Speaker 1: 0:00

Welcome back to Inspire AI, the podcast where we explore how artificial intelligence is transforming the world around us. I'm your host, jason McGinty, and today we're diving into your new AI colleague, where we will be talking about how smart tools transform your workplace. Ai has moved beyond the buzzword stage. It's now part of our teams, no longer just quietly automating in the background. These tools are brainstorming ideas, drafting documents, attending meetings I'm looking at you, otter and even writing code alongside us. And adoption has been fast, very fast. By the end of 2024, three quarters of our co-workers were already using AI on the job, with 90% saying it saved them valuable time. Those are astonishing figures. So in this episode, we'll introduce some of the standout AI quote-unquote. Colleagues, you might already know ChatGPT, microsoft, copilot, claude, google, gemini, perplexity, ai, and there are so many others that are getting introduced to the market today, but we're going to focus on a few. Each of these brings their own strengths, from quick drafting and creative brainstorming to deep analysis, integrated productivity and fact-checking research. Together, they're reshaping the way we collaborate, solve problems and get work done. As we dive in, we'll explore how they fit into daily workflows like writing, coding, meetings and decision-making. We'll share real examples of them, boosting productivity, and give you tips for making the most out of your human and AI partnership. So grab your coffee or your nightcap, get comfortable and let's meet your AI colleagues.

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First up, we have ChatGPT, the all-rounder great for quick drafts, creative ideas, coding, help and clear explanations, always on, always ready. Next we have Microsoft Copilot, which lives inside Word, excel, outlook, github, you name it. It can draft, analyze, summarize and code without breaking your workflow. Next we have Claude Anthropics Baby, a standout assistant with tremendous memory, perfect for digesting long reports, detailed analysis and step-by-step problem solving. I would even go as far as call it the Volvo of AI models, where safety is its niche. Then we have Google's Gemini, more specifically in Google's workspace native, where it can draft emails, build slides, analyze sheets and even interpret images. You're always on brainstorming partner. And finally, we have Perplexity AI, the research pro. It finds answers with sources, searches, live web, plus your internal docs, and turns it all into clear, reliable summaries. And finally, we have each of these brings their own strengths, but they share the same mission Make work faster, smarter and more collaborative. And finally, Perplexity's new product called Amit, an AI-powered browser that sits on your sidebar ready to summarize pages, answers questions about what you're reading, or takes actions like sending emails without breaking your flow. Each of these brings unique strengths, but they share the same mission making work faster, smarter and more collaborative.

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You are now seeing and hearing how AI tools are no longer nice to have. They are woven into the fabric of our workflows. So here's how they show up in everyday tasks, starting with writing and brainstorming. Chatgbt and Gemini turn bullet points into polished drafts. They can suggest marketing slogans or outline a presentation in seconds. They're great for getting past the blank page and sparking creative ideas. One example in the wild Dunn and Bradstreet used Gemini to auto-draft personalized prospect emails, saving hours for their employees while keeping messages nice and tailored.

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Next we have coding and development. The examples everybody knows about are GitHub, copilot, ChatGPT and Claude. Some of the latest advancements in their AI models have made coding exceptionally easy and have expanded the horizons and imaginations of developers and non-coders alike. These tools have literally become pair programmers writing code, suggesting fixes and explaining logic. Claude's huge context window enables full code base Q&A. The result faster builds, fewer bugs and less time hunting through documentation.

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Next up meetings and communication the things we all love and cherish. Well, we have Microsoft Copilot in Teams, taking perfect notes, highlighting decisions and suggesting next steps. Jim and I in Gmail can now turn a few bullets into a ready-to-send email. These tools make it easy to stay aligned, even if you join a meeting late. Then we have Perplexity AI, which excels at real-time source-cited answers from both web and your internal docs. Comet takes this further, embedding an AI assistant directly into your browser for instant page summaries, context-aware answers and quick actions without leaving your current task.

Speaker 1: 6:15

Finally, what we've all come to love is summarization and insights. Both Cloud and ChatGPT can condense hundreds of pages into concise summary. Copilot and Excel can analyze your data surface trends and explain them in plain language, turning raw numbers into clear, actionable insights. What you'll find across all of these areas, the pattern is the same AI handles the repetitive work, so humans can focus on higher value thinking. We draft, they refine, we ask, they analyze, we decide, they support. It's not replacement, it's teamwork at machine speed. The day-to-day experience of work is changing for the better Less drudgery. Work is changing for the better Less drudgery, more creativity and insight. So let's ground this information in a couple of quick, real or hypothetical scenarios that illustrate what working with an AI colleague can look like.

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Imagine you're a product manager preparing a strategy document. You start by asking ChatGPT to brainstorm ideas for your product roadmap. It comes back with a creative list of features and improvements some expected and some novel. Next you outline your strategy points and ask ChatGPT through your company's ChatGPT team workspace, of course to turn these bullets into a draft proposal. In a few short moments you find the first draft of a strategy document, which you then refine and tailor. But wait, you notice a gap in the competitive analysis. So you turn to Perplexity AI. You query what are the latest trends in this industry and what are our competitors focusing on? Perplexity searches the web and your internal reports, then presents a concise summary with references. You drop those insights into your document.

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Now for data to back the strategy. You use Microsoft Copilot in Excel to analyze last quarter's sales and produces a quick chart highlighting that 80% of the growth came from one region. You incorporate that chart Before a meeting with leadership. To present this, you have Jim and I in Google Slides, suggest a few slide layouts and even generate some graphs, maybe even an illustrative icon set. You make the presentation pop After the meeting Copilot and Teams instantly provides you with a summary of the discussion and a list of the decisions and action items. No need for you to scribble notes frantically items. No need for you to scribble notes frantically. In one morning, with these various AI assistants, you went from zero to a comprehensive strategy proposal and aligned the team a process that used to take days or weeks of research, writing and coordination.

Speaker 1: 9:15

Next, an example near and dear to my heart. Consider a software development team working on a tight deadline. A developer let's call her Alice uses GitHub Copilot every day as she writes code. Copilot auto-completes lines and even writes entire functions. It suggests unit tests after she writes a function, saving time on test coverage. Suggests unit tests after she writes a function, saving time on test coverage. When she hits a snag on a bug, she pastes the error message into Claude and includes the problematic code block. Claude scans through the code. It's a lot of code but remember Claude's large context window will handle it. So it responds with a likely cause of the bug and a step-by-step fix. Problem solved in minutes. In parallel.

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Another teammate is new to a particular library that you're using. They ask ChatGPT, via their team's secure ChatGPT environment, to explain how to use this library and gets back example code and best practices. Later, the team has a daily stand-up meeting on Teams. Copilot in Teams transcribes and summarizes what everyone said, highlighting that two developers unexpectedly had opposing approaches to a feature. This alert lets the team lead resolve the discrepancy right after the meeting, avoiding a bigger issue later by the end of the week. This development team delivers their project faster than expected and they credit the AI assistance for automating the boilerplate coding and catching issues early, essentially amplifying their output without needing additional headcount, which saves the company lots of money. In fact, this mirrors the company lots of money. In fact, this mirrors what many companies have found. A GitHub study noted significant productivity boosts and developers often say AI lets them focus on interesting problems while it handles the repetitive setup work.

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These examples blend real capabilities with day-to-day work. They show us that, whether you're in marketing, engineering, sales or operations, there are tangible ways these AI colleagues can contribute. They can help your writing and research get done faster, your coding and testing become smoother and meeting follow-ups no longer get forgotten, and meeting follow-ups no longer get forgotten. It's not about AI taking over jobs. It's about AI taking on tasks to free us up for more strategic, creative and interpersonal work. Think of AI as an eager junior team member who can work super fast, never sleeps and doesn't mind doing the tedious stuff and is available whenever you need a hand. By now, you might be excited to work with these AI tools, if you aren't already. But how do you get the best out of an AI assistant? Working with AI is a new skill in and of itself, so here are some tips to make AI collaboration productive and smooth.

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First, choose the right tool for the right task. Each AI colleague has its specialties. For example, use GitHub Copilot or ChatGPT's Code Interpreter for coding tasks, but use perplexity or chat GPT with browsing and researching a topic with the latest info. If you want help within your email or document editor, lean on tools like Gemini and Google Workspace or Copilot in Microsoft Office, which are already context aware. Matching the tool to the job will get you the best results, just like you'd ask a finance colleague for a budget question and a design colleague for a graphics question.

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Next, be clear and specific in your prompts. When delegating to an AI, clarity is key. I'll say that again Clarity is key. Formulate your request with enough details so that the AI knows what you want. For instance, instead of asking help me with this data. You might say analyze the sales data and tell me which product category grew the fastest year over year and why that might be. Providing it context like relevant data or background information, and even suggesting the format of the answer Bulleted list versus table versus summarized paragraph can guide the AI to produce more useful output. Think of it as giving instructions to a colleague yes, ai colleague or an intern. The better the instructions, the better the results.

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Next, iterate and refine. Treat the AI as a partner with whom you can have a dialogue. Rarely will the first output be absolutely perfect. Use follow-up prompts to refine the result. If a draft is too formal, say make the tone more casual, please. Or if the code isn't quite doing what you need, say that's close, but adjust it to do X. All these AI tools allow an iterative prompting. You can keep tweaking your request or ask for improvements in different ways. For example, in a brainstorming you might go back and forth a few times by saying those first five ideas are great. Can you expand on idea number two? Don't be afraid to ask for changes. The AI doesn't take offense and will happily adjust its output.

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Next tip double check and edit the AI's work. Don't take for granted that it knows exactly what you're looking for or has done all of its due diligence. Even though the AI colleagues are smart, they do make mistakes or occasionally produce irrelevant information. We'll call those hallucinations. Always review and verify important outputs. Use the AI suggestions as part of your draft or first pass, and then apply your expertise to ensure accuracy and appropriateness. For instance, if perplexity gives you a statistic, glance at the citation to make sure it's from a reliable source. If Copilot writes a piece of code, run it and add tests to confirm it works. Check it for bugs, for vulnerabilities. Think of the AI's work like that of a diligent, high-potential employee, but it still needs senior oversight. This way, you combine AI speed with human judgment, which makes a powerful combo.

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And here I'd like to remind you of privacy and policies when using AI at work. Remember that these tools are powered by data. Make sure you're not passing confidential or sensitive information into the public AI service unless your company has approved it. Opt for enterprise versions. I mentioned, for example, openai's ChatGPT Enterprise ensures your data isn't used to train the model and is encrypted. Additionally, adhere to any AI usage guidelines your organization provides. A good practice is to keep personal or proprietary data safe. So think about using AI apps that let you work with data without it leaving your environment, like Copilot working with your files in place. So leverage these features, but leverage them carefully. Treat the AI like another co-worker in terms of confidentiality. You wouldn't broadcast your company's secrets to the world, so don't put them in the public AI prompt either.

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Finally, my favorite continue learning and experimenting. Ai tools are evolving fast. New features and improvements roll out frequently. Just think of how many updates ChatGPT had in one year, or how Google and Microsoft keep adding AI integrations. To truly get the most out of your AI colleagues, set aside a little time to stay updated and experiment. Try out new capabilities. For example, if your AI tool gets a new ability to handle images or voice input, consider how that might help you. Maybe you can now speak your ideas and have them transcribed and expanded by AI.

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Many companies offer tutorials or have communities such as forums, centers of excellence or internal champions where you can pick up pro tips. Don't be afraid to play around with prompts in a low-stakes context to see how the AI responds. The more comfortable you get with how the AI thinks, the better you'll be at collaborating with it. Remember, you and the AI are learning to work together, so there's a bit of training both ways. You might need to quote-unquote, train your AI by giving feedback or more context, and you train yourself by discovering what phrasing or approach yields the best results. By following these tips, you'll develop a smooth working relationship with your AI colleagues. Many early adopters say the key is to treat the AI as a partner or an assistant. Not a magic oracle that instantly replaces effort, but as a very capable helper that amplifies what you can do. With clear communication and a bit of oversight, your AI colleague can become an indispensable member of the team.

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As we wrap up this episode, let's take a moment to look ahead. We're at an exciting inflection point how work gets done. Just as email and the internet once revolutionized the office, ai is now poised to do the same as a day-to-day collaborator. Today, we focused on tools like ChatGPT, copilot, claude, gemini and Perplexity, each already making a mark in workplaces by handling tasks and offering insights. Tomorrow, the capabilities will only get better.

Speaker 1: 19:25

I'm here to tell you that the idea of AI as your co-worker is no longer science fiction. It's reality. These tools are transforming how we work, from automating the mundane to accelerating insight, and this is just the beginning. Future AI colleagues will anticipate needs, collaborate across tools and deliver even richer context. By learning to work side by side with these smart tools, we can free ourselves to focus on creativity, strategy and human connection the things machines can't replace. So give your AI colleague a task this week and see what you can accomplish together. You've been listening to Inspire AI, where we explore how intelligent technology is shaping the world. Today's episode gave us a glimpse into AI-powered teamwork. We'll be back soon with more insights and interviews on the cutting edge of AI. If you liked what you heard, give us a rating or share the podcast with a friend or a colleague, and thank you for listening. Go, have a productive and inspired day.