The Second Wave: AI Enhancements in Business Apps

In the last lesson, we explored how AI-powered tools are revolutionizing work by helping people generate text, images, and even videos with just a few clicks. But now, we’re moving into the second wave of AI adoption—where AI isn’t just a standalone tool, but is embedded inside the software businesses already use every day.

We’re talking about AI inside CRMs, workplace applications like Microsoft Office and Google Workspace, and nearly every SaaS product on the market. Instead of switching to a separate AI tool, businesses can now use AI within their existing apps to speed up tasks, improve efficiency, and reduce manual work.

But here’s something important to understand—AI inside business applications doesn’t function the same way as AI-native tools. It’s more of an add-on than a deeply integrated AI system. It’s like having a co-pilot inside your software—helpful, but still limited by the app it lives in.

In this lesson, we’ll break down how AI is enhancing business applications, the difference between AI-native tools and legacy software with AI add-ons, and how you can start using AI inside the tools you’re already familiar with.

How AI is Being Embedded into Business Apps

The first wave of AI adoption started with standalone tools—ChatGPT, DALL·E, Jasper AI, Midjourney, and other AI-powered platforms. These were built entirely around Generative AI and offered deep AI functionality.

But the second wave is different. Instead of introducing entirely new AI products, companies are embedding AI into the software businesses already use.

Almost every CRM, project management tool, document editor, and spreadsheet application is now adding some form of AI. The goal? To help users work faster and automate repetitive tasks.

A great example of this is Microsoft Copilot. Instead of forcing users to adopt a brand-new AI tool, Microsoft embedded AI directly inside Word, Excel, PowerPoint, and Outlook. Now, users can generate summaries, create charts, automate emails, and refine writing—right inside their familiar workspace.

Google is doing the same thing with Google Workspace. Gmail now suggests responses based on email context, Google Docs can generate outlines, and Sheets can help automate data organization.

CRM platforms like Salesforce and HubSpot have also jumped in, using AI to draft sales emails, generate reports, and even suggest next steps for leads—all within the CRM itself.

And almost every major SaaS product—from customer support platforms to HR management systems—is now layering AI on top of their existing functionality to help users automate tasks.

This is a huge shift because businesses no longer need to adopt entirely new software to benefit from AI—it’s simply becoming a layer within the apps they already use.

The AI "Add-On" Effect: Why Embedded AI is Different from AI Tools

While AI inside business applications is powerful, it’s important to understand how it differs from AI-native tools.

The biggest difference? Embedded AI is limited by the application it lives in. It’s an add-on, not the core engine of the software.

For example, let’s say you’re using AI inside a spreadsheet application like Excel or Google Sheets. AI can certainly help answer questions, suggest formulas, and provide guidance on how to manipulate data. But it’s not tightly integrated into the spreadsheet’s logic. It’s more of a co-pilot, guiding the user, rather than an AI system that’s deeply controlling how the app functions.

The same holds true in CRM applications. AI can help draft emails, summarize customer interactions, and generate reports, but it still requires a human to engage with it. It won’t fully automate your CRM for you—it will simply assist you in working faster.

This is where AI-native tools differ from legacy software.

AI-native platforms, like ChatGPT or Jasper AI, are built entirely around Generative AI—meaning they can generate content more freely, respond dynamically, and provide deeper functionality. Legacy business software, on the other hand, is still bound by its existing features, and AI is simply being layered on top to enhance those features.

In short, AI inside business apps helps accelerate tasks, but it still works within the boundaries of the original software.

How to Leverage AI Inside Business Applications

Now that AI is becoming part of the tools you already use, how can you make the most of it? Let’s look at some real-world use cases of AI inside business applications.

1. AI in CRMs: Automating Sales & Customer Interactions

If you’re using a CRM like Salesforce, HubSpot, or Zoho, AI can now assist with sales emails, lead management, and customer interactions.

Instead of manually drafting a follow-up email to a lead, AI can generate one for you based on previous conversations. Instead of analyzing customer interactions one by one, AI can summarize key insights and suggest next steps.

AI inside CRMs isn’t replacing human salespeople, but it’s reducing the time spent on admin tasks so teams can focus on closing deals.

2. AI in Workplace Apps: Smarter Writing, Summaries & Automation

In Microsoft Word and Google Docs, AI is helping professionals write faster, summarize documents, and refine messaging.

Let’s say you have a 20-page report that you need to summarize. Instead of reading through the whole thing, AI can generate a short executive summary in seconds.

AI-powered tools like Microsoft Copilot and Google’s AI assistant are also helping users write emails, brainstorm ideas, and structure content—all within the document editor itself.

The same goes for Outlook and Gmail. AI can now suggest email responses, generate drafts, and automate scheduling tasks.

3. AI in Spreadsheets: Guiding, Not Replacing Workflows

AI inside Excel and Google Sheets is helping users write formulas, analyze data trends, and automate calculations.

Need to create a complex formula but don’t remember the syntax? AI can suggest it for you. Want to analyze sales data? AI can highlight patterns and suggest improvements.

However, AI in spreadsheets doesn’t replace manual analysis—it’s simply a guide that helps users work faster and with more accuracy.

The Limitations of Embedded AI: What It Can’t Do (Yet)

While AI inside business applications is a major step forward, it still has limitations.

First, it doesn’t deeply change how the app itself works—it simply enhances existing features. AI in a CRM can help you draft emails, but it won’t run your entire sales process automatically. AI in a spreadsheet can help you with formulas, but it won’t restructure your data model on its own.

Second, it still requires human engagement. AI doesn’t fully automate workflows—it accelerates them. Users still need to review AI-generated content, make decisions, and refine AI-powered suggestions.

Finally, AI inside business applications is only as good as the software it’s built into. If a legacy SaaS tool has outdated workflows or poor integration, AI won’t magically fix it—it will just provide enhancements within its existing structure.

That’s why AI-native tools—like ChatGPT, Jasper AI, or Midjourney—offer more advanced AI capabilities than legacy software that simply adds AI as a feature.

Why This Matters for Businesses

The second wave of AI adoption means businesses don’t need to invest in entirely new AI products—AI is already being woven into the tools they’re using today.

This is great news because it means businesses can start using AI immediately without disrupting their workflows. However, understanding AI’s role as an add-on rather than a core system is key to setting the right expectations.

AI inside business apps is helping companies save time, work smarter, and reduce mundane tasks, but human input is still essential. It’s a tool to accelerate work, not replace decision-making.

What’s Next?

We’ve covered AI-powered tools in the first wave and AI-embedded applications in the second wave. But there’s one more stage of AI evolution—the third wave: AI Agents.

Unlike standalone tools or embedded AI features, AI Agents are designed to take action on their own, performing work without constant human input.

That’s what we’ll explore in the next lesson—how AI Agents are changing the way businesses automate complex tasks, handle workflows, and even make decisions.