AI for Leaders: How to Get Your Time Back and Actually Lead People

You don't have time for the people you're leading because you're spending hours on tasks that AI could handle in minutes. Leaders using AI save 40-60 minutes daily, yet only 26% of employees use AI weekly despite 91% of businesses adopting it. The AI Efficiency Framework (Colby Morris) recovers lost time through: Interactive Prompting (asking AI to ask clarifying questions before analysis), Context Building (using Projects/Spaces to build deep understanding over time), Workflow Automation (applying AI to sales analysis, overtime patterns, presentations, and daily tasks), and Compounding Returns (small time savings across email, scheduling, and meeting management that accumulate to 3-4 hours weekly). Workers using AI report saving 5.4% of work hours—approximately 2.2 hours per week—time leaders can redirect to coaching, relationship building, and strategic thinking.

Episode Description

You don't have an AI problem. You have a time allocation problem.

Enterprise workers using AI save 40 to 60 minutes every day. But only 26% of employees actually use AI weekly—leaving hours on the table that could be spent leading people instead of drowning in tasks.

In this episode, you'll discover:

→ Step-by-step AI workflows for sales analysis, overtime pattern detection, and presentation creation

→ The Interactive Prompting technique: how to get AI to ask YOU clarifying questions for better analysis

→ How to use Projects (Claude) or Spaces (Perplexity) to build deep contextual understanding over time

→ Simple daily AI applications for email, scheduling, and meeting management that compound to 3-4 hours saved weekly

The best leaders aren't doing everything themselves. They're automating tasks to be present with people.

The AI Efficiency Framework (Colby Morris)

Component 1: Interactive Prompting Ask AI to ask YOU clarifying questions before analyzing data for more sophisticated, context-aware insights.

Component 2: Context Building Through Projects Use Projects (Claude), Spaces (Perplexity), or ChatGPT Projects to build deep institutional knowledge over time by storing files and conversations in one dedicated workspace.

Component 3: Workflow Automation Step-by-step AI applications for sales analysis, overtime pattern detection, presentation creation with Gamma.app, and daily task management.

Component 4: Compounding Returns Small time savings across email, scheduling, and meetings accumulate to 3-4 hours weekly—redirected to coaching and relationship building.

When to Apply This Framework

Use the AI Efficiency Framework when:

• You're spending more time on tasks (data analysis, presentations, email) than on people (coaching, one-on-ones, relationship building)
• One-on-ones keep getting rescheduled due to lack of time
• You need to analyze data regularly (sales performance, overtime patterns, budget variances)
• You're creating presentations or reports from existing content
• You're drowning in email, scheduling conflicts, and meeting prep
• You want to recover 3-4 hours weekly for leadership activities

This framework is designed for leaders at all levels who need to shift time allocation from administrative tasks to people-focused leadership.

Diagnostic Questions

• What percentage of your week is spent on tasks versus people?
• If you could get back 3-4 hours per week, how would you spend that time with your team?
• Are you manually analyzing data when AI could do it in minutes?
• How much time do you spend creating presentations from existing content?
• Do you use Projects/Spaces in your AI tool to build contextual understanding over time?
• Have you tried Interactive Prompting (asking AI to ask you clarifying questions)?
• What's one regular task you d

• Colby's LinkedIn Profile
• NXTStepAdvisors.com

Transcript

People First Leadership Setup

SPEAKER_00 0:00

People first leadership. Actionable strategies, real results. This is Things Leaders Do with Colby Morris.

What Is Actually Eating Your Day

Sales Data Analysis In Seconds

Finding Overtime Root Causes Fast

Turning Notes Into Great Slides

Email Calendar And Meeting Prep Wins

Pick One Task And Lead

SPEAKER_01 0:11

You don't have an AI problem. What you really have is a time allocation problem. So you're spending three hours analyzing sales data when AI could do it in like, what, 10 minutes? Faster? You're spending two hours creating a presentation when AI could draft it in just 30 seconds. You're spending an hour scheduling meetings when AI could handle it automatically. And every minute you spend on those tasks is a minute you're not spending leading people. So stop saying you don't have time for your team. You do. You're just using the time wrong. Here's what actually happens Enterprise workers using AI save between 40 and 60 minutes every single day. That's three to five hours a week. 15 to 20 hours a month. Time they're getting back to focus on work that actually requires, you know, a human brain. But 91% of businesses use AI in some capacity while only 26% of employees actually use it weekly. What that means is most leaders are leaving those 40 to 60 minutes a day on the table. They're still manually doing work that could be automated. They're drowning in tasks when they sh should be focused on the people. They're too busy to coach. They're too busy to have one-on-ones, too busy to build relationships. Not because the time doesn't exist, but because they're spending it on things AI could handle. And here's the part that should really bother you. 75% of workers who use AI say it enables them to complete tasks they previously couldn't do at all. You hear that? Not just faster. Okay. Tasks they literally could not accomplish before. But 56% of workers have received no AI training. None. So most leaders are stuck in this weird middle ground. They know AI exists, they feel anxious about it, but they have no idea how to actually use it to make their lives better. Well, today I'm giving you the practical playbook, real scenarios, step-by-step examples, exactly how to use AI to get your time back so you can spend it on the people you're leading. Okay, I'm going to cover, you know, sales analysis, overtime pattern detection, turning content into presentations, and simple stuff that just adds up. Okay, not theory, not someday you should learn this, but actual tasks you can start automating this week. Because the best leaders aren't the ones doing everything themselves. They're the ones who figured out how to be efficient at tasks so they can be present with people. So let's get into it. Today, I have about 30 minutes of practical, immediately actionable AI use cases that will save you hours every week. Okay, I'm gonna try to use not a lot of technical jargon, you know, no learn to code type stuff. Just copy and paste examples you can use today. All right. So let's talk about what's actually eating your time. You're a leader, right? I mean, you're listening to the podcast, so that's my assumption. Your job is to build a team, to develop people, to navigate challenges, make strategic decisions, and create an environment where good work happens. But what are you actually spending your time on? Data analysis, presentation creation, email management, scheduling, report writing, meeting prep, pulling information from six different systems and trying to make sense of it. All tasks, no people. And then you wonder why you don't have time for coaching, why 101s keep getting rescheduled, why you haven't had a real development conversation with your team in weeks. It's not because you're bad at time management, it's because you're manually doing work that doesn't require your judgment, your experience, or your leadership. You're doing work a computer could handle while your people, actual humans who need actual leadership, they're waiting for your attention. Here's what the research shows. Workers using AI report saving 5.4% of their work hours on average. That's about 2.2 hours per week in a 40-hour work week. Doesn't sound like much, right? Two hours. Okay, so what could you do with an extra two hours a week? You could have four 30-minute one-on-ones. You could do a deep dive coaching session with someone who's struggling. You could actually think strategically instead of reactively. You could build relationships with stakeholders, you could mentor someone, you could sit in on your team's work and understand what they're actually dealing with. Two hours a week is eight hours a month. That's a full workday you're getting back every single month. And that's the average. People who actually use AI report saving way more. Some are getting back four hours a week. That's 16 hours a month, two full work days. But most leaders aren't getting any of this time back because they don't know where to start. They open Chat GPT or Claude or Gemini and stare at a blank screen like it's going to read their mind and type help me with leadership and get what? You know, some kind of generic response about emotional intelligence and then close it and go back to doing everything manually because at least Excel doesn't judge me. So let's make this concrete. Let me show you exactly how to use AI for specific tasks you're probably doing right now, step by step, no guessing. Starting with one of the most time-consuming tasks leaders phase analyzing data to make decisions. All right. Let's say you're leading a sales team, and every week you need to analyze performance to figure out what's actually working, what's not, and where to focus. Here's what that used to look like. You log into your CRM, wait for it to load because CRMs are apparently powered by hansters on wheels. Export the data. Open Excel. Discover the export formatting is completely broken because of course it is. Spend 20 minutes fixing column headers and removing random blank rows that shouldn't exist. Create pivot tables. Make charts. Squint at the numbers trying to spot patterns while questioning whether you should have paid more attention in that statistics class in college. Realize you need to cross-reference this with the last quarter's data. Hunt for that file. Can't find it. Check your email. Check your downloads folder from three months ago. Finally, you find it with a file name like Q3 underscore final underscore final underscore blah blah blah. Actually final XLSX, which you know isn't actually the final version because there's probably a Q3 final, final, blah, blah, blah, blah, somewhere that you just haven't found yet. So you write up your findings, you format it into something presentable. Maybe create a slide deck if you're you know presenting to leadership. Five to PowerPoint alignment for what, 15 minutes? Because apparently perfect alignment is a myth perpetuated by graphic designers to make the rest of us feel inadequate. The total time? Probably two to three hours. And that's if everything exports correctly the first time, which it usually never does. There's always that one column that comes through with, you know, four pound signs in a row, and you have to figure out what went wrong. Spoiler, it's always the column width. It's always been the column width. So here's what it looks like with AI. Step one, export your sales data into a CSV file. Just the raw report. Don't clean anything up. Let it be ugly. AI doesn't judge your messy data. It has seen worse, trust me. Step two, pick your AI, Claude, Chat GPT, whatever, and upload the CSV file. And then step three, give it a prompt like this. Analyze this sales data. I need to understand one, which products are performing best and worst this month. Two, which sales reps are exceeding targets and which are falling short. Three, any patterns in deal size or close rates. And four, recommendations for where to focus coaching efforts. Present the findings clearly with specific numbers. Step four, wait about 30 seconds. Maybe grab a coffee or just sit there feeling weird about how fast this is happening. Like when you're used to traffic being terrible and then one day the roads are empty and so you just don't trust it. That's it. AI will analyze the entire data set. Okay, it'll spot patterns, spot patterns you might have missed, and give you a clear breakdown with actual insights. Here's the thing: it won't just regurgitate numbers at you like you're in a statistics lecture taught by the world's most boring professor. Okay, it'll tell you things like your top performer is closing deals 40% larger than average, but taking 15% longer to close them. Or three reps or consistently losing deals in the$50,000 to$100,000 range, suggesting a need for training on mid-market objection handling. Yeah. That's an analysis you would have spent an hour doing manually while questioning all your life choices and wondering if it's too late to become a park ranger. AI did it in 30 seconds without complaining once. Now you're not done. You still need to apply judgment. Okay, AI doesn't know that your top performer is working different accounts or that one of your struggling reps just came back from parental leave and is still getting back up to speed. It doesn't know that the person losing$50,000 deals just got assigned to territory where everyone's budget got slashed. But AI just freed up two and a half hours of your time. Time you can now spend actually talking to your reps, understanding what they're dealing with, coaching them through challenges, you know, leading. Let me give you another example. Same sales data, different question. Here you put in this prompt. Look at our dual pipeline. Which opportunities are most likely to close this quarter based on historical patterns? Which ones are probably going to slip? Give me a prioritized list of where my team focus should be. Then AI will analyze close rates by dual stage, time in the pipeline, deal size, rep performance history, and give you a prioritized action list. It's like having a data analyst who actually enjoys looking at spreadsheets and doesn't make sad faces when you ask them to pull another report. That's strategic intelligence you can use immediately. And it took you, what, two minutes instead of two hours? And here's what you do with that time you just saved. You have actual conversations with your team. You ask better questions, you help them, you know, prioritize. You coach them through the deals that matter. Because that's your job. Your job isn't to be the best Excel user on the team. Okay. Your job isn't to win pivot table competitions. Your job is to make your people better. AI handles the data, you handle the humans. Okay. Let's talk about another scenario. You're noticing overtime costs are creeping up. Finance is sending you emails with, you know, the concerned subject lines, you know, the ones that start with quick question, but are never real really actually quick. They're the email equivalent of we need to talk. You need to figure out what's driving overtime and how to fix it. So the old way, you pull overtime reports from your HRIS system. That requires remembering your password because you only log in once a quarter. Can't remember it. Try your usual password. Wrong. Try your other usual password. Wrong. Try the password you used three systems ago. Locked out. Reset your password. Create a new password that meets 17 different requirements, including at least one hieroglyphic. Get locked out again because you typed it wrong. Call IT. Wait 20 minutes while listening to hold music that sounds like it was recorded in 1987. Finally, get in. Now you export the data for the last six months. Import it into Excel, sort by department, sort by employee, create more pivot tables because apparently that's your life now. You're a pivot table person. That's who you've become. You try to spot patterns, look for trends. You cross-reference with project timelines that someone saved in a shared drive with a folder structure that makes no sense. Who organized this? Why is there a folder called miscellaneous two when there's no miscellaneous one? What does old files do not delete mean? Which old files? Why can't we delete them? Then you pull your hair out trying to figure out if this is a staffing issue, a workflow issue, or just seasonal. Realize you've now spent three hours on this, you still don't have a clear answer. You have more questions than when you started, and a headache. That's great. Time investment? Probably a full afternoon if you're lucky. Maybe a whole day if the data's messy, which it usually is. The AI way is completely different. It looks like this. Step one, export your overtime data, include employee names, departments, hours, dates, projects if you have them. The messier the better. AI loves a challenge. It's like a puzzle to AI, except AI doesn't get frustrated and quit halfway through like you do with actual puzzles. Step two, upload to Claude, and here's where you do something smart. Instead of just asking it to analyze it, you prompt it like this. I need to analyze this overtime data to understand patterns and root causes. Ask me whatever questions you may need to give me a detailed report. And here's what happens. Claude will ask you clarifying questions. What's your typical staffing model? Are there known seasonal patterns? What's your target overtime percentage? Are there specific projects or initiatives that might be driving this? Then you answer the questions. And now Claude has context. Real context about your specific situation. And instead three, now you give it the full prompt. Based on my answers, analyze this overtime data. I need to understand one, which departments or teams have the highest overtime? Two, is this consistent or are there spikes tied to specific dates or projects? Three, which individual employees are working the most overtime? Four, are there patterns suggesting systemic issues versus individual work habits? And then five, what recommendations would you make to reduce unnecessary overtime? And then step four, read the analysis AI gives you in about 45 seconds. Okay, pour yourself another coffee because you actually have time now, like real time, time you didn't have to steal from something else. Here's where it gets really interesting. If you've been using Claude for a while, if you've been having conversations with it about your company, your team, your challenges, it already knows things about your context. It knows your industry, it knows your team structure. It remembers previous conversations about your workflow bottlenecks. So when it analyzes your overtime data, it's it's not doing it in a vacuum. It's doing it with an understanding of your specific situation. And here's how you make it even better. Create a project in Cloud. In ChatGBT, they call them projects. In perplexity, they call them spaces. It's the same concept. But you create a project called overtime analysis or operations efficiency or whatever makes sense. And in that project, you can upload all your relevant files, okay? Overtime reports, staffing models, project timelines, budget data. You can have multiple conversations all related to this one topic, and you can build a deep, rich understanding over time. So the first time you upload overtime data, Cloud might give you good analysis. But the tenth time, when it's seen six months of data, when it knows your seasonal patterns, when it understands your team structure and your ongoing initiatives, the analysis is going to be way more sophisticated. It's like the difference between explaining your situation to a consultant who just walked in the door versus a consultant who's been working with you for months. Except the consultant is AI and doesn't charge you by the hour. You're building institutional knowledge, except the institution is the AI that never forgets, never leaves for another job, and never takes vacations. And the analysis it gives you might say something like overtime spikes occur every month end in your operations team, suggesting a workflow bottleneck that is the close process. This pattern has been consistent for the last six months. Three employees in that team account for 60% of total overtime, and their overtime hours directly correlate with the volume of manual data entry required for financial reporting. Based on your previous conversations about automation initiatives, this would be a prime candidate for process automation. Yeah. That is a specific, actual insight based on your data and your context. You now know it's not a staffing problem, it's a process problem. Specifically, manual data entry end of month. Okay? The kind of soul-crushing repetitive work that makes people question their career choices at 7 p.m. on a Friday while everyone else is already at happy hour. So your next move isn't hire more people, it's automate the month-end data entry workflow. And you just saved your company probably$50,000 a year in overtime costs because AI helped you find the actual problem in 45 seconds instead of spending a day playing detective with spreadsheets. But more importantly, you didn't waste a full day on analysis. You spent 45 seconds, and you used the rest of that time talking to your operations team about what's actually making month end painful, building solutions together, making their lives better. That's leadership. Okay, not drowning in data, but having conversations that fix things. Want to take this even further? Here's your next prompt with that same project. Based on this overtime analysis, draft a memo to leadership explaining the root cause and proposing solutions. Keep it under one page, make it executive friendly, reference the cost savings potential. And then AI will write the memo. Okay, it'll probably be better organized than what you would have written because you're tired from analyzing data all day. Oh, wait, you didn't analyze data all day. You have energy now. You're not exhausted. You can actually think clearly. You'll edit it to add your voice and judgment. Okay, total time 10 minutes. You just saved another 30 minutes of writing time. See how this compounds? It's like finding Money in your couch cushions, except instead of quarters, it's hours of your life. Instead of a couch, it's your job. All right. Here's one that's going to save you hours. Turning content into presentations. Let's say you just wrote a strategy document, or you had meeting notes from a planning session. Or you need to, I don't know, present research findings to leadership. And now you need to turn all of that into a slide deck. So, what's the old way? You open PowerPoint. You start a blank slide, wondering why the default font is Calibri, and wonder who made that decision. You look at all the fonts in the world and said, yes, this one. This is the one that should represent business. Then you try to figure out how to structure it. Copy and paste content, format it, watch all your formatting break because PowerPoint has apparently decided that pasting text should also paste the font, the size, the color, and the emotional baggage from wherever it came from. Find images? Where do you find images? Google images? Those are definitely copyrighted. Stock photo sites. They all look like models pretending to have a business meeting while laughing at a salad. Nobody laughs at salad. Salad isn't that funny. Then now you adjust the layouts. You fight with alignment. You spend 10 minutes trying to make two boxes the same size. They look the same size to you. They look the same size to everyone who's ever looked at them. But PowerPoint insists they're 0.02 inches different and will not let you rest until you fix it. Now you realize it looks terrible. Like a slide deck from 2008, like something someone made before they knew better. So you start over. You try a different template. No, that one's worse. It has decorative swoosh. Nobody needs decorative swooshes. Now you go back to the first one. You spend two to three hours producing something that looks like fine. Corporate, forgettable, the kind of deck that makes people wish the meeting was an email. The kind of deck that makes people check their phones halfway through slide three. The AI way is even better. I'm going to walk you through the exact workflow. Step one, take your content, could be a word doc, meeting notes, a research report, whatever, and paste it into Claude or Chat GPT. And then use this prompt. Turn this content into a presentation outline. I need one, a clear narrative art with eight to twelve slides. Two, each slide should have a headline and two to four key points. Three, suggest where visuals would help. And then four, keep it executive friendly, clear, and concise. And then I want you to review the outline the AI gives you. Make adjustments, maybe combine two slides, split one, reorder them. This takes what, five minutes? You're thinking about structure and story, not fighting with fonts and alignment. Okay? You're doing the creative work that actually requires a human brain. And then next, here's where it gets cool. I want you to go to gamma. That's gamma.ap. Okay. It's an AI-powered presentation tool. And no, I'm not getting paid to say this. I just really hate PowerPoint. Like deeply. If PowerPoint were a person, we would not be friends. So I want you to copy your AI-generated outline and then paste it into gamma and tell Gamma to create a presentation. And then watch as Gamma turns your outline into a fully designed, professional-looking presentation in about 30, 40 seconds, with layouts that make sense, with suggested images that are actually relevant and don't involve people laughing at salad, with design that doesn't look like every other corporate PowerPoint from 2015. It's like it's like watching magic happen. Except it's it's not magic. It's just software that doesn't hate you. Okay, software that was designed by people who also got tired of fighting with PowerPoint alignment at 11 p.m. the night before a big presentation. Okay, and then finally you make the edits. Swap out an image, adjust some text, tweak the design to match your brand if you want. Maybe 10 minutes of refinement to make it yours. Total time from content to finished presentation, about 20 minutes. And that's on the high end. You just saved yourself two and a half hours. And honestly, the presentation probably looks better than what you would have made manually because you're not a graphic designer, and that's okay. Neither am I. That's why we have AI. That's why gamma exists, to save us from ourselves and our terrible design choices. Now, here's what you do with those two and a half hours. You actually prepare to deliver the presentation well. Yeah. You practice, you think about your audience, you anticipate questions, you strategize how to get buy-in. You figure out who the skeptics are going to be and how to address their concerns before they bring them up. Or spend it with your team. Okay. Building alignment before the presentation so there are no surprises. Have the conversations and make the meeting go smoothly. Making sure everyone's on the same page so you're not hearing, wait, I thought we decided on something different in the middle of your presentation. That's how you use AI. Not to replace your thinking, not to free up time for you know something else, but to free up time for better thinking, to get the busy work out of the way so you can focus on the work that actually matters. Okay. Those were the big scenarios. Sales analysis, overtime patterns, presentations, those save hours at a time. But let me tell you about the simple stuff that adds up, like loose change that eventually becomes real money. Like when you finally clean out your car and find$7 and quarters, except instead of quarters, it's minutes instead of seven dollars, it's hours. Email management. Yeah. You get an email that requires a thoughtful response. You stare at it. You draft something, delete it, start over, overthink every word. 15 minutes later, you've got something that's okay. Probably. Maybe you should reread it one more time just to be sure. Actually, that second paragraph might come across as passive aggressive. Is it passive aggressive? You don't mean it to be passive aggressive. Better rewrite it. Okay, here's the AI version. Copy the email into Claude and add this prompt. Draft a professional response that, you know, whatever your goal is, keep it concise and warm. Don't make me sound like a robot or like I'm passive aggressively annoyed. AI gives you a draft in 10 seconds. You read it. You edit to sound like you because AI doesn't know you say hey there instead of hello. And AI doesn't know that you always sign off with thanks because one exclamation point feels friendlier than a period, but two feels too enthusiastic. So you send it. Total time, two minutes. You just save what, 13 minutes? Does that, you know, five times a day, and you've saved an hour. Do that every day for a week and you've saved five hours. That's almost a full work day. You got back from not agonizing over email tone like you were writing correspondence for the queen. And then there's calendar optimization. You're trying to schedule a meeting with six people. You send an email. Does Thursday at two work for everyone? I'm out Thursday, 2 p.m. doesn't work for me. Can we do Wednesday instead? Wednesday I'm in meetings all day. What about Friday? And it just goes on. 30 minutes later, you're ready to just not have the meeting. Okay, everyone can figure it out themselves, or maybe everyone can just email their updates. Actually, maybe we don't even need updates. Maybe we'll all just work independently forever and never speak again. Okay, the AI version. Use a tool like reclaim.ai or clockwise that uses AI to automatically find time that works for everyone based on calendar availability and working preferences. Or paste everyone's calendars into ChatGPT and ask it to find optimal meeting times that doesn't make everyone want to quit. Boom. 30 minutes back. Your sanity intact, your faith in humanity is slightly less damaged. And then there's meeting prep. You've got a meeting an hour. You need to review background information, previous meeting notes, and action items. You know, be prepared like a professional who has their life together. You know the old way, hunting through emails, trying to find that one thread, check your download folders, your shared drives, Slack, Google Doc. You can't find it. You give up. You go into meetings, slightly confused, and hope no one notices. You wing it, you nod thoughtfully when people reference things you don't remember. But the AI way is you drop all the relevant documents into Claude and you prompt, summarize the key point decisions made, and outsend on outstanding action items from these documents. What do I need to know going into today's meeting? What questions am I likely to be asked? Time? Two minutes. Information? Comprehensive. The confidence is high. Your ability to look like you know what's happening significantly improved. Here's what I want you to do today. I want you to pick one task this week. Okay? Something you do regularly that eats your time and use AI for it. Okay. See how much time you get back. Then spend that time with your people. Okay. Actually lead them. You've got this. The secret is to stop doing work that AI can handle. That's it. That's the secret. Now, if your organization is struggling with helping leaders adopt AI effectively, freeing up time for people-focused leadership, or building a culture where efficiency enables better relationships, I'd love to help. I work with organizations for keynote speaking, executive coaching, and leadership training to build people-first cultures that get results. You can connect with me on LinkedIn or at my website, and both those links are in the show notes. And hey, if this episode helped you, would you do me a favor? Would you subscribe to the show wherever you listen to podcasts and leave a review? Those reviews are huge. That's what helps get the word out and helps us help more leaders be better leaders faster. And remember, keep automating the task, keep focusing on the people, and keep using your time where it actually matters. And you know why? Because those are the things that leaders do.

SPEAKER_00 33:39

Thank you for listening to Things Leaders Do. If you're looking for more tips on how to be a better leader, be sure to subscribe to the podcast and listen to next week's episode. Until next time, keep working on being a better leader by doing the things that leaders do.