Ask AI as an executive assistant or management consultant
K
Keith Besherse
Ask AI as an executive VP rather than as an entry-level receptionist.
Right now, many of the proposed agents feel like entry-level roles (receptionist, junior marketer, task executor). That’s useful; but I’m more interested in Ask AI eventually functioning like a chief of staff / executive VP rather than a frontline assistant.
The mental model I’m using is the solo or very small business owner, the person who is simultaneously the owner, operator, foreman, and salesperson. They are so busy serving customers that they rarely have time to step back and think about the business itself, let alone analyze data.
We often tell business owners to “know your numbers,” but that advice assumes they:
> Know which numbers matter
> Have time to analyze them
> Know what “good” looks like
Many don’t; not because they’re incapable, but because they’re overloaded.
Thoughts on the poll options:
CRM Agent:
I hear “CRM Agent,” I imagine a receptionist. That may be valuable - but only if the objectives, authority, and guardrails are clearly defined.
What guidance is the agent operating under? What does “success” look like? Is it doing something new, or just executing workflows differently?
Users who vote for this signals pain points I don’t personally experience - not that the idea is wrong.
Email Agent (outbound):
I had a chance to look at the Email AI beta. I’m only marginally interested in generating “beautiful” marketing emails; as a recipient, I usually ignore them because they’re obviously not personal.
However, if “running campaigns” means:
> Monitoring engagement
> Adjusting strategy mid-stream
> Knowing when to stop sending
…then that becomes more interesting.
An Email Agent as a content strategy implementation specialist, not just a writer, is compelling.
Content Agent:
Adding blogs to the current Content AI makes sense. But the real opportunity, in my view, is a master content strategist that plans a quarterly narrative and then uses sub-agents (social, email, blog) to execute a cohesive, audience-aware, cross-platform message.
If it’s just writing content, that’s mildly interesting.
If it’s orchestrating an on-brand, culturally relevant, omni-channel strategy — that’s very interesting.
Support Agent:
This is the biggest immediate gap from what I’ve seen so far.
A support agent needs to:
> Understand HighLevel’s limitations
> Know when to say “I need to hand this to human support”
> Assume users have low technical literacy
If this is ever rolled out to client accounts (not just agencies), those constraints matter.
A support agent that can check inventory, shipping schedules, or account state would be valuable. A support agent that confidently gives wrong answers is worse than no agent.
Additional use cases:
Inbound Email / Mailroom Agent:
Most AI discussions focus on outbound. Historically, businesses also had mailrooms and executive assistants who triaged inbound communication.
HighLevel still struggles here. For example, the “Customer Replied” trigger doesn’t actually detect new inbound emails properly and can’t evaluate headers (sender, recipient, or subject).
An inbound triage agent would solve a longstanding platform pain point.
Account Analyst Agent:
For agencies, this would function like a junior account strategist:
> Evaluating KPIs across campaigns and channels
> Spotting underperformance or drop-offs early
> Highlighting opportunities the client may not see
> Prompting proactive, data-backed conversations with clients
For Service businesses:
Imagine a small home services company (plumber, roofer, HVAC) running ads, answering calls, and sending follow-ups through HighLevel. But then acting as a customer service representative responding to queries and evaluating sentiment, shifting priorities, and advising the owner if special care or attention is needed. An experienced sales rep, not just an order taker.
Instead of the agency reacting when the client complains, the agent flags issues early and frames the conversation:
“Here’s what’s changing, here’s why it matters, and here are two options to correct course.”
This turns account management from reactive support into decision support, which is where agencies deliver value.
Decision Support Agent
More broadly, this is about helping business owners see the forest instead of getting buried in the weeds.
An agent that evaluates trends:
> Sales
> Calls
> Content
> Inventory
…and then interprets what that means would be enormously valuable for busy operators.
The core idea
At a higher level, I’m less interested in Ask AI as a task doer (though those sub-agents are necessary) and more interested in Ask AI as a business analyst, consultant, and auditor.
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K
Keith Besherse
So much of a company’s activity already flows through The Platform. Helping owners interpret that data (not just execute tasks) feels like where the real long-term value is.
In the military world I come from, a commander is supported by a full staff: operations, intelligence, logistics, personnel, plans, communications, training, finance, and public affairs. In small business, all of that responsibility collapses onto one person — without the staff.
Ask AI could become that staff!
Account Analyst Agent vs. Decision Support Agent
(Why these are different — and why both matter)
K
Keith Besherse
Account Analyst Agent
Scope: Account-level performance
Primary user: Agency owners, account managers, client-facing teams
Time horizon: Tactical → short-term (weeks to a quarter)
The Account Analyst Agent functions like a junior account strategist whose job is to answer:
“Is this account performing the way it should be — and if not, where is it breaking down?”
Core responsibilities:
Monitor KPIs tied to marketing execution (ads, calls, forms, bookings, follow-ups)
Detect underperformance or regressions early
Compare actual results against expected baselines
Surface actionable insights within the context of a specific client account
Prompt proactive conversations before clients feel pain
An Account Analyst Agent could surface insights like:
“Call volume is steady, but booking rate has dropped 18% in the last 30 days.”
“Most missed opportunities are happening after-hours — consider call routing or voicemail automation.”
“Your Google Ads are driving calls, but those leads are converting at half the rate of referral traffic.”
“You’re spending more on ads, but revenue per booked job is declining.”
Service business example:
A local HVAC company is running Google Ads and SMS follow-ups.
The Account Analyst Agent might flag:
“Lead volume is stable, but booked jobs are down 22%.”
“Calls from ads convert at half the rate of calls from Google Business Profile.”
“Missed calls increased after 5pm — revenue leakage is likely operational, not marketing.”
This agent helps the agency say:
“Here’s what’s happening in your account, and here’s where to intervene.”
K
Keith Besherse
Decision Support Agent
Scope: Business-wide health and direction
Primary user: Business owners and operators
Time horizon: Strategic → medium-term (quarters to a year)
The Decision Support Agent functions more like a business analyst or trusted advisor. Its job is to answer:
“What does all this activity actually mean for the business?”
Core responsibilities:
Synthesize data across systems (sales, calls, marketing, inventory, capacity, seasonality)
Identify patterns, trends, and second-order effects
Highlight trade-offs and risks
Help owners prioritize decisions when everything feels urgent
Translate raw metrics into judgment support
Service business example:
The same HVAC owner might hear:
“Revenue is up, but margin per job is declining.”
“Marketing is working, but technician capacity is becoming the constraint.”
“You’re spending more to acquire customers than you were six months ago, but customer lifetime value hasn’t increased.”
“Based on seasonality and current booking trends, cash flow will tighten in 60–90 days unless pricing or capacity changes.”
This agent helps the owner say:
“Now I understand what matters next.”
K
Keith Besherse
The Key Difference (One Line)
Account Analyst Agent helps you manage accounts and execution.
Decision Support Agent helps you manage the business.
They overlap in data, but not in purpose.
One answers:
“How is this account performing?”
The other answers:
“What should I do, given everything that’s happening?”
Why This Matters for Ask AI’s Future
If Ask AI only executes tasks, it saves time.
If Ask AI interprets outcomes, it saves bad decisions.
Long-term, the real leverage isn’t more automation; it’s better judgment, at scale, for owners who don’t have time to think.
That’s the difference between:
An AI assistant
And an AI staff
Again, I’m thinking in terms of what’s possible, not what should ship immediately. Happy to clarify or expand if helpful.
I’m not thinking in terms of what should ship next quarter. I’m thinking more along the lines of what Ask AI could reasonably become over the next 12–18 months if we treat it as a core capability rather than a collection of task automations.
K
Keith Besherse
For the Mailroom Agent:
- Mailroom AI to triage and sort emails (prioritization & catagorization).
- Conversation AI to draft email replies.