential, too human, and too accountable to outsource entirely.
The risk is not that AI will replace judgment overnight. The risk is gradual erosion. Small delegations that turn into defaults. Recommendations that quietly become decisions. Humans who stop questioning outputs because the system has not failed yet.
This is exactly the tension we explore in our upcoming white paper, The One AI Question Federal Leaders Can’t Avoid – And Four Others They’re Struggling With.
The first question is the hardest for a reason: Which decisions must never be outsourced to AI, no matter how advanced it becomes?
Because once that line blurs, trust follows.
If you want early access to the paper or to join the ongoing conversation, join the ACG mailing list or reach out to us directly.
This is not about slowing AI down.
It is about leading it responsibly.