How to Use AI for Enterprise Planning in 2026

95% of enterprise AI deployments fail. And we look at why the research points to the same root cause. The requirements are wrong before execution even starts. The problem is planning has never had a system. It's always been manual, fragmented, dependent upon whoever happens to be in the room. And that's because planning isn't deterministic. It requires reasoning. It requires holding context across dozens of stakeholders, asking intelligent follow-up questions. Adapting when things change. Software just couldn't do that until now. That's what's completely different about 2026. AI can finally handle the complexity that planning requires. I know because we've helped hundreds of teams plan this new way. So in this video, I'm gonna break down how to actually use AI for enterprise planning. I'll show you what the 5% of enterprises that implement AI successfully are doing differently and why the approach most companies are taking is fundamentally limited. Let's get into it. So why most companies are using AI wrong for planning. Here's what I see most enterprise teams doing right now. They've adopted AI, ChatGPT, Copilot, maybe some internal tools. They're using it to draft requirements faster, which is great. Summarize documents, generate content, and it feels like progress because things are moving quicker. But here's the problem. That's generative AI. Helps inside tasks. You prompt it, it responds. It makes you faster at the thing you are already doing, which is good, but the burden The burden of orchestration still stays on you. You're still tracking context manually, chasing stakeholders, managing documents, hoping nothing critical slips through the cracks. GenAI is like giving every project manager a faster pen. It doesn't change how planning works. It just speeds up pieces of a broken process. And that's why most organizations aren't seeing the results they expected. What Agentic AI actually changes. Agentic AI, on the other hand, is structurally different. It operates autonomously. It pursues goals. It coordinates work across teams. It maintains memory across conversations and stakeholders. Rather than waiting for a human to prompt it, an Agentic system asks questions on its own. It identifies context gaps. It recommends actions. It can execute workflows. It keeps context synchronized as things evolve. This is what planning has always needed. And the reason planning never had an operating system is because software couldn't, couldn't reason, couldn't hold context or ask intelligent follow-up questions. Planning fundamentally required judgment and under inherently uncertain conditions. And until now, no technology could do that. Agentic AI can. Here's a simple way to think about the difference. GenAI is like giving every project manager a faster pen. Agentic AI is like giving your organization a planning engine. What does AI-native planning actually look like? What does it look like in practice? It starts with getting the problem right. Most teams jump straight to solutions. That's the wrong approach. An agentic system starts with deeply exploring context and asking the uncomfortable questions first. What's the actual problem? What's, what's just a symptom? What does success look like before we build anything? Are we all aligned? Let me show you how we do that inside Force Equals, an agentic tool for enterprise planning. Welcome to Force Equals. Start by giving Force Equals 30 seconds worth of context on your project, and FourSquads AI will instantly automate hundreds of hours of work for you and your team. FourSquads will ask you a few questions to enhance the context. You can add as much or as little context as you have. You can add context through documentation that you already have just by uploading it. And when you're done, generate details. Draft project plan is created organizing the information that you've input, and you create the first project. That's it. That's all it takes to get started. Add or upload as much or as little as you know about the project to 4SEQUELS will meet you where you are and help you quickly organize. AI agents dive in looking deeply at the context to understand where there are gaps, who we need to interact with, who the potential stakeholders are across your organization. One of the first things that the AI agents do is they start to identify who's missing from the stakeholder mapping. What roles do we need to engage so that we can ensure that we're not making expensive mistakes in planning and realizing too late that you forgot to involve somebody critical? Security, compliance, operations, downstream owners, the people who show up in 3 months and say, "Hey, wait, nobody told us about this." The AI surfaces these gaps early before decisions get locked in. FourSQL drives context exploration down contextually relevant dimensions of planning, always responsive to new context as it emerges, even suggesting additional dimensions to investigate. FourSQL closes gaps by automatically recommending questions and work assignments to the right stakeholders. As context is gathered and stakeholders are engaged, communications assets and presentations are automatically created and maintained. Traditionally, you do discovery and then you build the business case. Forsequals AI agents are always keeping context in sync with your assets for presentation and communication. We maintain these assets across any type of report or presentation that your business requires. You can use our AI solution to create new reports and presentations on the fly or to ask questions across any of the reports, uh, that are related to any plan. We're constantly connecting scope to cost, value to outcomes, risks to mitigation, so leaders see the trade-offs as they emerge in real time. And finally, it tells you when you're actually ready. Instead of 6 meetings debating whether you're ready to proceed, the system evaluates it across problem clarity, stakeholder alignment, resources, and dependencies. FourSqurels helps teams align on project-associated project goals, and the associated solutions and detailed requirements— functional, technical, and operational— so that you know you've got vetted solutions that have owners and they move through your approval flow. Bad ideas get filtered out early. Good ideas move faster. You can quickly understand the status of any plan, what work has been done, what work needs to get completed, who is assigned to the work, and where you are in finalizing the plan. Then you can hand them off with one click to upload full prototypes into development workflows in Claude, Cursor, Windsurf, and others, upload projects into Asana, Jira, monday.com for project management, match detailed requirements of this particular project with a shortlist of capable vendors for procurement. You can even ask questions across multiple projects. Our AI agents can parse across and help you prioritize and plan. Maybe I want to understand which projects provide the most ROI that are in the queue. So how to apply this? So if you're planning AI or transformation initiatives this year, what I'd recommend is start with one initiative, not 10. Don't try to transform your entire planning process overnight. Pick one complex initiative that's about to kick off, run it through an Agentic planning system, see what it surfaces that you would've missed, understand the stakeholders, the gaps, the assumptions, experience the efficiency of new ways to collaborate, new ways to manage planning approvals, new ways to hand off to execution. That's your proof point. Elevate your impact from managing tasks and executing work up to orchestrating a planning ecosystem. Treat this transition from strategy to initiative as deliberate work. Most organizations treat this as an implicit handoff. Strategy gets set, then teams figure out how. That's where things fall apart. You need to be using AI to make the transition structured. Define the problem, identify who's missing, pressure test assumptions before commitments get made, and finally measure planning differently. Stop measuring planning by documents produced, tasks managed or meetings held. Start managing by how many assumptions got challenged early, how many stakeholders got involved, involved with the project before it was too late, how fast you reached a confident go/no-go decision. That's what actually predicts execution success. Now, if you want to see how multi-agent AI can transform your planning process, encourage you to try FourSqualls by clicking the first link in the description. We built it specifically for enterprise teams who are tired of the manual fragmented planning processes that creates execution problems downstream. It'll compress hundreds of hours of planning work into minutes while improving your execution success rate dramatically. So again, click the first link below to try it out now completely for free. And if you want to see more content about using AI for enterprise planning, then watch this next video.