Choosing the right AI model

AI models can be incredibly powerful tools for saving time, cutting costs, and boosting productivity. But like any tool, they work best when you use the right one for the job. In this article, we’ll explore the four main types of AI models used in business today: chat models, image generators, game-style learners, and all-in-one (multimodal) models. We’ll walk through their strengths, how you can use them day-to-day, and what to watch out for.

Chat Models

What they are:
These are AI tools that understand and generate human language. Examples include ChatGPT and Claude. You type in questions or prompts, and they respond with clear, often helpful answers.

Strengths:

• Writing and editing: Chat models can quickly draft emails, write reports, or create customer responses.
• Idea generation: They help brainstorm meeting agendas, marketing slogans, and new approaches.
• Summarizing information: Quickly condense long documents into digestible overviews.

Why it’s okay to use AI here:
You’re not handing over control—you’re giving it the first pass. Think of it as drafting support that saves you from starting with a blank screen.

Weaknesses:

• Doesn’t always get the facts right:
  Workaround: Ask for sources, double-check data, and use it for framing, not final decisions.
• Can be too generic:
  Workaround: Personalize after the draft. Inject your voice and insight.

Image Generators

What they are:
Tools like DALL·E and Midjourney that turn written descriptions into pictures.

Strengths:

• Fast visual content: Perfect for mockups, slides, and early-stage design.
• Creative inspiration: Great for exploring options before involving a designer.
• Low-cost drafts: Ideal for lean teams with minimal creative resources.

Why it’s okay to use AI here:
Speed and direction matter more than polish. These tools give you a jumping-off point.

Weaknesses:

• Poor detail rendering:
  Workaround: Use image editors to fine-tune. Generate assets in stages if needed.
• Not consistent with brand design:
  Workaround: Use it to explore ideas, then hand off to a designer for brand alignment.

Game-Style Learners

What they are:
Models that learn by repetition—often used in robotics, logistics, and simulations.

Strengths:

• Efficiency modeling: Simulates thousands of options to find the best path.
• Process automation: Learns how to execute workflows more accurately over time.

Why it’s okay to use AI here:
These tools do the heavy simulation work, helping your team focus on strategy and oversight.

Weaknesses:

• Needs lots of training data:
  Workaround: Use pre-trained models or simulation tools to cut setup time.
• Struggles when context shifts:
  Workaround: Keep a human in the loop for real-world oversight.

All-in-One (Multimodal) Models

What they are:
Advanced models like GPT-4o or Gemini that handle text, image, audio, and more—often in the same task.

Strengths:

• Handles complex workflows: Can take in a spreadsheet, an image, and audio, and return a written summary.
• Useful for cross-functional teams: Great when multiple data types are in play.
• Context-rich responses: Helps reduce back-and-forth when teams need to connect dots fast.

Why it’s okay to use AI here:
These tools cut across roles and data formats. If you’re juggling tools or data types, they consolidate the load.

Weaknesses:

• Slower to process large inputs: Workaround: Break tasks into smaller steps or simplify data before submitting.
• Still evolving:
  Workaround: Use for drafts, experimentation, or collaboration—not critical final decisions.

Final Thoughts

No single AI model is perfect for every task. But when you understand each model’s strengths, you can use them as leverage—delegating the right task to the right tool. That’s how businesses get more done without adding headcount.

Start small. Use one model to automate or speed up one part of your workflow. Test, adapt, and scale from there.

Efficiency comes from alignment—not perfection.