most founders I talk to want to know the same thing - “is my business ready for AI?” whenever I get that question, I don’t even talk about AI. I ask them how their business is running right now. where is your data? are your processes documented or do they live in someone’s head? is your team spending their days on tasks that actually move the needle?
readiness is more an operations question than a tech question. the companies that are most ready for AI don’t need to be the most technical but they do need to run a smart operation.
processes live in people’s heads
the most common thing I see when I start working with a company is that the process I’m building on doesn’t actually exist anywhere. it lives in someone’s head. the ops manager, administrator, or the founder. somebody knows the process and they just train new people on that as they come in and it mostly works. but things fall through the cracks, sometimes steps get missed in training or just aren’t done the “right” way.
I worked with a company where the entire onboarding process for new clients was just a memorized sequence. there was no system tracking it, no checklists, just experience and memory. clients would sometimes get email updates, sometimes they wouldn’t. documents would go out on random schedules and never get followed up on. client experience varied so much because the system wasn’t real.
when we mapped out the process, steps kept getting added after the fact because the team would totally forget about them. the process was actually a lot more complex than they even realized because no one had ever taken the time to articulate it. this matters because AI lives and dies by the instructions you give it. if you hand AI a well documented and detailed process it can follow, improve and run parts of it for you. if you give it nothing or a half-remembered version of process, you will get a generic and unreliable tools that misses the steps your team used to memorize and handle.
it’s like hiring someone with no training. they might figure out the basics but they’ll miss the context, the exceptions, the why behind each step. AI without documented process works the same way. giving specific and detailed inputs will give you useful outputs. without the foundation you’re setting up for failure. your team may even lose faith in AI and once your team decides AI doesn’t work, good luck getting them to try again.
before you think about AI, ask yourself: could a new team member follow our core processes from documentation alone? if this answer is no, here is your starting point. real process.
your data is storage and not a tool
data is an important part of integrating AI. naturally, AI can only learn from data that was designed to teach you something in the first place. so how does your data look at the moment? a lot of companies have been built on excel sheets and usually pretty simple ones. most of them start with good intentions, lots of data points and variables to track. but over time recording gets sloppy and the result is half completed data that really doesn’t give much to go on. to be ready for AI means having your data consistently recorded with good detail.
a company I worked with was an example of tracking good data. they were disciplined in keeping their inventory sheet in top condition. they recorded every small part of the transaction, details of when stock was brought in and when it was sold. when milo works came to build in AI to their system we had a great data set. our system was able to take the existing data, understand their sales cycles and as a result make high certainty decisions on when to order inventory in the future. this system saved hours of planning and analysis but it only worked due to the data it was built on.
how is your data being recorded at the moment? is there intention behind the inputs? if no one can use your data now, then, it doesn’t matter how much you have. you may find data to be a sticking point on integrating AI. the best time to start collecting good data was years ago and the second best time is now - you will need this.
what is your real work to boring work ratio
when a business owner tells me they feel like they should be getting more out of the day, it’s usually not because the team isn’t busy. it’s because the work getting done doesn’t feel like it’s moving the business forward. everyone’s working hard but nobody feels like they accomplished anything by the end of it.
I worked in financial services early in my career where this was the reality. for every hour spent meeting a client we would need two behind the scenes to orchestrate the deal. between spending time prepping for meetings, saving data in our systems, doing paperwork, following up etc. it felt ridiculous. none of it was heavy lifting, it was just moving data from one spot to another. constantly. the days of paperwork never felt like wins and your team feels the same.
every business owner wants to energize and inspire their team. the manual repetitive work is draining though. and definitely not why they came to work there in the first place. supporting your team means giving them the freedom to think and make impact.
the instinct when things feel slow is usually to hire. it has been like this for many years. more people equals more capacity and problems solved. but today we have the technology to get significantly more from our teams. AI and automation can take the repetitive manual work off your team’s plate and give them more time to focus on work that grows the business. you don’t always need more people. but you do need to stop wasting the people you have on work that good systems could handle.
if you’ve tried automation before and it didn’t stick, that’s actually a good sign
when a company tells me they already tried to automate something and it didn’t work out, I’m honestly more excited than if they’d never tried at all. it shows some initiative and it shows their team understands that there is value in new systems. most importantly, it gives us something to dig into. a failed attempt isn’t a dead end but part of the roadmap.
usually this is what happened. someone got a zapier account or something similar. they found a spot in the business where it looked like it could plug in. they plugged it in and it sorta worked but not enough for anyone to trust it. so the team stopped using it and went back to the old way. now the leadership is skeptical and the team thinks automation is more work than its worth.
the problem was likely not the tool. the problem was not stepping back and understanding the process before trying to automate it. they automated for the sake of it. it’s similar to collecting data without intention. it feels productive but it doesn’t go anywhere.
where you automate in your business matters just as much as whether you automate at all. some processes have many edge cases and make more sense to have humans involved. if you force automation into those spots you will find your team spending more time babysitting the system and that is worse than just doing it manually. the best automations are predictable, repetitive and no judgement needed jobs.
if you tried something before and it fell apart, don’t write off the idea. look at what you tried and ask why it failed. was it the wrong process? was the process not documented well enough for a tool to follow it? a company that failed at automation and learned from it is closer to being ready than a company that’s never thought about it at all.
your team doesn’t need to be excited about AI but leadership needs to be in the room
if you brought up AI in a meeting and half your team looked nervous, that’s not a dealbreaker. most people aren’t against AI specifically. they just don’t understand what it means for them yet. some are worried it replaces their job. others just don’t see the point. that’s normal and can be worked with.
what’s not easily fixable is leadership that isn’t bought in. change in a company comes from the top and if the people running the business treat AI as some IT project they’re funding from a distance, it will stall. your team takes cues from leadership. if management can’t confidently explain why the company is investing in this and what it means for the people doing the work then nobody can carry it forward.
the most ready companies I work with have two things. firstly - leadership that genuinely understands why AI matters for their business use cases. not for any reason other than solving a real problem in their own business. secondly - they have at least one person on the team that is curious (some companies I have worked with have a task force already). someone who’s been reading about AI, tried tools or heard stories. that person will be vital in your transformation, your AI champion. they’re the one who translates the vision into something the rest of the team can see. they bridge the gap between what leadership wants and what the team experiences day to day.
you don’t need every person in the building to be excited about AI. you need leadership that’s willing to lead the change and one person who can champion it. if you have that, the rest of the team will come along once they see real results. if you don’t, that’s not a reason to abandon the idea. it’s a reason to start with the people at the top and build understanding before you build systems.
no company checks every box
if you read through all of this and feel like you’re only hitting two out of five, that’s okay. it doesn’t mean AI isn’t for you. it means you know where to start. readiness is about a foundation you can build towards. some companies need to start with documenting processes. others have great processes but their data isn’t there yet. some have everything in place operationally but leadership hasn’t bought in. the point isn’t to have it all figured out before you begin. the point is to understand what the pieces are so you’re building on something solid and these pieces work together. you can have the perfect data and a great system built but if your team isn’t going to use it then it doesn’t matter. you can have the most eager team in the world but if the data doesn’t educate the system then the system isn’t any good. every piece supports the others. that’s what makes it a foundation.
if you feel behind because every company seems to be talking about AI right now, here’s the reality. most of them aren’t ready either. a lot of businesses are forcing AI into places it doesn’t belong and we’re seeing the results. abandoned projects, wasted budgets, teams that lost faith in the whole idea. you’re not in a race. we are still early and there is still so much opportunity.
the close
if you do things right you only really have to do them once. get the foundations in place: your processes, your data, your team, your leadership and then you’re not just ready for one AI project. you’re in a position to keep building. the companies that take the time to get this right now are the ones that won’t have to start over later.