Pillar number two is the AI command center. This is arguably one of the most important decisions that a company is gonna make in this AI transformation journey. This is deciding if you're gonna go all in on Chatuchupti, on Copilot, on Claude. Not making this decision is the equivalent of not caring whether your company and employees use Apple Mail, Gmail, Outlook. It'd be crazy and cause chaos. And there's no doubt in my mind that all of your employees are absolutely using these tools on their own, on a personal account, and high likelihood, putting a lot of company information into it. And so this causes a lot of risk. It's I talk to thirty, fifty companies a week, and it blows my mind how many people have not made this decision at this stage in the in their business. And I can tell you this. For thirty dollars a month, there it is gonna be the highest ROI within your business. The thirty dollar a month license for each of your employees, deploying that, setting up that infrastructure, deploying projects, it's just gonna be the best thing that you've ever done. What people don't realize about a lot of these command centers, ChatchBT, Copilot, Claude, is that they are filled with features that are going unused. So very similar, we look in companies, and if I audit a company around their Salesforce, most likely they're using less than ten percent of what Salesforce has to offer. And so even the companies that have made the decision and have rolled out ChatGPT or Copilot aren't using ninety percent of the value of that tool. And so things agent mode, operator mode, ChatGPT actions, Claude projects, ChatGPT projects, custom GBTs, Canvas mode for document creation. These tools offer so many robust features that can unbelievably enhance the productivity within your company, and most companies haven't even gotten the license out to their teams. And so it's absolute chaos and it drives me crazy, but this thirty dollar a month license per person in your company might just nail the absolute highest ROI that you've ever seen.

The third pillar is AI first culture shift. And believe it or not, this is a lot harder than people think. And so what this really means is it starts with an AI policy. How do you create a really clear AI policy for your company that everybody's on the same page? Secondarily, communication of the AI strategy. So that's advising a lot of times clients on how should the CEO be talking about AI. And why that's critical is we've surveyed hundreds of companies where we talk to their C suite. Now we ask them, how does your team feel about AI? Are employees excited? And then we do the same thing with their team all the way through the org. And I'll tell you, it is a huge gap. And leadership thinks one thing, but there's a lot of fear within employees in the organizations when it comes to AI. They're afraid, is it going to replace my job? People are afraid of change in general. All these different things that make it really tough. The other thing when it comes to an AI first culture is very, very rarely is your AI strategy. And as you start integrating this technology, is it gonna snap into your existing process? There is gonna be substantial change management of the way that your team operates and does business is going to have to change. And they're gonna have to adapt the way they do stuff to work through this AI system and to realize the benefit. And so this culture is really critical because what we've seen in the most successful AI transformations of companies is the team needs to be very involved. And to some extent, once you find a big business opportunity and you're solutioning against it, you need to make sure that those users that are gonna be implementing it, that it's their strategy, whether that's incepting it into their head, whether it's getting them comfortable with that, whether it's having to be part of that process. But I can't express enough how much work it takes to build that confidence and to train them and to get them excited and how critical that is. If you don't have that, you are not going to be successful with AI, period, even if you do all these other things really, really well.

So the fourth pillar is the AI enabled tech stack. And what does that mean to you? There's two main components of this. One is understanding the existing API access that we're gonna have. All of your company data lives inside of your tech stack, and pretty much every company I talk to has fragmented technology that isn't integrated and is not talking to each other. And so with the existence of APIs and MCPs, this allows us to push and pull data. And so in order for us to achieve any of the AI things that we wanna do, we need to know that can an agent go in, access the data? Let's say it's your CRM or your ERP or even your internal communications platform. If we have an agent, we wanna deploy it in. The question is, are they going to be able to get access to that? We've looked at clients where it's incredibly friendly, and we have some clients where they have big AI dreams, but their core ERP tech stack doesn't have an API, and so everything we wanna do cannot do it. The second pillar of the AI can enable tech stack is ensuring and unpacking the AI features that your tool might have. And so ultimately what we'll do is go into your CRM, go into your ERP, Salesforce, for example, and instead of you looking for an extra third party AI tool, you may have that feature unlocked in your current CRM or your current ERP. So not only do we go and make sure the API access around your current tech stack is gonna be friendly in the world of AI, Then we look in your current tools and try to save money and prevent unneeded tool purchases by unpacking what are the AI features on the roadmap of the current tools that you have, because a lot of the things that you might want to accomplish might you might be able to do in your current tech stack.

So pillar number five is AI healthy data. Right? And as we're going through our process and all of the pillars, number four, we're looking at technology. And throughout all of them, we're getting a deep look into a business's people, workflow, processes, and technology. All of that creates a work off of data, just like AI. And you might have heard the phrase garbage in garbage out. That applies to humans or to AI. If you have data that's unstructured, it's messy, it's all over the place, it's difficult for a human to look at and reason about. It's difficult for a human to search your SharePoint and go and find the files or the documents you're looking for. Same thing with AI. AI can reason about much more information at a time, but if it's messy, it's still difficult for it to go in and grab and then summarize for you or do something with. And so when we look at all of this, we want to understand where is data being created, where is it being transformed or manipulated, where is it going, and how clean is it.

Pillar number six is AI agent readiness. We are moving into a world where agents are just going to be a part of every organization. And so think of these agents as virtual workers or digital employees. They're going to sit inside your organization, taking context, running tasks, executing against vision. And so what we do is we map out which agents are gonna be most impactful for your business. We unpack the SOPs and the workflows that that agent is gonna have to follow, and we make sure that the infrastructure is gonna be friendly for those agents. So you really have to think of it as digital worker. So if you ask an agent to do a task, I want you to get this information from the CRM, create this email, and then send this document, maybe a sales contract out to a a partner. We need to ensure what is the process that that agent is gonna go through. Does it have access to all the systems? Does it know where to get that information? When it creates that document, is there a company template that it's gonna use? Really needs to understand what we like and what we don't like inside the organization, and then unpack the expectations. Who is gonna actually monitor if this is successful or unsuccessful? So just like your, your human employees, these agents are gonna need weekly check ins. They're gonna be need monthly reviews. And just the same as a human employee, six months in, that agent is gonna be way, way better than it is on month one. And so the training, the feedback, the process improvement, all those things need to happen in order to ensure success with AI agents. And so that's what we do in pillar six.

Pillar number seven, departmental deep dives. This is us getting in deep with each department or business function, really understanding like what is that team doing? What is that function? What does that look like? And as we go in there, we understand the people and the process and the technology. We're looking for areas where AI is going to be a great fit for the job, where it might be a great fit for that job six months from now, twelve months from now, or it's such a repetitive, mundane, kind of fixed process that it's more for traditional automation or RPA. And when we find those opportunities, whether it's traditional automation, it's an AI workflow, agentic AI or some piece of software, we're looking to see how can we leverage those tools to help these teams do more with less. Right? So how can we, instead of hiring two sales engineers, how can we still get that same output with the team that we currently have? And maybe we can also allow people to do less of the tedious work that detracts energy from them and allow them to do the things that they love to do, that they're specialists in, they're experts in, the high value strategic work that really gets people energized.

The eighth pillar and really the final step to getting really clear on your strategy and this initial strategy phase before you start really hammering nails and turning screws is your three year AI vision. And, know, look, for a lot of clients we may end up going with a two year AI vision. But really what it is is a longer term vision of what is our dream state for our company. Based on where we see AI today and where it's going, how do we envision our company in the future being fully AI enabled, the most scalable, efficient company that it can be in our category? And until there's clarity and aspirational dreams on that, you're just aimlessly executing. And so that is really critical because then it allows us to socialize that in the company. It allows companies to share that with their board and their board to wrap their head around where they're going. And it allows month six, year one, year two to be laddering up to a bigger vision and for you to be able able to really tell, am I on track towards that vision? And am I making good progress? And without that, it's very, hard to judge yourself. It's the same reason why every company has a a forecast and creates a budget for the year. Because without that plan, how do you know if you're doing well or not? So that's a really critical thing and this is something that CADRE has done with many, many clients, really helping them build that blueprint, that roadmap so that everybody is really clear on where the company's going and company has big aspirations. And some of those things, the technology is not there. And it allows us to then track the technology and as it gets to that point know, okay, now AI fits into our vision in this way and we're ready to do so.