Hey there,
Have you noticed how AI looks brilliant on the demo and then goes estranged on actual results? With tech dominating across industries, recent discussions and debates offer real insights toward how these factors will impact COO & HR management in the long run.
Utilize this moment to gain understanding from leaders across industries and how they cope with discipline & secure investment returns.
In this issue:
Playbook of the Day
COOs Secures AI Return On Investment 🪙
Goal: Focusing on overcoming adoption setbacks, enforce measurable returns, and setting operations as AI's profit engine currently decline amid $2.5T globally.
Who: COO, CFO, CTO, an AI department lead, and 1 operations head for each high ROI sector (R&D, supply chain). Weekly meeting, 15 mins max, once a week.
Before the debrief (3 mins):
Each lead logs 2–3 bullets in shared dashboard: AI tool deployed, efficiency gain or risk hit, an evaluation for tomorrow's blocker.
COOs/HR comprehensively scans for Return On Investment gaps or declines, taking note of current 26% implementation.
During the 15 minutes:
AI Wins & Metrics Today (4 mins): Each lead reports top metric: cost save, revenue lift, or risk dodged (only 12% CEOs see both).
Top Risks & Barriers Tomorrow (6 mins): Tackle Top 1 ROI disruptions, skill incompetence (68% CFOs), & cybersecurity (80% barrier).
Scale Plan Lock-In (3 mins): COO assigns 3–5 actions: business case for costs, C-suite collab boost by 50% CFOs & stronger ties.
Rules: None of the over-exaggeration, and an actual unavoidable pilot gaps. set strict business performances with clear savings & efficiency like Match Group's standard. Record operations: growth acceleration, tax penalties, & optimal decisions.
Latest News
HR Debates Tech Adoption Challenges ⚙️
Published: 01/22/2026
The CFO Dive discusses why 2026 is a rocky year for AI: global expenses are expected to reach $2.52 trillion, and only 12% of CEOs yet acknowledge both cost and revenue. Autonomous AI has already decreased from 42% to 26% as companies paused rushed programs, insisting on actual business managing, monetizable ROI, & stricter administration.
Upside: COOs and HR are able to utilize these factors and challenges, such as ROI vagueness, 80% citing cybersecurity, & 68% flagging incompetence. By doubling down more on delivery, boundaries as safety measures, and ops improvements for steady maximization.
Impact: Departments measures AI beyond productivity, bounding it to growth, savings, and safety measures. Pairing it with automation and optimization will turn AI management and ROI into durable and executable operational results.
🧑💼 Davos 2026 on HR’s New AI Mandate
Published: 12/16/25
Recent reports on People Management states that during the Davos 2026, leaders stopped debating on whether AI is capable to change the course of workflows, and focused rather on how fast they can redesign organizations around it instead. For HR & COOs; focus on competent staffing, & treat operation improvements as a consistent discipline.
Upside: These recent insights provides COOs and HR a concrete & precise ideas on integrating digital systems, rebuilding structures for optimization, redefining ideas with the use of recent tech strategies and manpower management for competence across departments.
Impact: Davos CEOs were not trying to come across as biased over traditional workflows; they insistently expect HR and leaders to revamp work itself as AI adapts to tasks & careers.
Tech Restructures Traditional Procedures 🤖
Published: 01/26/2026
The Josh Bersin Company predicts that 2026 will bring the biggest HR reformations over the past decade as AI assistants evolve into influential “superagents” that can automate more than 100 HR activities across staffing, training, performance, and operational management. HR headcount could fall by about 30%, forcing CHROs to quickly adapt HR’s structure.
Upside: HR & COOs should focus on a list with 11 proven adaptive actions. so '“superagents” become a strategic backbone, such as building AI stacks, strategizing restructures, build better staff relations, and preparing for major HR tech vendor disruption for risk oversight.
Impact: Organizations that move first are expected to run “superworker” models by the end of 2026, with higher revenue and profit per employee and HR focused less on transactions and more on leading the AI transformation for the whole business.
Prompt of the Day
Optimal COO-HR Workflow Radar Prompt
Trigger Event | Action | Use Case Example |
|---|---|---|
Start of the week. | List top AI use cases, current metrics (cost, revenue, risk), and any ROI gaps. | Quick map of which AI tools are paying off, which are stalled, and where ROI is still fuzzy. |
Before the Thursday AI sync | Capture 2–3 bullets per function: tool deployed, efficiency or risk impact, tomorrow’s scaling blocker. | Clean inputs so the 15‑minute debrief stays on hard numbers, not status chatter. |
When an AI test run seems unstable | Note adoption issues, skills gaps, data or workflow problems, and security concerns. | Decide whether to fix, harden, or kill a pilot that isn’t meeting the higher bar for AI spend. |
After a major AI incident or surprise | Log what happened, which data, systems, and people were affected, and how it was handled. | Turn an AI misfire into governance and training upgrades for COO, HR, and IT. |
Month‑end / quarter‑end AI review | Summarize AI ROI (savings, revenue, risk avoided), workforce impact, and next capability bets. | Set the AI scale plan for the next 30–90 days and 2–3 moves to boost skills, trust, and performance. |
Prompt
“Act as my AI ROI and workforce optimizer. Based on this snapshot of our current AI use cases, metrics, and talent signals, (1) flag the top 3 bottlenecks blocking AI ROI or safe deployment in the next 30 days, (2) surface early warning signs on skills, adoption, and trust I should watch this week, and (3) suggest 2–3 concrete actions I can assign today to improve returns, close gaps, and keep our AI–people model sustainable.”
Complexity is the enemy of execution. Keep it simple, and you’ll move faster.
One last Thing
Though AI can be a disciplined profit engine, it should not only be promising just as experimental demos; Securing ROI & getting ahead of metrics, competence, and operations now lets you expand further on what works—and restructure workflows “superagents” on your terms, not the vendor’s.
AI becomes a profit engine when you measure outcomes, work on competence, and confidently expand or terminate tools for proficiency.
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!