Suhel Shaikh | AI Automation

I design & deploy AI automation for business processes - sales ops, reporting, support, finance. Human approval built in. DM 'audit' for a free process review.

[Suhel Shaikh | AI Automation @suhelbuilds]

most companies don't need "more AI tools". they need one painful process that runs itself.

that's what i do: i design and deploy AI automation for business processes. sales ops, reporting, support, finance.

how it works:
1. map the process as it really runs, exceptions included
2. build the agent inside the tools you already use
3. a human approves anything risky
4. it runs, and i measure hours saved

example: inbound lead → enriched → routed → follow-up drafted → approved on telegram. 2 days → ~3 minutes.

got a process that eats your team's week? DM me "audit".

[Suhel Shaikh | AI Automation @suhelbuilds]

@aakashgupta "memory, approvals and scope" is the right list. for a clinic chasing missed payments, approvals matter most: let the agent draft the reminder, but have a person okay the first money message to any patient. once the drafts stop needing edits, loosen it

[Suhel Shaikh | AI Automation @suhelbuilds]

@wadefoster @zapier #1 is the one ops teams should care about. if the steps that don't need AI run as plain code, you get the same result every time and only the judgment calls can vary. curious how the self-fix decides what counts as a "bigger change"

[Suhel Shaikh | AI Automation @suhelbuilds]

G2 surveyed 1,000+ software buyers on AI agents:
- 66% have agents in production
- 31% say staff spend 6+ hrs/week checking agent work
- 45% say fixing agent mistakes eats 25%+ of the gains

that's the "distrust tax". the fix isn't checking less, it's checking only what's risky.

[Suhel Shaikh | AI Automation @suhelbuilds]

@freightcaviar the 4:45 quote is the real test. revenue per head goes up when software runs the loads that go fine and hands the missing POD or the gate call to one person with the whole history already on screen. not when it tries to handle those too

[Suhel Shaikh | AI Automation @suhelbuilds]

~60% of the AI risks one security startup finds come from apps built by non-developers (via TechCrunch). finance teams top the list. developers are 4th.

if your team builds its own AI tools, check:
1. can outsiders reach it?
2. whose login does it use?
3. what data can it read?

[Suhel Shaikh | AI Automation @suhelbuilds]

@mardehaym starting with appeals because the data was reachable and the value easy to measure is the call most teams get wrong. they go after the most valuable process first, then spend three months arguing about whether it worked

[Suhel Shaikh | AI Automation @suhelbuilds]

@freightcaviar a five-minute repost is the kind of thing a shipper or broker could catch automatically. match every load you tender against public board postings on the same lane, pickup date and weight, and a re-posted load shows up before it moves, not after the claim

[Suhel Shaikh | AI Automation @suhelbuilds]

AI agents can now run for days, inside your email, CRM and ERP.

before you switch one on, answer 3 questions:
1. what can it do without asking?
2. who approves the rest?
3. where is every action logged?

if you can't answer all 3, it's not ready for real work.

[Suhel Shaikh | AI Automation @suhelbuilds]

@tarush_agarwal_ point 4 is the one that matters for booking calls. the voice can be perfect and still lose the appointment if it reads back "tuesday the 14th at 3" in a way the caller half hears. confirming dates and times is worth its own test set

[Suhel Shaikh | AI Automation @suhelbuilds]

@iliasconfidency agent failures, but specifically the silent ones. a risky payment usually has someone watching anyway. an agent that quietly stops processing invoices on friday afternoon is the one nobody notices until monday

[Suhel Shaikh | AI Automation @suhelbuilds]

google, microsoft and cisco all pushed AI agents deeper into work tools this week.

the tools aren't the bottleneck anymore. most companies still use AI to save one person 20 minutes, not to run a process like order entry or claims follow-up.

pick one process, not one tool

[Suhel Shaikh | AI Automation @suhelbuilds]

@IIoT_World how are plants handling the audit side of this? if software restarts a line, the plant manager will want to know who approved it and why, and most historians weren't built to log AI decisions next to operator ones

[Suhel Shaikh | AI Automation @suhelbuilds]

@FreightWaves drivers who push back hardest are usually the ones who lived through a camera rollout that was really about discipline. sharing the savings changes that, but only if the first payout lands within a quarter, not a year later

[Suhel Shaikh | AI Automation @suhelbuilds]

@flxrnc Thanking you now!

[Suhel Shaikh | AI Automation @suhelbuilds]

@flxrnc Damm Good

[Suhel Shaikh | AI Automation @suhelbuilds]

@jumperz Anthropic just made many startups
and skilled peoples less useful

[Suhel Shaikh | AI Automation @suhelbuilds]

@dan__rosenthal Interesting

[Suhel Shaikh | AI Automation @suhelbuilds]

@N01ennn Thanks, it would help

[Suhel Shaikh | AI Automation @suhelbuilds]

@jasonzhou1993 @treg_ai Good to know, everyday there is something new

[Suhel Shaikh | AI Automation @suhelbuilds]

@iliasconfidency "earned, not granted" is the right way to put it. what makes removing a gate easy later is logging every action the agent wanted to take while a human still approved it, so the decision is based on evidence, not gut feel