AI-Powered Growth

May 20, 2026

Captain's log

Sorry for the delay in this week's delivery. Gosh, kind of a lot has happened with search over the past 24 hours.

Google I/O dropped yesterday, and if you were watching, the signal was impossible to miss. AI Mode has crossed one billion monthly users. Queries are more than doubling every quarter since launch. Google led with that number.

The shift is real, and it’s here now.

Last week at Google's Brandformance summit (where Google brings together its top agency partners to talk about what's actually working), Chris Marino, Google's Head of Agency, said Google is enabling Level to monetize measurement as a service through integrations that help defend the impact of media investment in a platform-agnostic way.

That framing matters more today than it did seven days ago. When the search environment changes this fast, the agencies that survive are the ones that can prove what's working regardless of where the conversion happens.

That's why we've been moving clients toward intent and predictive-based technology with Level.Signal, and building causal measurement capability through early access to Google's Causmos. When a platform rewrites the rules, you need measurement that doesn't depend on the platform to grade its own homework.

AI Overviews, AI Mode, agentic search, multi-step reasoning queries. These aren't features; rather, they’re a completely different surface. The CMO who walks into a budget meeting this fall with causal proof of what worked, what didn't, and how the team pivoted is the CMO who gets a bigger budget. The CMO who's still optimizing for a SERP that no longer exists is in a harder conversation.

We've been building for this for two years. The timing feels about right.

Register here.

Now for this week’s stories.

Patrick Patterson

CEO at Level Agency

What's interesting this week

Level's framework for measurement that holds up in a CFO meeting

Level Agency's latest piece makes the case that measurement isn't a reporting exercise, it's a revenue strategy. The piece walks through how to identify which signals actually correlate to growth and how to keep your framework intact when the platforms change their definitions underneath you.

Key takeaway: The teams that can translate marketing performance into language finance trusts are the ones that get more budget. The teams that can't are the ones defending last quarter's numbers with a chart that proves nothing.

A look into YouTube's Brandcast 2026

YouTube’s annual upfront delivered a pointed message: YouTube now reaches more US viewers than Netflix, CTV conversions grew 200% year-over-year in Q1 2026, and creators are driving 13x more branded searches than passive ad exposure. New tools around creator sponsorships, AI-matched placements, and CTV checkout are designed to convert that attention into measurable action.

Key takeaway: Key takeaway: If your YouTube strategy hasn’t evolved to include creators or CTV formats, the brands that have are putting up numbers you can’t match with a repurposed TV spot.

The Meta Ads mistakes that are costing teams money right now

PPC Hero's breakdown covers the structural problems that show up repeatedly in Meta accounts: overcomplicated campaign structures, audiences that cannibalize each other, creative designed for one placement and forced into five. It's a useful checklist for teams who inherited accounts or are onboarding new clients.

Key takeaway: Most Meta performance problems are structural, not budgetary. Fix the foundation before you scale the spend.

Social data is reaching analysts but not the people making decisions

Marketing Dive surfaced an uncomfortable data point: social listening and audience intelligence rarely makes it to the people who control strategy and budget. Too much data, not enough time, unclear ownership of who translates insight into action.

Key takeaway: Social intelligence is only valuable if someone acts on it. If you can't connect a data source to a decision made in the last 90 days, it's generating noise, not clarity.

Deep dive: AI

What Google I/O 2026 means for your search strategy

Google I/O 2026 made it official: the search experience most marketing programs were built around is no longer the default. Search revenue up 19%. Open web ad revenue down 4%. AI Mode at one billion monthly users with queries doubling every quarter. The surface where most search budgets were built is no longer where most search happens.

That matters because the programs most teams are running today, the bidding logic, the content strategy, the attribution models, were designed for a search environment that produced a list of links and measured a click. AI Mode doesn't work that way, and the gap between how search actually behaves and how most teams are measuring it gets wider every quarter.

The harder problem is that the infrastructure required to operate in this environment takes time to build. Measurement that doesn't depend on platform-reported attribution. Content built for AI Overview citation, not just SERP rank. Lead quality data clean enough to support predictive modeling. Brad Stephenson breaks down what changed at I/O and what each of those problems actually requires to solve.

Deep dive: Growth

Meta's data on where consumers actually discover products

Meta published research this week on how consumers use social platforms at the top of the purchase funnel. The data makes a case for social as a discovery channel rather than a conversion channel, which is a useful reframe for teams evaluating social primarily on last-click performance.

The research shows how much of the buying journey begins in feeds, before any intent signal fires, before any search query is typed. Brands that show up in that early window are the ones who make the shortlist. The ones waiting for high-intent signals are often arriving after the consideration set is already closed.

If your social strategy is built entirely around conversion campaigns, you're optimizing for the end of a journey you had no part in starting. Discovery is where brand preference gets built.

AI tool of the week

Typeless AI

Most AI workflows still start the same way: open a tab, type a prompt, wait for output, copy it somewhere useful. Typeless AI removes most of that friction by letting you interact with AI models directly inside your existing tools, without switching context. For teams producing high volumes of ad copy, email sequences, or content briefs, the time savings compound quickly.

Where it earns a permanent place in a workflow is anywhere the copy-paste loop is slowing people down. Social caption reviews, subject line variants, quick reframes of existing content for a different audience or channel. The tasks that take two minutes each but add up to an hour by end of day.

Why I recommend it for growth leaders: the best AI productivity gains are not coming from flashy new capabilities. They're coming from removing friction from the tasks your team already does every day. Typeless AI is a good example of that.

What does ChatGPT actually say about you?

When a potential buyer asks an AI agent for a Top 5 list in your category, do you make the cut? More importantly: Why or why not?

Don't leave your brand’s reputation to an algorithm you haven't audited. Our scorecard pulls back the curtain on how AI platforms frame your brand sentiment and which sources they use to vet your authority.

Inside your custom report:

Sentiment analysis: Is the AI's summary of your brand accurate or outdated?
Citation audit: Discover which third-party sites are feeding the AI your info.
AEO roadmap: Immediate steps to improve your "AI discoverability."

SEE WHAT AI SAYS ABOUT MY BRAND

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