Can You Use AI to Help With College Essays?

AI Is Quietly Changing the Way We Evaluate Investments — Here’s How I Use It Daily

If you asked me two years ago how I evaluated investments, my answer would have been simple: spreadsheets, news feeds, and long evenings spent reading reports. It wasn’t glamorous, but it worked well enough. Today, my workflow looks entirely different — not because the market changed (although it always does), but because AI quietly moved in and took over half of my process.

I’m not talking about replacing human judgment. I’m talking about something far more powerful:
AI as an extension of how I think, research, and make decisions.

In this article, I want to share exactly how AI fits into my daily investment routine — not theory, not hype, but real-life ways I use it every day as someone who actively screens opportunities, studies trends, and tries to understand where the market is heading next.

Why I Started Using AI in the First Place

Like many people, I began experimenting with AI out of curiosity. One question led to another, and suddenly it became obvious:

• AI reads faster than I do
• AI helps me see patterns I usually miss
• AI reduces research time from hours to minutes
• And most importantly — AI helps me avoid emotional decisions

But the real breakthrough came when I realized AI wasn’t just helping with research.
It was transforming how I evaluate opportunities altogether.

Below are the five main parts of my workflow where AI plays a daily role.

1. AI as a Rapid Research Engine: Turning Noise Into Signal

The investment world is a firehose of information. A single day can include:

• market news
• regulatory announcements
• quarterly reports
• price movements
• investor commentary
• social signals

There is no realistic way for one human to process all of this every day — but AI can.

My real workflow:

Every morning, I feed the previous day’s news (crypto + macro + sector-specific) into an AI summarizer. I don’t ask for a general overview — I ask for risk signals.

My prompt looks like this:

“Extract anything that could materially impact investor sentiment, including red flags, regulatory actions, liquidity issues, token unlocks, insider sales, or macro indicators.”

The result is usually a clean, 5–7 bullet breakdown that replaces 40 minutes of manual reading.

Why this matters:

AI doesn’t get tired, overwhelmed, distracted, or emotionally attached.
It simply points at the data and says, “Look here.”

This has helped me avoid impulsive decisions more times than I can count.

2. AI for Financial & Tokenomics Analysis

I’m not an analyst by profession, so reading through tokenomics models or 100-page reports used to feel like running a marathon. AI changed that.

How I use AI for fundamentals:

• Upload the whitepaper or PDF
• Ask AI to identify economic incentives, distribution risks, inflation pressure, real utility, historical performance, or projected sustainability
• Request a neutral breakdown of risks vs. rewards
• Ask for a simplified summary that covers the project “as if I were checking it for the first time”

This works not only for crypto, but also:

• equity earnings reports
• REIT financials
• ETF sector exposure
• VC-style startup evaluations

Favorite example:

A few months ago, I was looking at a project that heavily promoted its “fair distribution”.
I fed the tokenomics PDF to an AI tool and asked:

“Identify any potential concentration risks in allocation, including lockup schedules and vesting cliffs”.

AI immediately flagged:

• 32% allocated to the team
• a 6-month cliff
• multiple large unlocks planned during bear-market conditions

I passed on the investment.
The token dropped 57% two months later.

AI didn’t predict the future.
It simply removed the blind spots.

3. AI for Pattern Recognition: Seeing Trends Before I Normally Would

Here’s something that surprised me:
AI is extremely good at identifying long-term patterns that humans overlook.

I often feed AI datasets like:

• historical price movements
• on-chain metrics
• social momentum indicators
• sector inflows/outflows
• developer activity trends

Then I ask:

“Identify patterns or correlations that are not obvious at first glance”.

For example:

• AI spotted that a particular DeFi token historically pumped during periods of rising ETH gas fees
• AI flagged that a gaming token’s activity correlated more with new user growth on Telegram than with Bitcoin dominance
• AI highlighted a predictable pre-halving pattern in some alt sectors that I never manually noticed

Important note:

I don’t use AI to “predict prices”.
I use it to understand behavior — which is more reliable.

AI gives me early awareness without pretending it’s a crystal ball.

4. AI as a Personal Investment Journal — but Smarter

This is the most underappreciated use case:
I let AI act as a thinking partner that tracks my reasoning.

Every time I consider a new investment, I write a quick note into an AI-powered journal:

• what the opportunity is
• why it seems attractive
• what risks I’m worried about
• what emotions I’m feeling
• what I might be missing

Then I ask the AI:

“Challenge my thinking. What cognitive biases might influence this decision?”

This single habit has saved me from:

• chasing hype
• entering too late
• ignoring red flags
• overestimating upside
• underestimating risk
• following crowd sentiment instead of logic

My returns improved not because AI became smarter — 
but because I became more self-aware.

5. AI for Scenario Testing: “What If” Simulations

One of the most useful (and fun) ways I use AI is for scenario forecasting.

Not prediction — but simulation.
There’s a difference.

I’ll ask:

“If BTC hits X, what historically happens to L2s?”
“How do small-cap tokens behave when liquidity dries up?”
“What would a regulatory crackdown mean for DEX tokens?”

AI replies with:

• historical precedents
• logical connections
• risk pathways
• potential second-order effects

This helps me see multiple possible futures, not just the one I emotionally prefer.

So, Is AI a Competitive Edge?

Yes — but not because it replaces expertise.

AI gives me:

• more data than I could ever process myself
• clean structure in a chaotic world
• higher clarity
• fewer blind spots
• more disciplined decision-making

It’s like giving your brain a second processor.

But here’s the part people often miss:

AI is not about finding answers.
AI is about asking better questions.

When I use AI well, it forces me to think deeper, act slower, and evaluate more carefully.

And in investing, that alone can change everything.

Final Thoughts

AI isn’t loud.
It isn’t flashy.
It doesn’t shout “look at me, I’m changing finance!”

It just quietly sits next to you, turns complex chaos into something understandable, and lets you make decisions with a clearer mind.

That’s why I use AI every day — not because it guarantees success, but because it makes me smarter, calmer, and more systematic than I would be on my own.

If I stopped using it tomorrow, I could still invest.
But I would feel like I suddenly lost half of my tools.

AI Is Quietly Changing the Way We Evaluate Investments — Here’s How I Use It Daily was originally published in Coinmonks on Medium, where people are continuing the conversation by highlighting and responding to this story.