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AI agents: the five workflows that actually pay off · MBA Training AI

• 0:00
  Host: Leaders' Insights.
• 0:06
  Host: Five minutes on Pick the Five workflows where agents earn their keep.
• 0:09
  Expert: Three weeks ago, a midsize insurer I know quietly killed its agent program.
• 0:14
  Expert: Six figures, gone.
• 0:16
  Host: What did they do wrong?
• 0:17
  Expert: They pointed agents at everything.
• 0:19
  Expert: Claims triage, customer email, underwriting notes, fraud flags.
• 0:24
  Expert: The moment you spread agents across a dozen fuzzy tasks, you're not deploying software.
• 0:29
  Expert: You're gambling.
• 0:30
  Host: But that's the whole pitch, right?
• 0:32
  Host: Agents that handle anything.
• 0:34
  Expert: The pitch is the problem.
• 0:36
  Expert: What I'm seeing in the field is brutally simple.
• 0:39
  Expert: Agents earn their keep in maybe five workflow types.
• 0:42
  Expert: And everywhere else, they burn money and trust.
• 0:45
  Expert: The operators who get this treat it like hiring, not installing.
• 0:48
  Host: Name the five.
• 0:49
  Host: Don't hedge.
• 0:50
  Expert: Structured data extraction.
• 0:52
  Expert: Pulling fields out of invoices and contracts.
• 0:55
  Expert: Ticket routing and first draft replies.
• 0:57
  Expert: Road migration and test generation.
• 0:59
  Expert: Research aggregation.
• 1:01
  Expert: Meaning pull and summarize across known sources.
• 1:04
  Expert: And reconciliation.
• 1:05
  Expert: Matching records between two systems that never talk.
• 1:08
  Host: What do all five have in common?
• 1:10
  Host: Because that's the actual lesson.
• 1:12
  Expert: A checkable answer.
• 1:15
  Expert: Everyone produces output.
• 1:16
  Expert: You can verify fast and cheap.
• 1:18
  Expert: Did the invoice total match?
• 1:20
  Expert: Did the test pass?
• 1:22
  Expert: When a human can confirm correctness in seconds, the agent's occasional mistake costs you
• 1:27
  Expert: nothing.
• 1:28
  Expert: When verification is slow or subjective, one bad output poisons the whole thing.
• 1:34
  Host: So the durable principle is verifiability, not intelligence.
• 1:38
  Expert: That's it.
• 1:39
  Expert: The best team stopped asking, can the model do this task?
• 1:43
  Expert: And started asking, can I catch it when it's wrong?
• 1:46
  Expert: Completely different question.
• 1:48
  Expert: Open AI's own numbers show reasoning models, clearing high marks on coding benchmarks.
• 1:54
  Expert: Worth remembering they sell the models.
• 1:56
  Expert: So cross check against O'Reilly's developer surveys, which are messier and more honest
• 2:01
  Expert: about real world failure.
• 2:03
  Host: Give me the reconciliation example.
• 2:05
  Host: That one sounds boring enough to actually work.
• 2:08
  Expert: Boring is the tell.
• 2:09
  Expert: A logistics firm I worked with had two systems.
• 2:13
  Expert: The warehouse count and the finance ledger.
• 2:15
  Expert: Disagreeing on inventory constantly.
• 2:19
  Expert: Humans spent 40 hours a month matching rows.
• 2:22
  Expert: The agent does the matching, flags the mismatches, and a person approves.
• 2:27
  Expert: Errors dropped because the human now only looks at exceptions instead of drowning in
• 2:31
  Expert: the whole list.
• 2:32
  Host: Where's the trap in that?
• 2:34
  Host: Because it sounds too clean.
• 2:36
  Expert: The trap is letting the agent resolve mismatches instead of just surfacing them.
• 2:41
  Expert: The second you give it authority to change the ledger, you've removed the checkpoint.
• 2:45
  Expert: It'll confidently fix a discrepancy that was actually a real shortage.
• 2:49
  Expert: And now your books are wrong and nobody noticed.
• 2:52
  Expert: Keep the human on the approved step.
• 2:54
  Expert: Always.
• 2:55
  Host: Let's do the skip list.
• 2:56
  Host: What are people deploying agents for that they absolutely should not?
• 3:00
  Expert: Anything open ended with a customer on the other end and money on the line.
• 3:05
  Expert: Autonomous negotiation.
• 3:07
  Expert: Final say approvals.
• 3:08
  Expert: Multi-step chains where step four depends on step one being perfect.
• 3:15
  Expert: Those compound errors.
• 3:18
  Expert: Hugging face published work showing agent chains degrade sharply as steps stack up and
• 3:23
  Expert: they build the tooling so take the framing with salt.
• 3:26
  Expert: But independent MIT technology review reporting lands in the same place.
• 3:31
  Expert: Long autonomous chains fail quietly.
• 3:34
  Host: Fail quietly is doing a lot of work there.
• 3:36
  Host: Explain.
• 3:37
  Expert: The worst failure isn't the crash.
• 3:39
  Expert: A crash you see.
• 3:41
  Expert: The dangerous one is the agent that produces plausible garbage.
• 3:44
  Expert: A summary that's subtly wrong.
• 3:46
  Expert: A routing decision that's confidently misfiled.
• 3:50
  Expert: No alarm goes off.
• 3:51
  Expert: You find out three weeks later when a customer escalates.
• 3:55
  Expert: That's how the insurer died.
• 3:56
  Expert: Silent errors accumulating under a green dashboard.
• 4:00
  Host: So how do you even start without becoming that insurer?
• 4:03
  Expert: Pick one workflow from the five.
• 4:05
  Expert: Run the agent in shadow mode for a month.
• 4:07
  Expert: It does the work.
• 4:08
  Expert: But a human still does it too.
• 4:10
  Expert: And you compare.
• 4:12
  Expert: If the agent matches the human on the checkable metric, you promote it.
• 4:16
  Expert: If it doesn't, you've spent one month, not a budget.
• 4:19
  Host: One thing the listener does tomorrow, go.
• 4:22
  Expert: Take your candidate task and ask, can someone confirm the answer is right in under 30 seconds?
• 4:27
  Expert: If yes, it's an agent task.
• 4:30
  Expert: If no, if verifying takes an hour or a judgment call, walk away no matter how good the
• 4:36
  Expert: demo looked.
• 4:37
  Expert: That single question would have saved that insurer their six figures.
• 4:41
  Host: What we read for this one, ours, Technica AI, TechCrunch AI, the decoder, KD Nuggets,
• 4:47
  Host: MIT Technology Review, O'Reilly Radar.
• 4:50
  Host: We'll leave it there.
• 4:51
  Host: The AI self-assessment at MBA-training.com will tell you where you really stand.