AI
GPT-4o for business: start with a workflow, not a demo
Multimodal AI opens useful possibilities. Here’s how to test one without handing over the decisions that matter.
Growth Gearshift3 min read
OpenAI introduced GPT-4o on May 13, 2024, describing a model designed to work across text, audio, and images. The announcement made a compelling demonstration, but a model demonstration is not a business case. Capabilities and access differed between ChatGPT and the API, so the first question is what your chosen service actually supports.
The opportunity is to test a specific bottleneck. Can a model prepare a better first draft from approved information? Can it help organize a document before someone reviews it? Treat each possibility as a hypothesis, not an automatic productivity gain.
Pick a task you can check
Choose work that happens frequently, follows a clear process, and has a result someone can verify before anything consequential happens. Summarizing approved meeting notes, preparing alternatives for a campaign brief, or organizing customer questions can be more suitable starting points than autonomous customer replies.
Write down the current baseline: preparation time, review time, factual corrections, and rework. Name the person accountable for the final result. If the pilot produces drafts more quickly but doubles review effort, the first-draft speed is not the whole story.
Use multimodal input deliberately
An image can supply context that is difficult to describe in a prompt. A team might test a draft description of an approved product photograph or an initial summary of a presentation. But visual interpretation can be wrong: a reviewer should confirm details against the actual source before the draft becomes a customer-facing claim.
Check the exact capability available in your tool before designing the process around it. An announcement about audio, images, and text does not mean every interface exposes every capability in the same way. Keep a fallback process for inputs the system cannot handle reliably.
Build three review checkpoints
A bounded pilot needs more than a good prompt. It needs checks at the points where an incorrect or inappropriate output could become someone else’s problem.
- Input check: confirm you are authorized to share the material and remove unnecessary sensitive information.
- Output check: compare names, figures, commitments, product details, and deadlines with the original source.
- Outcome check: measure the total time and correction rate, including the human review—not just the model’s response speed.
Keep final actions with people
Let the system draft, organize, or suggest. Keep external commitments, financial decisions, sensitive record changes, and customer communications behind a responsible person’s approval. A fluent answer can sound ready even when it contains an unsupported detail.
If a pilot is useful, document the inputs it accepts, the errors reviewers should look for, and when staff should stop using it. Expand only when the evidence supports expansion. The May 2024 launch matters as a milestone in multimodal AI; the longer-lasting lesson is to choose a measurable workflow before choosing automation.
The takeaway
A useful AI pilot has a bounded task, approved inputs, a human reviewer, and a measurable outcome.
Sources & further reading
This article uses an editorial archive date. Platform announcements are discussed in their historical context; linked help pages may change over time.