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Hello again wherever you are today, mentally, physically or emotionally! I am really excited about this post. If you’re curious about how AI is truly transforming the workplace, not just in theory, but in the day-to-day reality of our jobs, you’ll be excited about this post too! Today, I’m diving into Ethan Mollick’s Co-Intelligence: Living and Working with AI, focusing on the insights from Chapter 5: “AI as a Coworker.” This chapter is absolutely packed, and after several read-throughs (and a lot of reflection), I’m excited to distill the key points and anecdotes for you. Let’s go!The New AI Revolution in the WorkplaceLet’s start by busting a big misconception that Mollick starts off with: Many people assume the AI revolution is about automating the most tedious, repetitive, or dangerous tasks first. After all, that’s how previous automation waves have worked. But this time, it’s different. Research shows that “AI overlaps most with the most highly compensated, highly creative, and highly educated work.”As someone who leads product at a software company, I see this firsthand. AI isn’t just about outsourcing the boring stuff. It’s touching the heart of what many of us do best (and love to do). This is a fascinating paradox, and it means we need to rethink both our jobs and our organizations.Rethinking Jobs: Beyond Roles, Toward SystemsMollick reframes jobs not as single, static roles, but as bundles of tasks within larger systems. To make the most of AI, leaders need to understand their organizations as interconnected systems and look for opportunities where AI can make a real difference. Buying AI tools without a strategy? That’s a recipe for confusion and missed opportunities.Here’s a quote from Mollick that really stuck with me:“The systems within which we operate play a crucial role in shaping our jobs as well.If left to our own devices, people often misuse AI, making themselves redundant or trusting AI too much in the areas that require more human oversight. This can lead to carelessness, skill atrophy, and even risk for the organization. Disclaimer: This paragraph may have been a quote directly from the book, but I can’t find it now. However, it’s an important point that I took away from this chapter. I just don’t know if it’s a direct quote! Below is legit proof I read and take handwritten notes (like a non-AI using psychopath) when I create this substack.So, it’s essential for organizations to provide thoughtful guidance and leadership in the rollout of AI tools. One of Mollick’s core principles: Always invite AI to the table. This means intentionally bringing AI into collaborative sessions to see where it adds value (and where it doesn’t).The Three Types of Tasks: Just Me, Delegated, AutomatedMollick introduces a wonderful framework for thinking about tasks in the age of AI:* Just Me Tasks: Deeply personal, authentic, and sometimes ethical tasks that make us human. Think creative writing, sharing personal anecdotes, or anything that needs your unique touch. For me, creating the podcast is mostly as a “just me” task!* Delegated Tasks: These might be tedious or complex, but you’re happy to hand them off to AI, BUT with oversight. You’re still accountable for the results, so your decisiveness and discernment matter. For me, creating the blog version you are reading is mostly as a “just me” task but has a lot of delegated tasks too! (e.g. This sentence was NOT written by AI!)* Automated Tasks: Fully automated, no supervision needed (think spam filtering). These are reliable, scalable, and don’t need your attention.A lot of people assume AI is all about automated tasks, but most of the value (especially in creative, educated roles) comes from a blend of “just me” and “delegated” tasks, where humans SHOULD stay in the loop.Side note: When I hear human in the loop, I literally think of a hoola hoop!Organizational Systems: Why Policy MattersProblems often start with policy. When organizations are too restrictive or slow to adapt, people find workarounds. Hello, shadow IT! I’ve experienced this myself. When my company initially prohibited AI use, I started blogging and podcasting outside of work to keep up with the technology. It was a perfect way to dabble and up-skill with AI because I could not at work. Mollick points out that the usual top-down, centralized approach to rolling out new tech doesn’t work for AI. Instead, the best results come from partnering with your most advanced users and encouraging experimentation—while providing some strategic guardrails.Four Tips for Effective Organizational AI AdoptionMollick offers four practical tips for organizations looking to adopt AI effectively:* Recognize and Celebrate Early AdoptersThese are the people figuring out how to use AI best. Bring them to the table and let them help shape your approach.* Reduce Fear and Stigma Around ExperimentationLeaders should make it safe for people to talk about and try AI without fear of getting in trouble. Ethics and safety are important, but so is fluency and comfort.* Incentivize AI Use and InnovationConsider offering rewards, promotions, or other incentives for employees who drive AI productivity. This one might be controversial, but it can spark creativity!* Prepare for Structural ChangesWithout rethinking how organizations work, the benefits of AI will never be fully realized. Be ready to evolve your structures and processes.Opportunity Mapping: A Practical ApproachOne of the most valuable tools I’ve learned recently is opportunity mapping! Huge shout out and thanks to a certification with 33A and mentorship from Judith Cardenas at Strategies by Design. Here’s how it works:* Start with your org chart (or part of it).* Identify core business values, pain points, and where AI is already in place.* Overlay different AI technologies to find the biggest opportunities.* Use tools like 33A’s AI cards to educate and spark ideas—tying them directly to business needs.This isn’t just about brainstorming; it’s about connecting AI opportunities to real pain points and business values.A Manager’s Experiment: Mapping Genius and FrustrationRecently, I piloted an AI opportunity mapping session with my product team. I adapted the Organization Opportunity Mapping framework I learned to the specific context of product management competencies and jobs to be done. Here’s what we did:* Identified each person’s “working genius” and “working frustration” (using Pat Lencioni’s, Six Types of Working Genius framework). This was a continuation of the the previous retreat I facilitated with my team and wrote about here. * Mapped competencies to these geniuses and frustrations, not just tasks, but the relationship to personal joy and frustration.* Brainstormed ways AI could help, either by turning frustrations into delegated or automated tasks, or by protecting the “just me” tasks.* Created a system of accountability, pairing people up as accountability partners to run experiments and track progress.In just one hour, we saw how powerful it can be to start mapping opportunities at the organizational level, starting with our product competencies and jobs to be done.If you are curious, I made a video capturing my excitement before I rant the workshop and overviewed it. The workshop was EVERYTHING I hoped for, my team loved it, and one week out I am seeing their growth and experimentation with AI come to life! Some products managers went from 0 to 1 or even level 3 quickly!Wrapping Up: AI Is Changing the Fabric of WorkAI isn’t just about automating the boring stuff, it’s changing the very fabric of our work. I’m weaving it into my creative process and daily routine, and I encourage you to experiment, reflect, and keep yourself in the loop as you explore AI in your own work.If you’re interested in learning more or want to see how opportunity mapping could work for your team (or even as an individual), let me know! I’m planning FREE, LIVE TRAINING soon and would love to have you join. It will have limited spots so COMMENT if you want to be the first to know!Until next time, keep experimenting, reflecting, and staying curious!Whenever you're ready, I can help you with:* Workshop design and facilitation* Facilitation and workshop training, including AI Opportunity Mapping and Sprints* Intention setting, planning, and incremental progress for success This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit facilitationartist.substack.com