AI That Can Explain Things: A Buyer's Guide

What makes an AI good at explaining things

Explanation quality in AI comes down to three variables, and different tools optimise for different ones. Understanding which variable matters for your use case tells you which tool to use.

Most searches for “AI that can explain things” are looking for help with the first variable. The ones that feel disappointed afterward needed the second or third.

The main AI explainer tools — what each one actually does

The honest take: AI summaries and explanations are good enough for most readers on most topics. The one case where they're not is financial news — where the explanation without the market context is technically accurate and substantively incomplete.

Why financial news is where generic AI struggles most

Financial news has a specific problem that general-purpose AI is poorly positioned to solve: the stated fact and the actual news are often different things. The Federal Reserve held rates at 5.25%. That's the stated fact. The actual news — the thing that moved markets — is that they held when everyone expected a cut. An AI explainer that tells you what an interest rate is hasn't explained the article.

The FT and WSJ write for people who already carry this context in their heads. That's not a criticism — it's just an audience mismatch most readers don't realise they're in. The result is that the average financial article contains between 4 and 7 terms that require background knowledge to understand, and that background knowledge is assumed rather than provided. Generic AI tools fill in the definitions. They don't fill in the background.

This is the gap UNPACKTHIS is built for. Rather than explaining what a term means in isolation, it explains what the article means — terms defined in context, the market background stated explicitly, and the implication spelled out. The distinction between a definition and a contextual explanation is the difference between knowing what a basis point is and understanding why a 25-basis-point move surprised analysts in this quarter.

Investopedia gives you the definition. It doesn't give you why the definition matters in the article you just read. Asking ChatGPT the same question produces a slightly longer version of the same problem. This can be fixed.

How to get better explanations from any AI tool

If you're using a general-purpose AI and want a better explanation of something, the quality of what you get is almost entirely determined by how specifically you ask. Vague prompts produce textbook answers. Specific prompts — the ones that include what you already know and what you're still missing — produce something closer to an actual explanation.

1. 01

   State what you already understand

   "Explain this to me" is the worst possible prompt. "I understand that the Fed controls interest rates — what I don't understand is why holding rates caused markets to fall" is the prompt that gets you a useful answer. This matters because it prevents the AI from starting two steps before where you are.

2. 02

   Ask for the implication, not just the definition

   Most AI explanations stop at the definition. If you want the so-what, ask for it explicitly: "What does this mean for someone who holds equities?" or "What changes because of this?" The question that produces the most useful answer is almost always "compared to what?"

3. 03

   Push back once

   If the first explanation doesn't land, say so specifically: "That's the general definition — what I still don't understand is X." AI tools are significantly better at the second iteration than the first, because the first response is calibrated to the broadest possible interpretation of your question.

4. 04

   Paste the article, not just the question

   Context-blind AI explanations are the weakest kind. If you paste the actual article and ask for an explanation of a specific section, the tool works from the source material rather than from its training data. This is the difference that matters for news, where the specifics are everything.

When AI explanations still aren't enough

AI explanation tools have a real limitation that doesn't show up in demos: they are trained to sound helpful, which means they will produce a confident-sounding explanation even when the underlying situation is ambiguous. In financial news, ambiguity is often the actual story. “Markets are uncertain about the direction of rates” is a meaningful piece of information — and it's information that a generic AI summary will often paper over with a tidy explanation that resolves the ambiguity in a way the article itself does not.

The fix is to read any AI explanation critically and hold two questions in mind: does this match what the article actually said, and does this explanation raise any questions I still want answered? A good explanation should raise questions, not close them. If you have no questions after reading an AI explanation, either the topic was genuinely simple or the explanation was too shallow. For financial news, it's almost always the second one.

Reading more financial articles doesn't make you more financially literate. Reading fewer articles better — with explicit attention to what changed, why it matters, and what you still don't understand — does. The tool you use matters less than whether the explanation you received actually answered the question you had.

Frequently asked questions

What is the best AI that can explain things?

For general topics — concepts, ideas, science, history — ChatGPT and Claude are the strongest options. Both handle follow-up questions well and can adapt their explanation to your level. For financial news specifically, purpose-built tools like UNPACKTHIS are more useful because they explain the article in context rather than defining terms in isolation.

Can AI explain financial news accurately?

Yes, with caveats. General-purpose AI tools can explain financial terms accurately, but they often produce explanations that are technically correct without being contextually useful — the equivalent of looking up every word in a sentence without understanding the sentence. The risk is in the implied context: AI tools can generate plausible-sounding implications that weren't in the original article. Verify anything that starts with 'this means' against the source.

What's the difference between an AI explainer and a summary tool?

A summary tool shortens a text — it removes content. An AI explainer translates content — it makes something clearer without necessarily making it shorter. The best tools for financial news do both: they summarise the key facts and explain the terms that require background knowledge. Tools that only summarise often miss the explanation step, which is where most reader confusion lives.

Why does ChatGPT sometimes give me a generic explanation even when I ask about a specific article?

Because without the article text, it's working from its training data rather than from the specific piece. Paste the article directly into the chat and ask your question in reference to it — the explanation quality improves significantly. If you're still getting generic output, add a line explaining what you already understand and what specifically you're still missing.

Is Perplexity good for explaining financial news?

Perplexity is better for research than explanation — it gives you sourced facts from the web rather than a structured breakdown of what an article means. If you want to know the background on a company or event, Perplexity is excellent. If you want to understand what a specific article is actually saying and why it matters, a purpose-built tool handles that better.