Hey there,
Ever notice how AI shows up everywhere in board slides but feels fuzzy when you ask what it changed in yesterday’s operations? With budgets climbing and risk headlines piling up, a simple, repeatable check‑in on where AI money goes, what outcomes it should move, and what might quietly derail it can keep execution grounded while you build the data, training, and infrastructure foundations that actually make scale possible.
Take a moment to see how a short AI investment and risk debrief can make your roadmap feel far less theoretical and far more tied to real performance.
In this issue:
Playbook of the Day
How to Run a 15-Minute AI Investment & Risk Debrief
Goal: Turn current AI spend and risk signals into clear operational decisions and metrics.
Who: COO, finance/FP&A lead, data/AI representative, and 1 rep from a major impacted function. Run monthly or after big AI funding/rollout calls.
Before the debrief (3 mins):
Each person adds 2–3 bullets: where AI money is going, what outcome it should drive, and what feels at risk.
Host flags anything tagged as the following: “high spend,” “low clarity,” or “adoption risk.”
During the 15 minutes:
AI Spend in 60 Seconds (4 mins): Each lead shares biggest AI investment, one target outcome, and one key dependency.
Adoption & Performance Risks (6 mins): Review risk tags and assign one mitigation per item: training, workflow changes, & governance).
Wire AI Into the Dashboard (3 mins): Host confirms 3–5 AI impacted metrics & owners, plus the next review date.
Rules: No new AI projects, no vague “innovation”—only funded initiatives, concrete risks, and measurable outcomes the COO will own in 2026.
Latest News
AI Budget & Risk Guide for Operations 🧠
Published: 01/21/2026
Facilitate Magazine outlines 3 practical ways facilities managers can keep buildings operations smoothly during the holiday season, when foot traffic patterns changes, staffing declines, and systems are under unusual strain. The piece focuses on getting ahead of the rush with clear schedules and vendor plans, tightening up safety and security checks for untracked structures. Using the lull to run essential maintenance without disrupting core operations.
Upside: COOs get a benchmarked roadmap from 250+ execs to audit readiness, route budgets for scale under productivity & resilience and embed AI KPIs into dashboards, skipping hype for execution that ties ops to enterprise goals without siloed experiments.
Impact: Master this, and AI shifts from risk to revenue driver, proving COO value through measurable outcomes like cost cuts and efficiency in CRE ops; leaders who operationalize now build governance moats, turning 2026 trends into sustainable edge over laggards scrambling on adoption stalls.
🧑💼 Asia’s COOs Unveil a New AI Game Plan
Published: 01/16/26
FutureIoT has outlined how AI flips Asia’s COO role from cost-focused efficiency to a constant revenue orchestration, with McKinsey data showing 68% of APAC ops leaders gaining 20-30% planning capacity using automation for resilience plays. Simon Bernie of Teceze defines AI beyond genAI hype. Machine learning, automation, & analytics to unlock predictive ops as table stakes in Vietnam/Singapore hubs, despite Gartner’s warning that just 35% have data governance ready for scale.
Upside: COOs can target quick wins in siloed supply chains for real-time visibility, KYC acceleration in finance, and agentic AI in compliance/accounting, evolving KPIs to OKRs that track value over activity while blending large vendors for stability with nimble partners for speed. It stresses embedding AI into business models onto working teams, automating repetitive tasks to grow revenue without headcount spikes in tight talent markets.
Impact: Asian COOs who nail data foundations, fast iteration, and ecosystem partnerships turn operations from cost centers into agile growth engines, countering legacy burdens to deliver wide responsiveness positioning firms to outpace rivals as Gartner predicts 70% APAC disruption by mid-2026.
🤖 HR Co-Leads Ops Revolution
Published: 01/08/26
HCA Mag warns of a readiness chasm as 98% of firms push AI urgency but 91% lack culture prep, urging HR to co-lead with COOs on people-centric transformation per AIHR’s HR Priorities 2026 Report. Dr Marna van der Merwe stresses AI’s prime wins in reshaping work design for productivity and innovation, yet most ops prioritize automation over workforce alignment.
Upside: AI has unlocked 120+ hours/year per employee (30% gains), demanding CHROs reinvest in proven and tested strategiesv63% more effective per Deloitte, transitioning from headcount to flexible skills amid 77% execs eyeing disruption navigation. HR pros (just 35% AI-ready) must integrate via cross-functional upskilling beyond fragmented self-learning.
Impact: Impact: HR evolves from silos to strategic partners fueling sustainable ops intelligence, ensuring AI capacity drives growth over margins. Crucial for COO teams building trust, culture, and fluency to hit 59% near-term impact mandates without stalling innovation.
Prompt of the Day
COO Task Efficiency Radar Prompt
Trigger Event | Action | Use Case Example |
|---|---|---|
Start of the week. | List top tasks, owners, and success metrics | Align on 8–10 priority tasks where AI/automation can cut cycle time. |
Before leadership / ops sync | Summarize status, blockers, and dependencies | Surface slow handoffs and propose workflow or tooling fixes. |
When a project feels “cluttered” | Identify low-value work, rework, and context shifts | Strip duplicate reporting and busywork to free team capacity. |
After a surprising incident | Capture what happened and where effort was wasted | Spot preventable rework and design new guardrails or playbooks. |
Month-end / quarter-end planning. | Map workload vs. capacity and automation options | Decide which workflows to automate, outsource, or defer to protect focus. |
Prompt
Act as my task-efficiency radar. Based on this snapshot of our current projects, workflows, and capacity, (1) flag the top 3 task or workflow bottlenecks for the next 30 days, (2) show me early warning signals that execution efficiency is slipping this week, and (3) suggest 2–3 concrete changes (automation, delegation, or simplification) I can assign today to recover time and throughput.
A mediocre strategy executed brilliantly is often better than a brilliant strategy executed poorly.
One last Thing
AI budgets and risk reviews can be a strategic window, not just a compliance exercise. Getting ahead of where funds flow, how teams adopt new tools, and which metrics prove value can cut wasted spend, reduce failed pilots, and improve the day‑to‑day experience of people who depend on these systems to do their work.
The most important AI progress often happens in the quiet discipline of these check‑ins, long before the big case studies appear—and this is one of those moments.
Until next edition,
Chloe Rivers
Editor-in-Chief
COO Intelligence
P.S. Interested in sponsoring a future issue? Just reply to this email and I’ll send packages!