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Happy Monday!
Somebody on your team will tell you this week that AI has made them faster. They will be telling the truth. Four-fifths of the people in McKinsey's 2026 State of AI survey, published 25 August, say exactly that.
80% report AI improved their individual productivity. Half say it helps them make better decisions. Adoption is no longer the problem: 44% now report AI scaling across the enterprise, and the share using it in three or more functions climbed from 51% to 56%.
Then you get to the money.
The share of respondents reporting that AI has contributed to EBIT is essentially unchanged from a year ago, at 37%. And the group McKinsey calls high performers, the ones attributing at least 5% of EBIT to AI and describing the impact as significant, stayed flat at about 6% of all respondents.
A full year. Every tool got better. The number did not move.
There are honest reasons a gain takes time to reach earnings, and about 20% say AI operating costs already constrain their use. Fine. But if your 2027 plan is being built on how fast the team feels, you are budgeting against the 80% and reporting against the 37%.
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TALK ON THE MARKET
Anthony Kennada, announcing on 24 August that he has joined Armada as Chief Marketing Officer:
He goes on to say the buildout is hitting a wall, that energy is the bottleneck, and that communities are pushing back on centralized data centers even in places that never say no to construction.
A CMO whose first public sentence in the job is about power supply. Worth noting he has just joined a distributed-infrastructure company, so the quote argues his own book. It is still where the category has moved.
NUMBERS MATTER
99%. That is the share of self-identified AI bots that USA Today Co currently blocks, according to Digiday on 26 August, while it reformats its content to attract licensing deals from the ones it lets in.
The gate is shut, and the shop window is being redressed at the same time.
Have you heard about Kling, Seedance, or DeepSeek for marketing? Only vaguely?
A massive shift is underway: the Chinese AI ecosystem is using frontier open-weight models to quietly replace $1,500/mo video tools and agency retainers for pennies.
ShanghAI is your insider gateway. Every Monday, 4,000+ founders and marketing leaders read our 3-minute brief to deploy these exact tools, slash campaign costs, and automate creative pipelines.
DAILY PROMPT
You are a strategic marketing finance advisor helping a [COMPANY_TYPE] allocate their annual marketing budget across channels and initiatives.
## Context
- Total Annual Marketing Budget: $[BUDGET_AMOUNT]
- Current Revenue: $[ANNUAL_REVENUE]
- Primary Business Goal: [PRIMARY_GOAL] (e.g., customer acquisition, retention, market expansion)
- Target Customer: [TARGET_AUDIENCE_DESCRIPTION]
- Industry/Vertical: [INDUSTRY]
- Current Market Position: [MARKET_POSITION] (e.g., market leader, challenger, emerging)
- Planning Horizon: [TIMEFRAME] (e.g., fiscal year, calendar year)
## Current Channel Performance (if available)
[PROVIDE EXISTING CHANNEL DATA: channel names, spend, ROI, conversion rates, CAC, or state "no historical data available"]
## Strategic Priorities
Rank these 1-5 in importance to your business:
1. [PRIORITY_1]
2. [PRIORITY_2]
3. [PRIORITY_3]
4. [PRIORITY_4]
5. [PRIORITY_5]
## Constraints & Considerations
- Team Size: [TEAM_SIZE] (e.g., 3 people, 15 people)
- Technology Stack: [EXISTING_TOOLS] (e.g., HubSpot, Salesforce, in-house)
- Geographic Focus: [GEOGRAPHY] (e.g., US only, EMEA, global)
- Seasonal Variations: [SEASONALITY] (e.g., Q4 peak, summer slump)
- Competitive Landscape: [COMPETITIVE_CONTEXT]
## Task
Provide a detailed budget allocation recommendation that includes:
1. **Channel Breakdown** - Recommended percentage allocation across digital advertising, content marketing, sales enablement, events, partnerships, brand building, and other relevant channels. Justify each allocation based on the context provided.
2. **Quarterly Distribution** - Show how budget should be distributed across Q1, Q2, Q3, and Q4 to align with business goals and seasonal factors.
3. **Initiative-Level Allocation** - Break down major initiatives within top channels (e.g., within digital advertising: paid search, social, display, video).
4. **ROI Assumptions** - State the expected ROI, CAC, and payback period for each major channel based on industry benchmarks and the company's position.
5. **Risk Assessment** - Identify budget allocation risks and recommend contingency reserves (suggest 5-10% of total budget).
6. **Quick Wins vs. Long-Term Bets** - Allocate budget between immediate revenue-generating activities and longer-term brand/market development.
7. **Implementation Roadmap** - Provide a 90-day activation plan showing which channels launch first and why.
8. **Success Metrics** - Define 3-5 KPIs to track budget effectiveness and recommend review cadence.
Format the response as an executive summary followed by detailed tables and justifications. Use clear percentages, dollar amounts, and actionable recommendations.Use this when you have to defend next year's number and the only evidence you have is that everyone feels quicker. It forces you to attach each line to an outcome you would actually be measured on, which is the exact conversation the McKinsey gap is about to start in your finance meeting.
CMO CORNER
Your involvement should shrink as your system matures.
Here is the awkward reading of that 37%. If AI made your people meaningfully faster and none of it reached the P&L, the time went somewhere. Usually it goes back into the same review loops, the same approval queue, the same three people who have to see everything before it ships.
You automated the drafting and left the bottleneck exactly where it was. Speed only becomes margin when the system needs less of you, not when the first draft arrives sooner.
→ We provide consulting services for CMOs on AI strategy for marketing teams through our Teamless offering.
TOOL UPGRADE
If the productivity is real and invisible, the instrumentation is the job:
Diginius — best for pulling campaign data from every channel into one view, so the return is arguable rather than anecdotal. Try Diginius here →
Copper — best for teams whose CRM is really Gmail, capturing contacts and meetings without anyone typing them in. Try Copper here →
Aira — best for turning buying signals into pipeline you can point at, instead of activity you can only describe. Try Aira here →
→ We have 300+ curated, filtered, and categorized AI tools in our directory. Browse to find the best ones that help your marketing team.
LEARN THIS
For the meeting where somebody asks what the AI spend returned and "the team is faster" is not going to survive the room: AI Marketing ROI.
It covers what to measure when the gain is real but diffuse, and how to say "we do not know yet" without losing the budget. For leaders who have to convert a productivity story into a number a CFO recognizes.
→ We publish workshops, courses, guides, manuals, and more on AI marketing for free. Browse our learning resources for free.
BRAND SLOP
CGTrader has sold 3D models since 2011. More than two million of them.
AI-generated uploads have flooded the platform, and 404 Media reported on 12 August what happened next: almost nobody bought them. The marketplace's own report puts it plainly.
Buyers are voting with their wallets, and AI-generated content is struggling to compete. The upload numbers alone would suggest a takeover. The revenue numbers say otherwise.
Alexander Spivak, a 3D artist who sells there, is not against the technology. He just says he has not yet found a way to collaborate with it.
This is the McKinsey gap with a price tag attached. Supply went vertical, willingness to pay did not follow, and the people refusing to pay aren’t activists. They are customers with a budget and a preference.