Artificial Intelligence is everywhere in broker software right now.
Every platform claims to be “AI-powered”, “AI-enabled” or “using AI” — but when you look under the hood, those claims often mean very different things.
For brokers, this creates confusion:
- Is the tool thinking for me?
- Is it just speeding things up?
- Or is it simply marketing language?
This guide is designed to clarify how we talk about AI at Broker Tools, explain the different types of AI used in broker businesses, and give you practical questions to ask software providers so you can separate real capability from buzzwords.
This article also doubles as a FAQ you can return to when reviewing new platforms.
Why “AI” Feels Confusing Right Now
AI is not one thing — it’s a spectrum of capabilities.
Two tools can both say “we use AI” while doing completely different jobs:
- One might simply read a document
- Another might extract data, validate it, trigger actions, and update systems
- Another might decide what to do next without being told
All three are “AI”… but only one truly changes how you work.
The 4 Types of AI We Refer To in Broker Businesses
At Broker Tools, we group AI into four practical categories:
- AI-Enabled
- AI Integrations
- AI Automations
- AI Agents
Understanding the difference is key.
1. What Does AI-Enabled Mean?
AI-enabled usually means AI is used somewhere in the product — but not necessarily in a way that transforms workflow.
Common examples
- OCR reading a bank statement
- AI transcribing a phone call
- AI tagging or categorising documents
- AI suggesting fields (without saving or acting)
What it does
- Assists a single task
- Improves accuracy or speed
- Still requires manual follow-up
What it doesn’t do
- It doesn’t complete workflows
- It doesn’t move data between systems
- It doesn’t make decisions
Important distinction:
OCR reading a document does not mean the system can automatically fill a fact find, validate data, or submit an application.
AI-enabled = assisted intelligence, not automated intelligence.
2. AI Integrations (Analysis, Summaries & Insights)
AI integrations use AI to analyse, summarise, compare or interpret data, usually on demand.
This is where many platforms sit today.
Examples
- Summarising a client application
- Comparing lender policies
- Generating notes from uploaded documents
- Producing a credit or serviceability overview
- Drafting emails or recommendations
What it does well
- Saves thinking time
- Reduces manual review
- Improves consistency
- Helps brokers explain decisions to clients
What to look for
- Does it pull from your data or generic prompts?
- Is the output editable and auditable?
- Can it reference sources (documents, policies, data)?
AI integrations = intelligence on request.
3. AI Automations (Rules + Intelligence)
AI automations combine AI with rules, triggers and workflows.
This is where AI starts to materially reduce admin.
Examples
- Extracting data and writing it to the CRM
- Validating documents and flagging issues
- Triggering tasks when data is missing
- Updating pipeline stages automatically
- Pre-filling lender forms after validation
Key difference
Automation means:
AI output directly causes an action
Not:
- “Here’s a summary, now you copy it”
But: - “This is complete — the system has updated it for you”
Questions to ask software providers
- What actions happen after AI runs?
- Where is the data saved?
- Can I audit or override decisions?
AI automations = intelligence that does something.
4. AI Agents (Autonomous & Goal-Driven)
AI agents are the most advanced form of AI in broker businesses — and still relatively rare.
An AI agent:
- Has a goal
- Knows the steps to achieve it
- Can decide what to do next
- Can use tools, data and integrations without being told each step
Examples
- An agent that prepares a deal for submission
- An agent that follows up missing documents
- An agent that reviews a deal and flags risk before submission
- An agent that monitors pipeline health and suggests actions
What makes an agent different?
AI agents = digital team members, not tools.
Common FAQ: “This Tool Says It Uses AI — What Should I Ask?”
When a software providers says “we use AI”, ask:
1. Where does AI sit in the workflow?
- Reading?
- Analysing?
- Acting?
- Deciding?
2. What happens after AI runs?
- Is data saved?
- Is something updated?
- Or do I still do the work?
3. Is this AI-enabled, automated, or agent-based?
If they can’t answer clearly — that’s your answer.
4. Can I see and control the output?
- Is it explainable?
- Is it auditable?
- Can I override it?
Why This Matters for Brokers
AI should:
- Reduce cognitive load
- Remove duplication
- Improve compliance
- Increase consistency
- Scale without adding staff
It should not:
- Create more steps
- Hide logic
- Lock data away
- Replace judgment without transparency
How We Use These Definitions at Broker Tools
When we review platforms, we don’t just ask “does it use AI?”
We ask:
- What type of AI is this?
- Where does it sit in the broker journey?
- Does it give energy back or take it away?
That’s the lens we use — and the lens we recommend you use too.
Final Takeaway
Not all AI is created equal.
- AI-enabled helps you see
- AI integrations help you think
- AI automations help you do
- AI agents help you scale
Knowing the difference puts you back in control — and makes sure AI works for your business, not just around it.
Still not sure?
AI language can be noisy — and not every broker needs the same level of automation or intelligence.
If you’re unsure what type of AI your current tools are actually using, or whether a platform is AI-enabled, automated, or agent-driven, have a chat with one of the Broker Tools team.
We’ll help you:
- Decode software providers AI claims (without the sales spin)
- Sense-check whether a tool fits your workflow and stage
- Identify quick wins using tools you may already be paying for
- Flag where AI genuinely adds leverage — and where it doesn’t