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AI in Our Work - Where are we now (2025 10 13 captioned)

[00:00–01:00] Introduction & Purpose Sue opens by noting AI’s rapid acceleration and how professionals must now show their AI impact in résumés, CVs, and LinkedIn. Despite limited job postings requiring AI skills, she emphasizes integrating examples of AI use into career materials. ________________________________________ [01:00–02:00] Workplace AI Use Many professionals report restrictions on AI tools (e.g., CDC limits to its own LLM), yet most use them privately. The challenge: demonstrating AI results when workplace use is constrained. ________________________________________ [02:00–04:00] Rapid Corporate Investment Major firms (Google, Oracle, Amazon, Meta, Nvidia) are deeply invested in OpenAI’s expansion. Nvidia dominates because its chips power most LLMs. Corporate adoption shows AI’s deep integration across industries. ________________________________________ [04:00–05:00] Employee Usage vs. Leadership Awareness McKinsey data: Employees use AI three times more than leaders realize. Suggests wide “shadow usage” and lack of executive understanding, driving bottom-up innovation. ________________________________________ [05:00–07:00] AI Application Areas Top uses: practical advice, information searches, ideation, and writing. Reliability improving though errors persist. Growth fastest in computing, mathematics, architecture, and design. Hung Lee notes: AI adoption happens not when it’s better than humans, but when it’s cheaper. ________________________________________ [08:00–10:00] From Digital to AI Literacy UNESCO’s framework moves from digital to AI literacy with three stages: 1. Awareness 2. Application 3. Human-centered outcomes These parallel behavior-change models used in health practice. ________________________________________ [10:00–12:00] Human Skills Remain Vital AI amplifies, not replaces, creativity, empathy, and critical thinking. Liberal arts and humanities backgrounds remain valuable. World Economic Forum’s top skills for 2025 include leadership, adaptability, and social influence—skills AI can’t replicate. ________________________________________ [12:00–15:00] Real Job Postings with AI References AI now appears in limited job types: • Business Analyst: Evaluating and improving AI solutions—similar to managing workflow transitions. • Policy Analyst: “AI-informed context” roles vaguely phrased. • Health Educator: Training others to use AI or label data for machine learning. Most listings use AI as a buzzword rather than a concrete requirement. ________________________________________ [17:00–19:00] AI on Résumés Only 11% of résumés mention AI (up from 6%). Applicants hesitate due to unclear expectations. Focus on: • Critical thinking in AI use • AI for business and strategy Demonstrate insight and results, not just tool familiarity. ________________________________________ [19:00–23:00] Framing AI Experience Effectively Start resume bullets with results, then add how AI enabled them: • “Reduced drafting time by 35% using AI tools.” • “Improved team efficiency by 50% via AI-aided workflows.” • “Saved 8 hours weekly automating analysis.” Always name specific tools (ChatGPT, Copilot, Perplexity). Include only those that suit job descriptions—don’t list every tool. ________________________________________ [23:00–24:00] Skills & Terminology Tips Rate proficiency (basic/intermediate/advanced). Avoid filler terms like “prompt engineering.” Instead, highlight capabilities aligned with recognized AI literacy frameworks. ________________________________________ [25:00–30:00] Participant Dialogue: Applying AI with Care Peter notes difficulty including AI use (“I don’t say I used Word—why list AI?”). Sue suggests framing: • “AI-informed analysis” or “efficiency improvements with AI.” • Discussing AI adoption thoughtfully in interviews: “How is your organization integrating LLMs?” Emphasis on situational awareness—some employers may restrict AI tools. ________________________________________ [30:00–31:00] Interview Strategy & Outdated Job Ads Even without explicit AI requirements, interviewers appreciate curiosity and awareness. Many postings are outdated; candidates must initiate tech-related dialogue. ________________________________________ [31:00–32:00] Final Takeaways • Begin documenting practical examples of AI use now. • Even if not in the résumé, prepare anecdotes for interviews. • Reframe achievements to highlight outcomes driven by AI. • Continue refining language around AI literacy and tool use. Next MentorTime session will focus on Verbal Self-Reflection and the value of having a partner for professional growth. ________________________________________ Core Actions: 1. Capture measurable benefits of AI in your workflow. 2. Add credible, context-relevant AI examples to your professional profiles. 3. Use AI literacy frameworks for clarity. 4. Ask organizations about their AI practices during interviews. 5. Treat AI as a tool, not a title—demonstrate integration, not fascination.