AI-Powered Growth

April 29, 2026

Captain's log

Last week, our team was split across two conferences. Half were on the floor at LeadsCon in Las Vegas. The other half were at LeadSquared ELEVATE in Nashville. Different rooms, same problem on every marketer's mind.

The conversation that kept coming up was not about generating more leads. It was about why so many leads go nowhere. Teams are running campaigns, filling funnels, hitting volume targets, and still watching pipelines stall. The leads are there. The quality leads (and therefore, the outcomes) are not.

The honest diagnosis is a signal problem. Most lead generation programs are still optimized for the form fill, not for what happens after it. They treat every inquiry as equally valuable, which means the algorithm is chasing volume without any sense of which leads are actually likely to convert. You get more of what you measured for, not more of what you needed.

The better path is also the harder one to build: using first-party data and propensity modeling to tell your media what a good lead actually looks like before you spend the dollar. When you do that, something counterintuitive happens. Lead volume can come down. But qualification rates and closed revenue go up, sometimes dramatically.

Level Signal, part of our Level Intelligence Suite, is built around exactly that shift: moving optimization from lead quantity to lead value, so your media learns to find the people most likely to become customers, not just the people most likely to click.

More leads is not the answer. Better signals are.

If you are trying to work out where to start that process for your own organization, our diagnostic is a useful first step.

Patrick Patterson

CEO at Level Agency

What's interesting this week

6 top answer engine optimization benefits for growth and enterprise marketers

AEO has moved from a niche concern to a core channel consideration. This piece from HubSpot lays out the case for why optimizing for AI-generated answers, not just traditional search rankings, creates compounding visibility advantages.

The highest-value benefit is reach into zero-click environments where buyers are forming opinions before they ever land on your site.

Key takeaway: If your content strategy is still organized entirely around search rankings, you are optimizing for the last stage of a buyer journey that already started somewhere you cannot see.

The martech investment nobody budgets for

Three recent studies land on the same conclusion: the gap between what marketing technology can do and what teams can actually execute keeps growing.

Organizations with strong execution get enormous results from average platforms. Teams with weak execution underperform with sophisticated ones. The investment that is consistently overlooked is training, process, and data discipline, not the tool itself.

Key takeaway: Before you add another platform to your stack, ask whether your team can fully put the ones you already own to work.

The Generation Gap has closed. Has your strategy?

Meta's research finds that the behavioral divide between generations on its platforms has narrowed significantly. Millennials, Gen X, and Boomers are now using Meta in ways that closely resemble how younger users engage.

If your creative and targeting strategy was built on generational audience assumptions, those assumptions are increasingly out of date.

Key takeaway: Segment by behavior and intent, not age. The data has moved on even if your media plan has not.

YouTube testing AI-powered search feature that shows guided answers

YouTube launched a test of "Ask YouTube," an interactive search feature that returns step-by-step guided answers combining text and video clips in response to open-ended queries.

Users searching for recipes, travel plans, or how-to questions now get an experience closer to a conversational AI interface than a traditional results list. This is YouTube making a direct play for the query types that have been migrating to ChatGPT and Perplexity.

Key takeaway: Every major platform is now building an answer layer. Your brand's presence in those answers is becoming as important as your presence in the search results below them.

Deep dive: AI

Vibe coding is hollowing out the martech stack fast

The data is starting to show what the theory predicted. Mid-market firms have seen a 35 percent year-over-year decline in renewals for single-function martech tools, according to Chiefmartec and MartechTribe's 2026 report. About 63 percent of vibe coding users are non-developers, meaning marketers themselves are now building the tools they used to buy. The shift is most visible at the edges of the stack, where point solutions once filled gaps that are now easier to recreate internally.

Scott Brinker put it plainly: AI-native tools are winning the creation layer. Copy, pitch decks, visual production, competitive intelligence. The tasks where the primary input is a prompt. Established platforms like HubSpot and Salesforce still control the orchestration layer, but the single-purpose tools sitting between them are increasingly hard to defend.

The practical implication is not that SaaS is finished. It is that the bar for what earns a renewal has fundamentally changed. Software you can replicate in a day with a prompt is software you will not keep paying for.

Key takeaway: Audit your stack for tools that do one thing AI can now do faster. That budget is better spent on the orchestration layer or on the human capability that makes the whole system work.

Deep dive: Growth

How HubSpot grows with Agent-First GTM

HubSpot published a detailed look at how they have rebuilt their go-to-market model around AI agents at every stage of the funnel. The headline numbers are striking: qualified leads from AI-generated answers grew 1,850 percent between Q1 2025 and Q1 2026, and those leads convert at up to three times the rate of traditional search. They now book over 10,000 meetings per quarter through their Prospecting Agent, with a 13 percent increase in win rate on deals where guided selling is used.

What makes the piece worth reading is not the scale of those results but the model behind them. HubSpot is explicit that agents do not work alone. Each one has a defined scope. Demand Agent expands reach. Inbound Agent converts interest. AEO captures buyers who were never in the funnel. Prospecting Agent and Deal Assistant accelerate active opportunities. Customer Agent handles retention. The flywheel compounds because every interaction improves the data underneath it.

The lesson that applies regardless of your company size: the teams getting real value from AI have not bolted it onto their existing process. They have redesigned the process around what AI can do at scale and where humans need to stay in control.

Key takeaway: Agent-first GTM is not about replacing your team. It is about giving every person on your team more leverage at the moments that actually move deals forward.

AI tool of the week

Google Sheets Canvas

Google has added a canvas feature to Sheets, powered by Gemini, that converts spreadsheet data into interactive visual layouts without requiring any code. You describe what you want, and it builds it: kanban boards, dashboards, gallery views, heat maps, interactive calendars. The underlying data stays in the spreadsheet. The canvas is a live interface on top of it.

The practical use case that stands out is campaign and project tracking. If your team is managing event logistics, launch timelines, or lead routing workflows in a spreadsheet, canvas turns that data into something your stakeholders can actually navigate instead of squinting at rows.

Where it earns real attention is for teams that have been considering a project management tool but do not want to move their data. Canvas does not require migrating anything. The data you already have becomes the product.

Why I recommend it: if your team lives in Google Workspace and has been using Sheets as a de facto project tracker, this closes the gap between the data you have and the interface you actually want.

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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