←  Back to the analysis dashboard

AKKR Ascend · Capstone · Group 8 · Sales & Marketing

Meeting Notes

A running log of our working sessions — decisions, debates, and action items. 2 sessions logged, newest first.

Session 02August 2026

Working Session — Draft Framework & Section Ownership

Megan brought a full first-draft presentation framework — built by feeding all our survey data, AI results, peer-group examples and the capstone guidelines into Claude, then broken into timed, per-speaker sections. The team validated the structure, divided up the speaking parts, and set the deck up as a shared working document to refine over the next few weeks.

Who was there

Megan LangstonAaron WhitenerJanine NarvaliMark DavidsonSusan McGregorMelissa KorzunKen Allen
PresentPartialRegrets

Melissa and Ken were absent; the 30-minute recording goes to Melissa to review and confirm her section. Mark joined remotely from Yellowstone. Opened with quick team check-ins.

What we decided

The approach we agreed on

1Gauge
Four-stage GTM maturity model
Open on the maturity gauge (Ad Hoc → Emerging → Standardized → Scaled) and show that none of the PortCos are at Scaled yet — it sets the baseline the rest of the story moves against.
2Process A
AI Knowledge Exchange (2→3)
Gather working AI assets from people, vet and approve them, publish to one home, and have champions maintain them. Tool-agnostic — an intranet platform, a purpose-built vendor, whatever fits — with a live screenshot of what we are building as the example.
3Process B
Embedded Enablement Engine (1→2)
The learning layer: an AI-ready account executive who can research an account and hold an AI-about-AI conversation with a buyer. The two processes feed each other — the exchange supplies the skills the engine teaches, and learners contribute assets back.
Decisions locked
  • Use Megan’s Claude-built framework as the spine — it already breaks the 15-minute talk into timed, per-speaker sections with slides mapped to each.
  • Each person owns and builds their own section; word-smithing and graphics come later — lock the topics and flow now.
  • Keep it to ~2–3 minutes per speaker (15 minutes total) to leave room for rapid Q&A.
  • Company recommendations: AppSpace, Salesforce and VisiQuate start with enablement (Process B); the rest already have governance in hand and are ready for the knowledge exchange (Process A) first.
  • Ground the findings section in the survey data — AI adopted faster than the org can absorb, everyone building in private, and shared assets top the wish list — and keep the per-company AKKR data in the appendix.

Debates we settled

Debate
One combined deck or split the work?
✓
Each person owns a section and builds it in the shared slideshow; the deck becomes a living working document in the joint folder over the next 4–6 weeks, with names beside each slide and notes/comments left in-doc.
Debate
How do we avoid a playbook that’s stale the minute it’s written?
✓
Frame the deliverable as a continually-updating engine, not a static playbook — Mark’s point, reinforced by AE/AM retention of only ~9–12 months, which makes fast, repeatable ramp the whole value.
Debate
How do we assign the speaking sections?
✓
Match each section to a person’s expertise and style now, and let Melissa pick or swap after she reviews the recording — nothing is locked until she gives a thumbs-up in the WhatsApp chat.
Debate
Are we grounded enough to be credible?
✓
Yes — Mark cross-checked the survey results and portfolio-company materials ahead of the call; training, development and empowerment scored consistently high while risk scored low, which supports framing the story as movement from a baseline up the stages.

Follow-ups

Action items

Owner
Action
Target
Janine
Owns the opening — intros, agenda and methodology (how we ran the survey).
Draft by Sept 2
Aaron
Owns the fragmentation paradox and AI-maturity findings section.
Draft by Sept 2
Mark
Owns the enablement engine and flywheel (Process B), with the business-level framing.
Draft by Sept 2
Susan
Owns the AI Knowledge Exchange (Process A) — what the exchange looks like in practice.
Draft by Sept 2
Melissa
Proposed: ROI and per-company recommendations / strong close — to confirm after she reviews the recording.
Confirm via WhatsApp
Megan
Owns the maturity-model framing and decision signals; resend the recurring invites (Mark received only half — try his personal Gmail).
This week

What’s next

  • Refine the deck asynchronously in the shared folder; each owner develops their section and leaves notes/comments in-doc.
  • Next working sessions: Sept 2 and Sept 16 (biweekly).
  • After the Sept 2 session, assess progress and schedule a dry run with the presentation coach.
  • Get in early before the event for a focused rehearsal; use the late-Monday + Tuesday window to calibrate.
  • Send the 30-minute recording to Melissa and get her thumbs-up on the section split before finalizing.
Session 01July 2026

Working Session — Approach & Direction

Reviewed the AI Readiness Survey results and locked our capstone direction: build a GTM-specific AI maturity model, then deep-dive the knowledge-sharing and enablement levers that move a team up a stage.

Who was there

Megan LangstonMelissa KorzunAaron WhitenerJanine NarvaliMark DavidsonSusan McGregorKen Allen
PresentPartialRegrets

Mark and Janine joined for the first half. Opened with team check-ins and congratulations to Mark on his promotion to General Manager, Strategic Accounts.

What we decided

The approach we agreed on

1Assess
GTM-specific AI Maturity Matrix
Adapt the four-stage model (Ad Hoc → Emerging → Standardized → Scaled) and use our own survey as the scoring instrument. Levels are additive: a Stage 3 has mastered 1 and 2.
2Locate
Concrete GTM activities per pillar
For each pillar, show what the work actually looks like at each stage so a team recognizes itself instead of guessing. Break out Sales vs Marketing examples.
3Advance
Deep-dive: knowledge sharing & enablement
The main deliverable. Two stage-bridge processes — Embedded Enablement Engine (1→2) and AI Knowledge Exchange (2→3) — and how to drive them forward in a GTM org.
Decisions locked
  • Anchor everything on the four-stage maturity model and reuse AKKR’s stage language so our work reads as an additive AI layer, not a competing model.
  • The flagship deep-dive is knowledge sharing and enablement — the biggest gap in the data (69% can’t discover or reuse others’ work; 43% had no training).
  • Keep it tool-agnostic and grounded in our own survey data so it stays defensible and not commoditized.
  • Frame value as strategic alignment (Stage 3 = AI tied to business goals), not raw efficiency — we’re in the messy middle and still burning tokens on learning.
  • Ship a self-assessment toolkit in the appendix so any PortCo can place itself on the matrix.

Debates we settled

Debate
Are we duplicating AKKR’s existing department maturity models?
✓
No. Reuse their stages and position this as the AI-specific layer they said the original journey maps were missing. The capstone explicitly asks for framework ideas.
Debate
Is a knowledge exchange really “transformative”?
✓
Yes — it is the mechanism that moves a stuck org between stages and unblocks the non-builders. Defined as a stage-bridge, it is the transformation.
Debate
Won’t this feel commoditized?
✓
Make it tool-agnostic and anchor every recommendation in our survey findings. The data is the differentiator.
Debate
Do we claim efficiency / ROI now?
✓
Hold back. Lead with strategic alignment. The 2-billion-token rebuild with no business case is our anti-pattern exhibit.
Debate
One survey or two?
✓
One model, two lenses. Sales and Marketing motions differ, so show role-specific examples — and fielding to each team separately can lift response rates.
Debate
Playbooks go stale the minute they’re written.
✓
Treat the exchange as a living product: a named owner, a review cadence, and sunset rules — not a one-time document.

Follow-ups

Action items

Owner
Action
Target
Megan
Summarize the transcript, stand up the shared workspace + central slideshow, and start the GTM maturity matrix (survey data already in hand).
End of week
All
Contribute 2 individual PortCo recommendations each; confirm buy-in over WhatsApp.
Ongoing
Aaron
Explore fielding the assessment to isolated Sales and Marketing teams for higher response; owns the usage-analytics angle.
Next session
Team
Pull existing per-company AI survey data into the assessment and the stage definitions.
Next session

What’s next

  • Work asynchronously until the early-August meeting.
  • Aim for a solid draft by end of August / early September.
  • Book the AKKR operating specialist (Chad Bureau · Sales; Rachel Spasser / Wendy Ho · Marketing) and coach Matt with a month to spare.
  • Use this dashboard as the shared working space.