Roast & Rise

Riseplan from Roast & Rise

Trust, Anxiety, and the AI Conversation With Your Team

A practical path for managers to tackle AI job fear, model constructive use, and make skills investment visible.

Learn to break the silence around AI at work—name the real risks, run trust-building team conversations, model healthy AI use visibly, and make your commitment to skills unmistakable. Walk away with scripts, checklists, and a skills plan designed for trust, not false reassurance.

An overhead view of a long, warmly-lit meeting table with scattered, unmarked documents, blank cards, and a single open folder. Pools of soft light fall over the artifacts; generous negative space at the table edges suggests silent anticipation and the opportunity for conversation. No people, handwriting, or visible text. Burnt orange and brand white palette signal warmth and clarity.
A cinematic opening: the table is set for honest AI conversations. Artifacts of trust—scripts, checklists, worksheets—rest in warm, expectant light, inviting the viewer to cross from silence into action.

Course thesis

When managers avoid the AI conversation, employee anxiety rises and trust plummets. The 2026 Microsoft Work Trend Index shows that job security has never felt so fragile—and that manager silence, vagueness, and hidden experiments make it worse. But the same research proves that managers who acknowledge the risks, model AI use, and focus visibly on upskilling can spark new trust and readiness. This plan teaches practical moves for talking about job fear, showing your AI work, and investing in team skills when it matters most.

What you leave with

By the end, you’ll know how to lead an honest AI conversation, address job-security fear, model healthy AI use, and make skills investment visible—for a team that trusts you more and experiments faster.

For

Founders, frontline and middle managers, HR and people leaders responsible for navigating their teams’ AI fears, building trust, and delivering psychologically safe conversations.

Workflow

Team members ask if their jobs are safe or stay quiet out of fear; the manager either avoids the topic or offers empty reassurance. The new workflow: the manager addresses fear openly, runs a structured trust conversation, uses AI in the open, and launches a visible upskilling track—with outputs the team can see and respond to.

Change

Move from silent avoidance or vague reassurance to naming anxiety directly, modeling AI use with intent, and making real skills investment visible—sparking both trust and readiness.

What you can do

Use these as checks while you move through the plan.

Recognize and address explicit and unspoken job-security fears about AI.

Lead a team conversation that surfaces anxiety and builds trust using practical structure.

Model visible, grounded AI use as a manager—not just privately, but in team settings.

Design and communicate a real, visible plan for investing in team skills.

Spot and avoid the traps: corporate vagueness, false reassurance, and silent experimentation.

Chapters

01

Face the Fear: Naming Job-Security Anxiety About AI

Managers who avoid talking about AI and job security create more anxiety. This chapter teaches you to name the fear head-on—ending silence and unlocking honest conversation. Use the Fear-Naming Conversation Opener Script to surface unspoken concerns and demonstrate real leadership.

A single blank conversation script page placed at the forefront of a meeting table, an unused pen set alongside but not touching it. The paper edges catch warm orange light; background fades to shadow and empty chairs, emphasizing the pending, honest conversation. No people, handwriting, or visible text.
A fear-naming opener script, left visible but unsigned, sits at the edge of a meeting table—its position signals a pause before voice. Light highlights the readiness to face unspoken concerns.

Why this matters in the workflow

Too many managers dodge the hardest question: “Will AI take my job?” You feel the tension: nervous glances, careful language, silence when the topic comes up. The 2026 Microsoft Work Trend Index is blunt—only 22% of workers strongly believe their jobs are safe from elimination. When leaders avoid the issue, anxiety grows. Rumors fill the gap. Trust crumbles.

Naming the fear doesn’t make it worse. It dissolves the guessing game. An honest opener signals respect: "I see what you're worried about. Let's talk about it together." This is the starting move for every other trust-building step you’ll take. Without it, team discussions about AI will be surface-level at best—or just another silent, anxious meeting.

The working model

Quality checklist

States a specific, real team concern—avoids vague language.

References the Microsoft Work Trend Index (with relevant number).

Does not offer false reassurance—admits uncertainty where true.

Shows personal investment (shares a real observation/question from the team).

Invites honest input and pauses for responses.

Includes at least two questions that draw out team fears.

Common mistakes

Making empty promises or guarantees the manager can’t keep.

Using abstract business jargon instead of describing concrete concerns.

Failing to reference real data, making fear feel personal instead of common.

Dominating the conversation without pausing for input.

Checkpoint

Did you draft a personalized opener that names AI job fears directly and references the real numbers? Are you ready to try it in your next team meeting?

Exercise

Draft and Personalize Your Fear-Naming Conversation Opener

In 15 minutes:

  1. Open a blank doc and copy the script template below.
  2. Fill the [bracketed] sections with your team’s context—add one real example or question that you’ve heard (or suspect is being whispered).
  3. Include the Microsoft Work Trend Index number that best fits your team.
  4. Practice reading it aloud. If possible, ask a peer or mentor to listen and give feedback—aim for your own words, not a stilted read.
  5. Mark your calendar for a team meeting or check-in where you’ll use this opener.

Output: Your draft Fear-Naming Conversation Opener, ready to deliver live.

Bonus: Write two questions you’ll use to open the floor after sharing your script.

Use this at work tomorrow

Draft your opener using the template today. Set time in your next team meeting to say it, pause, and invite real concerns.

02

The Trust Script: Leading Open Conversations on AI

Equip managers with a ready-to-use script and checklist for holding open, trust-building team conversations on AI. Surface hidden anxieties and real hopes, setting a new baseline for trust.

A small bundle of blank checklist sheets and scattered note cards arranged in a gentle arc on a table surface, each card partly illuminated by warm light suggesting readiness to listen. Empty space invites participation. No handwriting, text, or people present.
A trust conversation checklist and multiple blank bullet-note cards arranged as if to collect honest team input—ready for use but untouched. The visual implies openness to concern and structure in the conversation process.

Why this matters in the workflow

Job-security fear breeds in silence. According to Microsoft’s 2026 Work Trend Index, only 22% of workers feel secure about automation, and the silence or dodging from managers makes this fear cut deeper. Conversations about AI, if avoided, create a vacuum filled with rumors or anxiety, not clarity. Open dialogue isn’t a nice-to-have—it's the trust floor that everything else stands on. When a manager runs a visible, structured AI conversation, employees report up to 30 points higher trust in AI decisions—and more readiness to learn.

The working model

A trust-building AI conversation has these rules:

  • Treat every concern as valid.
  • The work is to listen, not reassure or solve instantly.
  • Honest disclosure trumps hollow positivity.
  • Structure holds the safety net: the team sees the steps and knows you’re not hiding the topic.

Quality checklist

The script was followed—conversation was about surfacing, not solving.

Everyone present was invited to speak; nobody was silenced or ignored.

Live notes captured what was said, not who said it—protecting anonymity.

Summary and next steps were shared back to the team within 24 hours.

At least one follow-up item or next step is clear to all.

Common mistakes

Turning the conversation into a Q&A with leadership defensiveness.

Dominating the discussion—instead of drawing out quieter team members.

Ignoring surfaced fears or not capturing them in writing.

Skipping the follow-up (sharing the summary and next steps).

Failing to create a psychologically safe space—team members worried there was a "right answer."

Checkpoint

After running this conversation, did your team surface at least one real question, hope, or fear—and did you close the loop by sharing back next steps?

Exercise

Run a Team AI-Trust Conversation Using the Script and Checklist

Objective: Hold an honest team conversation about AI using the script to surface real concerns and hopes—and document what you learn.

Steps
  1. Schedule a 15–30 minute team meeting (do not tack it onto another agenda item).
  2. Use the Trust Conversation Script (see template below) to guide the meeting.
  3. Open by stating the purpose—make it clear this is about surfacing real feelings and questions, not grading opinions or announcing changes.
  4. Invite everyone to share at least once—track this lightly.
  5. Take live notes of what is said (not who said it). Capture questions, hopes, fears as categories.
  6. After the meeting: share a written summary with the team and name one next step or follow-up item.

Output: A one-page summary of the conversation: categories of fears, hopes, questions surfaced, and next steps.

Use this at work tomorrow

Book a dedicated meeting this week, use the script, and start capturing team AI hopes and fears—trust grows in conversation, not in comfort.

03

Model It: Making Your AI Use Visible

Managers grow trust by using AI in the open, showing what works and what fails, and being explicit about their thinking—no hidden solo experiments.

An open, blank manager's workflow checklist beside a notepad with visible process steps, both inviting inspection. A laptop sits closed in the background—suggesting digital process but not showing screens. Warm brand light focuses on the artifacts; the scene is devoid of human presence and completed text.
An open checklist and a visible 'in-progress' work pad are positioned for a shared screen moment—inviting critique, not showing a polished end. Light reveals honest, shared experimentation.

Why this matters in the workflow

The Microsoft 2026 Work Trend Index draws a straight line:

  • When managers actively model AI use, teams report a 17-point lift in AI value, 22-point lift in critical thinking, and 30-point lift in trust (source: Microsoft 2026).
  • Hidden or solo experiments keep everyone guessing. Most knowledge workers already worry their job isn’t safe—especially when big changes happen behind closed doors.
  • When you work with AI, and bring your team along for the ride, you shrink the trust gap and cut through rumor.

The working model

Visible modeling means three things:

  1. Demonstrate. Use AI for real team work during meetings—screen share, narrate, and let others watch the real mechanics (and your judgment).
  2. Narrate. Don’t just show the tool—narrate your choices, doubts, and limits. Are you checking AI output for errors? Did it help or waste your time?
  3. Debrief. Invite commentary, questions, and doubts. Name what surprised you. Make space for skepticism and improvement.

Quality checklist

The live demo used a real, relevant team task—not a cherry-picked or trivial example.

The manager narrated both the strengths and limits of AI use, including moments of doubt or correction.

The process (not just final outputs) was visible—screen shares, prompts, edits.

The manager explicitly invited critique and discussion from the team.

New insights, problems, or concerns surfaced during or after the demo.

Checklist is fully completed with honest notes and at least one area for next-step improvement.

Common mistakes

Picking a safe, PR-ready task rather than authentic team work.

Only showing polished results—never the live, messy process.

Shutting down critique or questions (intentionally or not).

Hiding uncertainty, making AI look infallible, or acting as an 'AI evangelist.'

Failing to ask for (or document) reactions afterwards.

Checkpoint

Did you demonstrate an AI workflow in the open, narrate your doubts, and debrief with your team—using the checklist fully?

Exercise

Run a Visible AI Workflow in Your Next Team Meeting

Steps
  1. Pick a real task for your next team meeting (e.g., summarize key feedback, draft a proposal line, research a competitor, prep a to-do list).
  2. Prepare your Manager AI Modeling Checklist (see template).
  3. During the meeting, screen-share and narrate your process as you use an AI tool (include prompts, edits, and skeptical checks).
  4. Debrief live: Invite your team to share what worked, what didn’t, what felt clear, and where they’d still have doubts.
  5. Capture your team’s reactions and your own learning.
Output

Fill in the Manager AI Modeling Checklist after your session. Use it to score your own modeling, note surprises, and commit to one improvement for next time.

Use this at work tomorrow

Run your next AI-powered workflow on a screen share, narrate the process and mistakes, and invite real critique from your team.

04

Safety to Experiment: Signals and Practices That Build Trust

Learn how to make experimentation feel safe by sending clear signals, naming mistakes as learning moments, and replacing silence or blame with honest sharing.

A blank psychological safety worksheet rests atop a softly lit binder with clean index tabs, open to the first divider—each inviting addition. The arrangement signals openness and recorded learning. No handwriting, text, people, or digital screens.
A psychological safety worksheet and an open log binder are present in soft, even light—suggesting a shared, non-judgemental record of experiments and learnings.

Why this matters in the workflow

There’s a ticking risk in every team: one failed AI experiment, one clumsy question, and people stop trying. According to the Microsoft 2026 Work Trend Index, teams with managers who actively create psychological safety around AI are up to 20 points higher in AI readiness and 1.4x more likely to be high-frequency users. Without explicit safety signals, silence and blame win. With the right moves, you create a routine where everyone brings their experiments—and their stumbles—into view.

The working model

Psychological safety isn’t a speech, or a blanket assurance—it’s built by small, public acts. Safety is proven real when people share their unfinished work, admit what didn’t go as planned, and get curiosity instead of consequences in return. Your job is to send unmistakable signals: mistakes are learning, experiments are expected, nobody goes solo.

Quality checklist

Manager shared a real imperfection or learning moment first.

At least one team member contributed an experiment or challenge.

Responses were curious and non-judgemental—no fixing or correcting.

Worksheet clearly lists visible safety signals and areas for improvement.

Summary is posted in a visible team space, not hidden.

Common mistakes

Manager only shares polished stories—no real vulnerability.

People don’t participate because the session feels forced or unsafe.

Session ends with critique or blame, not learning.

No public record of lessons learned—signals fade after meeting.

Skipping the follow-up makes the safety talk ring hollow.

Checkpoint

Have you run a live experiment-sharing session and captured the visible safety signals—and gaps—in your worksheet?

Exercise

Run a Team Experiment Sharing Session and Create a Safety Signals Worksheet

Goal

Hold a 15-minute session where team members share an AI experiment—win, miss, or question—and document the safety signals in your workflow.

Steps
  1. Schedule 15 minutes in your next team meeting for AI experiment sharing.
  2. Open by sharing your own experiment, including what didn’t work as planned.
  3. Invite team members to volunteer experiments or learning moments—encourage imperfection.
  4. Use only questions and curiosity when responding. Avoid instant solutions.
  5. After the meeting, fill out the Safety Signals Worksheet: what signals did you send? What did the team contribute? Where did safety crack or hold strong?
  6. Post the worksheet or summary in your team’s shared space for visibility.
Deliverable

Complete the Safety Signals Worksheet below.

Use this at work tomorrow

Block 15 minutes in your next meeting for experiment-sharing and post the completed safety worksheet where everyone can see.

05

Visible Investment: Designing and Sharing a Real Skills Plan

This chapter shows you how to craft and reveal a real, practical plan for AI skills investment—moving from vague promises to visible action. Learn why teams need proof, not platitudes, and how a shared plan builds trust and job security.

A paper folder labeled in a brand color block (no visible text), with a blank skills plan template and crisp feedback sheets arranged to show they’re ready to be filled and shared. Warm orange and white light covers the artifacts; space around them signals accessibility and transparency.
A visible skills investment plan: a shared folder, a plan template, and an empty feedback sheet, all seen under warm light. This signals real commitment—anyone can see and touch the team’s learning path.

Why this matters in the workflow

Job fear is toxic. But empty statements about "upskilling" do nothing. The Microsoft 2026 Work Trend Index found employees who see real investment in their skills are 5.3x as likely to feel their job is secure. Platitudes don’t move trust. Your team needs proof that there’s a path forward for them, not just the company. A visible plan, with clear outcomes, signals that you’re investing for real—raising security and readiness, not just shifting the burden of learning onto them.

The working model

A skills plan that raises trust is specific, public, and directly tied to team needs. It includes:

  • What skills matter (not just "AI" as a blob, but real tools, workflows, or core capabilities)
  • How people will learn them (resources, programs, time carved out for learning)
  • How you’ll know progress (observable outcomes, not seat time)
  • Where to see or ask about it (a living, visible document—never an HR black box)

Quality checklist

Output is live, visible, and accessible to the whole team—not a private or buried doc.

Skills listed are real, specific, and relevant to the team’s current or coming work.

Each skill has a clear resource AND time commitment set (not ‘as you find time’).

Plan names a visible output for each skill—something anyone can check or discuss.

Feedback is invited explicitly; the plan is a living document.

You gather at least one round of direct input after sharing.

Common mistakes

Announcing a plan but never publishing it in a visible, editable space.

Listing skills that are too broad, generic, or distant from current work.

Focusing only on learning resources but offering no time for execution.

Failing to ask for feedback or update the plan based on team response.

Letting the plan fade after launch—no follow-up or visible review.

Checkpoint

Can everyone on your team see, touch, and name a skill-building investment in their work—right now?

Exercise

Create and Share a Real Team AI Skills Investment Plan

You have 15 minutes to move from idea to action.

  1. Pick a format your team uses: doc, Notion, team chat pinned post—anything everyone can access.
  2. List 2–3 specific AI or automation skills your team needs in the next 1–3 months. You can ask the team for input if you have time; otherwise, use your best judgment but be specific.
  3. For each skill, set these points:
  • What’s the resource or training? (link, session, peer, or external)
  • What’s the dedicated time? (meeting, async, blocked calendar)
  • What’s a visible output? (draft, demo, review note, peer feedback)
  1. Add a note at the top: “This plan lives here. Please comment, question, or suggest updates.”
  2. Publish and share the link or location with your team.
  3. Invite feedback at your next team meeting or in chat.

Ready for your plan to get seen and used? Build it now—the template below gets you started. Copy, paste, and fill in. Then move.

Use this at work tomorrow

Draft your team’s AI skills plan, post it for everyone to see, and ask for feedback by the end of the week. You move trust from promise to proof.

30-day path

Week 1: Prepare and deliver the fear-naming opener; sense the silent concerns.

Week 2: Run the trust-building team AI conversation; use the script and checklist.

Week 3: Model AI use in an open team workflow or meeting; invite questions.

Week 3–4: Facilitate a team share-out of failed or successful AI experiments.

Week 4: Build and circulate a visible, practical skills investment plan with the team.

End of Month: Pulse survey—Did trust, confidence, and reported AI readiness change?

Success signals

Number and depth of job-security concerns voiced by the team after conversation (indicates safety).

Team trust pulse before and after structured AI discussion (survey or quick check).

Observed manager use of AI in visible settings (logged or recorded example).

Count and diversity of team experiments shared publicly after psychological safety moves.

Clarity and specificity in the shared skills plan (confirmed by team feedback).

Team-reported confidence in the manager’s commitment to their skills and security (short survey or check-in).

Reflection prompts

Where does this topic show up in real work?

What behavior should change first?

What evidence would prove this Riseplan worked?

Manager checklist

Choose one owner for the behavior change.

Use the exercise on live work.

Review the output before scaling the habit.

Decide what changes after 30 days.

Want this shaped around your company?

Risey can research your company foundation first, then build a version of this path around your real workflows, customers, and culture.

Start with your company