All posts by : Mason Whitaker

So how do you evaluate AI readiness within an organization? It's difficult. It's honestly very challenging to figure out if your company is gonna be ready to tackle something as big and hairy and scary as as AI is. And you can do this pretty methodically. You can look at this through three different lenses. The first being people, the second being process, and then the third being technology. And you have to look at this in that order. It's important. I'll get to why. You wanna start by looking at your people. Do you have your teams organized in a way that is intelligent? Do you have the structures of their job responsibilities and their job descriptions very clearly outlined? Do you know what your people are actually doing? And are they actually ready for a change like introducing AI into their business process? A lot of organizations, they are used to doing things the way that they've always done them, whether that's paper based or manual or, you know, maybe done in just an electronic fashion. Maybe you're a little bit more modern and tech savvy business owner. You have to take a hard look at your people and understand what's gonna be the lift from the change management side of things for this this project of implementing AI. Because implementing AI really is a project. It's it's no different than implementing any other system as you would have previously. And McKinsey has published a research paper that says that seventy percent of change management programs fail to ever go live, specifically system implementations, not because of the technology, but purely because of people adoption on the client side. So you have to take a hard look at your people, and you have to understand what are their current skill sets, what are their capabilities. You have to map out individual plans for each of your different departments of trying to level them up and get them ready for this change. So coming up with a plan and addressing each of the individual skill sets is gonna go a really long way. Also identifying within your people who the champions are gonna be is really important. It's not just gonna be you as the business owner or the CIO or IT director that's gonna be pushing this throughout the organization, you're gonna want people that are on your team that are excited about this technology that they can drive this through the rest of the organization. So identifying those champions up front, getting them really excited about the technology, showing them proof of concepts, and things like that, it's it's gonna go a long way as well. And you wanna look at how ready those people are as a measure of your evaluation if you're ready for AI or not. The second aspect is gonna be on the process. Within every single business, there is a process that you go through to perform something to be able to have an order come in and then collect cash in the end, or to be able to have a service performed and then cash collect At the end of the day, you can break down any business into a series of processes. And how well defined you have those processes, that's really gonna determine how ready you are to adopt AI. If you just have Janet who works at your company that she knows everything in the business and she essentially is your repository of processes, it's gonna be very difficult for you to apply AI to that scenario. So you wanna make sure that you have things documented across standard operating procedures of, you know, when this happens, then I need this to happen. So triggers and actions across your entire business. Getting that very clearly outlined from the offset, that's gonna enable you to springboard your AI usage because you're gonna be able to tell the AI exactly what you need to do along the entire way. And a recent MIT study came out that shows that ninety five percent of AI projects are failing to meet expectations of customers, which is pretty dramatic. So having these processes fairly clearly defined and written out is gonna be a huge enabler of success for you with these these AI implementations. And then the last thing that you wanna look at in all of this is the technology, and that's both the data and the system side of things that you wanna be analyzing. And starting with the data, if you're not capturing data in some sort of system of record or some area, like, if you're not you know, even if it's, putting things in filing cabinets, at least there's data there somewhere that you can capture capture and scan in with OCR and things like that. But if you're not capturing data on your business, then how do you expect AI to make decisions or perform processes based on data? It's just not gonna be possible. IBM estimates that bad data cost businesses three point one trillion dollars per year. So what you wanna do is you wanna look at those areas of where you have data in your business. Do you have clean data? Do you have reliable data? Like, what's the integrity of that data? If you can't trust it, then you're not gonna trust the AI then either. And so you wanna make sure you have a solid framework of your data and that you're collecting these things and putting it into a a manner that is reliable and accessible. Accessible. The other side of things is the system. You wanna have transactional systems that are accessible by modern AI applications, meaning that they need to be cloud enabled or AI enabled. So that way these AI tools can hook in and be able to understand what's going on within the system, perform actions on your behalf inside of the system, or do inquiry down into those systems to pull things out. If you have a system which is maybe just paper based, you're literally on a ledger, you know, writing out what your chart of accounts or your financial reports are, AI is not gonna be able to adjust that information or perform actions on your behalf. It's not gonna pick up a pen and and write down the ledger for you. You need to have a system that is cloud enabled or has modern accessibility into it. So looking at things like modern platforms like Microsoft or within, you know, any any modern application really is gonna have these API accessible features. And so you wanna look at it in this way. You wanna start with the people. You wanna go look at your process, and then you wanna look at the technology. And you can look at all three of these main categories as a score and create scorecards across each of how ready you are. And your goal should be able to max out that score. So you should have your people who are excited about the change. You have your power users or your champions identified. You have your organization really mapped out in terms of, like, your org chart, your job descriptions, what you guys do that is all clearly defined. And then within your processes, standard operating procedures across all of your different departments. So what are all those people actually doing, and how can you do this on repeat, those triggers and those actions across your entire business. And then lastly, all your technologies, so the data and the system side of things, how accessible is that data? Are you capturing all that data, ranking that within a scorecard? And then the same thing on the system side, how accessible are those systems? Are those systems about to go end of life, and are they no longer gonna be accessible by AI? You wanna be mapping those things out as well. All of this is really gonna give you a score on how ready you are for AI. And doing this now is gonna set you up for a massive scaling foundation for the future, scalable foundation. You're gonna be able to take advantage of these tools much faster. AI implementation is actually really fast when you have all of these things figured out. When you don't have all these things figured out, it's the same thing as previous system implementations where you gotta figure out all of those things so then you can add in the new system. So I'm excited for you to take advantage of it and follow for more tips.

Microsoft just made a five billion dollar bet that OpenAI alone is not enough. And honestly, that should tell you where the AI market is heading more than anything else that's gone on this year. And here's what most people back in January, Anthropic released Quad Cowork. In one single day, two eighty five billion dollars were evaporated from the software market, and Microsoft took a hit of nine percent on its stock price. That wasn't just a blip in the market. That's a signal where things are going. So what did Microsoft do? They didn't panic, but rather they looked to partner. They brought Claude more heavily in house and started diving into a deeper partnership with Anthropic. And now they've launched something called Copilot Cowork that I think is really gonna change the game for how every business runs with Microsoft three sixty five. And in this video, I'm gonna walk through exactly how that works, what happened, and how you can take advantage of it. So let's get into it. So here was the January wake up call. So let's set the scene. January twenty twenty six, Anthropic, the company behind Claude AI releases a product called Claude Cowork. It's a standalone AI agent that can automate processes within your computer and within your applications that you have connected to it. Pretty amazing. This is an AI that's not just inquiry and response, but it's rather it's actually understanding your context, your business context, reading documents, researching things, and then going and performing things on your behalf, like sending emails or adding records to your CRM. The market reaction was pretty immediate. Dollars two eighty five billion gets wiped away, Microsoft stock drops by nine percent, and people realize that this thing is doing real work. Now here's why this matters to you, even if you're a two hundred percent company and you're not just trading tech stocks. The AI model landscape is changing so fast. The company that you're building your tech stack around is making strategic bets that will affect your company for decades to come. If your ERP vendor, cloud provider, software provider is making the wrong moves today, then that becomes your problem now. What happened in January to Microsoft was pretty alarming, but it should tell you everything you need to know about how the market is going to be moving forward. Okay, so what is CoPilot CoWork? Well, Anthropic released Claude CoWork. It allows you to actually do tasks, hook up your computer and all your applications to perform real actions and real work. But Copilot Cowork now takes all that same capability but embeds it on top of Microsoft three sixty five. So all your apps like Teams, Word, PowerPoint, your OneDrive documents now are all able to be accessed by this co work tool. So you can set up recurring jobs or recurring triggers to automate functions in your business that never were possible before. And this all uses a concept called WorkIQ. WorkIQ, other people know it as the access to the Graph API, as it used to be called. But WorkIQ is the context layer of your organization that sits around Microsoft three sixty five. So it's all the Teams chats, the emails, the contents or contacts that you have and has access to all of that. Now, Cowork that's on top of that can reason over that context of all the meeting recordings of all the Teams messages, emails that you have and be able to perform things on your behalf. So whether that's creating daily recurring tasks to automate notes, getting added to a CRM based on conversations that you're having, or more complex work like outputting full scale deliverables and documents based on just conversations and triggering in Teams messages. Or recurring jobs that you want to have every day, something that happens that's automating a Teams message or giving you a news briefing of the exact details of what's going on within different departments. Really, the options are now endless with Copilot CoWork. One of the great things about it is that it's secure. So QuadCowork is a research preview tool that you have where it's pretty open ended and you can almost do anything and there's lots of areas for security vulnerabilities. Copilot CoWork is built on the Microsoft stack and meant to be secure from its bones. So what you should do today as a business leader is audit the amount of work that's going on within the Microsoft three sixty five stack. So what's happening in Teams, in SharePoint, in Word, in PowerPoint, Excel, and understand where work is happening. If you're having about eighty percent or more of that work that's happening within the Microsoft three sixty five stack, then Copilot co work is gonna be tremendously impactful for your organization. Now let's talk about the partnerships that go into all of this behind the scenes. In November twenty twenty five, Microsoft, Nvidia, and Anthropic entered into a three way partnership together. Anthropic committed thirty billion dollars towards Microsoft, billion with a B in Azure compute resources. And then Microsoft in turn invested five billion dollars into Anthropic. And Nvidia made a commitment to invest up to ten dollars bn into the latest compute and the latest hardware. So this is pretty incredible. You have an AI front leading company with Anthropic. You have Microsoft as the context, the business context and software engine for powering ninety five percent of Fortune five hundred companies. And you have NVIDIA who has ninety seven percent share of the GPU market today, all going into a partnership together. Pretty astounding what's possible when those three team up. So what does this really mean in practical terms? Well, Claude is now the de facto standard for AI models across the entire Microsoft stack and the NVIDIA stack. And so you have Claude's Opus four point six, the Sonnet and Haiku models embedded throughout all of the Microsoft set of products. What originally was GPT models now is being replaced in most cases with the Opus and Sana and Haiku models. So whenever using Copilot tools across the M365 ecosystem or using tools like CoPilot Studio, you now have the Anthropic models that are available there and they become really more of the de facto standard. In most interactions that we have with these AI agents, we're setting the Anthropic models as the default because it's producing better results today than the GPT models. So what this really means is that Microsoft is being abstracted away or agnostic to the AI models themselves, letting them advance as fast as they can while they operate more as the context layer and the engine orchestrating all the different AI agents that are out there. And this is important for you as a business leader to understand that when you're selecting Microsoft as a platform, you're not actually selecting OpenAI or Anthropic, you're selecting the ability to choose between whichever one is going to be best for that given scenario. I like to think of this as an airplane and an airport. The airplanes are the AI models that are getting faster, they're getting stronger, they can go from point A to point B very quickly, and more efficiently in terms of fuel. That's like the token cost for to accomplish, an AI model to accomplish a given task. But those airplanes are never gonna be able to land safely or manage themselves without an airport. And Microsoft is really operating as the, the air traffic control, the runway, the ground infrastructure, the way to get people onto the planes. They're the ones that are really setting up the stage for the airplanes to go as fast as they can and for things to be organized in a structured way. So Microsoft wants to be the platform and let these AI companies iterate and move very fast and allow people to take advantage of those while doing it within the safety and the efficiency of having a well run airport. And don't just think that Anthropic and OpenAI are the only models that are available out there. If you go look today with an Azure Foundry, there's gonna be more than twelve thousand models that are available to choose from. So Microsoft is really adopting the strategy of being the platform and letting you take advantage of whatever the best model is for your given scenario. So why does this matter for you as a small to mid sized business? Well, here's the thing. You already have the infrastructure in place if you're running on Microsoft three sixty five to take advantage of a lot of these tools. You don't have to go out and find an AI vendor. Instead, you already have it ingrained within the stack that you leverage and trust today. What you're going to find as you start to take advantage of more and more of these tools, that you're gonna wanna give it more and more context and more your business data. Great options out there with Dynamics three sixty five and the Power Platform to do that. And if you're running on Microsoft three sixty five today, you're already seeing that. Copilot is embedded across all the tools that you're using. You look up in the top right, you're gonna see that Copilot icon. And one of the great things is that they are updating the models underneath the hood, whether using the Anthropic models or the GPT models as the default, they're updating those as they go. So if you use the Copilot tools even just three or six months ago, give them another try. I promise you you're going to be surprised by what's now possible when using these tools. So this is the moment to pay attention here. You're already using these tools and you have access to them, but you just don't know the capabilities that now exist for you. And understanding those capabilities and taking advantage of them now creates real operational advantage versus others that aren't taking advantage of them. So think about that, let that settle in. You already have these tools at your disposal. Start learning how to use them and apply them and you'll be ahead of your competition. So what should business leaders be thinking of right now? Well, first I would say is governance. You want to make sure that you're locking down the use of these tools and you want to make sure that you have policies in place that don't allow for confidential or private data to get shared with these model companies that are being, you know, training based on the data that you give it. So building a policy out and enforcing the policy is key, but also the governance with the AI itself and setting evaluations against the agents that you're creating. So that way they're always reaching a certain benchmark and that way you're not giving out any bad agents or creating agents that are unreliant. And the second thing is model optionality. You don't want to go all in on one platform and be stuck based on what models they have available. Rather, you should invest in a platform like Microsoft that is going to allow you to have optionality and select different models. Azure Foundry has the most amount of models listed on it as any other platform that's out there, more than any other platform. Over twelve thousand models that are available. I was blown away when I first started diving in to how many options you have with model selection. So make sure to check that out. You'll see the governance framework in Azure Foundry as well. And the third thing is licensing. So looking at what you currently have from a license standpoint and your use of Microsoft because you likely already have these tools at your disposal. So doing a deep dive, understanding what's available out there, and then looking forward and seeing what's coming. Microsoft is releasing some new, SKUs like the E7 SKU that are going to bundle together lots of capabilities into a single license for your team to take advantage of. Microsoft is not just building an AI tool, it's actually building an AI platform. So a place where all of your agents can live regardless of the model that you're choosing or selecting. AI is moving from a thing that you ask questions and you get a response to actually running real actions in your business. And you're gonna need a full scale modern platform to be able to do that. So three main takeaways here. One, the AI model wars are becoming a game of distribution. Whoever has the most amount of access to users and platform become the winners. Not just who can go from point A to point B the fastest, but who can control all of the different movements of point A to B and C and D across your entire organization. Now that's real advantage when you put it on a platform. And the second piece is that AI is moving from inquiry and response to real action within your business. Copilot, co work and these tools are automating actual processes and performing full scale department functions using Teams, Word, PowerPoint, OneDrive, etcetera. And then lastly, the third thing is that business leaders who understand the capabilities that they have at their fingertips are gonna be able to create real operational advantage against those that don't understand what they have. So make sure you're doing an audit of what's available for you today and getting your platform prepared. Thanks for watching the video. If you liked this, then follow and subscribe for more actionable advice that you can take and adopt into your business. And if you want to watch another video, got one linked here and then also more information down in the description below. Thanks for watching.