Marketing to the Machine: Tom Wozniak on How Performance Teams Can Join Forces with AI to Drive Bigger Wins
Your next campaign won't be evaluated by a human buyer. Instead, it’ll be screened by an AI assistant acting on their behalf.
Yet, most performance marketing teams still treat AI adoption as a sprint to chase shiny new tools. Even worse, uncoordinated tool usage exposes companies to major privacy breaches.
At OPTIZMO, Chief Operations Officer Tom Wozniak takes a much more methodical approach.
OPTIZMO built a centralized AI framework to connect internal discovery and drive efficiencies, while maintaining the human element. This foundation means their marketing stack is structured for an era where AI agents act as gatekeepers for human consumers.
Here’s a look inside OPTIZMO's setup and how you can use the same blueprint to unify your own teams and prepare your campaigns for the machine.
Connecting Isolated AI Islands to a Single Context Layer
When a company begins adopting AI, individual experimentation naturally creates friction. One team member might build a custom agent to prioritize their inbox, while a colleague on another team spends days building the exact same tool from scratch.
"We're all off in our own little islands in a lot of ways, just finding ways to do things," Wozniak notes. "You've got people, essentially, trying to discover the same things. If I could just connect with someone on that, I could take their prompts and skip some of the first steps and hurdles."
To resolve this, OPTIZMO initiated a voluntary weekly Slack "AI Huddle" for their US team.
Led by team members going deep on AI, the weekly meeting gives employees a space to share custom agents, discuss technical hurdles, and level the playing field across varying comfort levels. Attendees range from eager power users to privacy-conscious skeptics.
Beyond team alignment, the most critical step was establishing a single company-level account on Claude. Loading one centralized repository of product features and documentation ensures that marketing, development, and executive teams draw from identical contexts.
Once a team unifies its internal context, the next step is applying that shared intelligence to daily execution.
Practical AI Workflows: How OPTIZMO Incorporates AI into Daily Operations
At OPTIZMO, AI functions as a force multiplier for daily tasks, data analysis, and asset creation.
Instead of replacing strategic human thinking, the OPTIZMO team deploys targeted workflows to eliminate routine legwork:
The Morning "Command Center" Dashboard
Rather than logging into five separate platforms every morning to check email, Slack, and system metrics, Wozniak used AI to build a unified morning command center. The system surfaces top-level stats in a single view, allowing him to spot anomalies before deciding where to deep-dive.
Rapid Video Creation
When OPTIZMO needed a product walkthrough video showing a feature still in active development, their head of development used AI video tools to build a full, polished demonstration in hours. This allowed the team to bypass traditional video editing suites like Adobe Premiere or Photoshop entirely.
Voice & Tone Emulation
During an internal experiment, OPTIZMO's leadership fed years of company content into Claude to see how well it could capture the brand's voice: the tone, phrasing, and personality that make OPTIZMO's writing sound like OPTIZMO. When shown a sample of AI-generated copy written in that style, Wozniak admitted he couldn't immediately tell it apart from the real thing.
Optimizing High-Volume Email and Deliverability with AI
While OPTIZMO uses AI internally for workspace productivity and product walkthroughs, Wozniak sees an even larger shift on the horizon for bulk emailers and high-volume senders.
Sifting through massive databases to identify engagement patterns, optimize send times, and build multivariate tests traditionally requires mathematical modeling and hours of spreadsheet work.
Deploying AI models to analyze historical response data allows senders to spot deliverability bottlenecks instantly. The technology can identify pattern shifts in complaints and automatically route traffic toward winning offer variations in real time.
Compliance Risks & the Rise of the AI Gatekeeper
The more performance marketers use AI, the more they expose themselves to legal compliance and data privacy risks. State privacy laws require businesses to collect minimal consumer data and disclose its exact usage.
When advertisers upload customer lists or performance metrics into public AI models whose default settings train on user inputs, they may risk sharing personally identifiable information (PII) with third parties.
"There's a really good chance they've broken their own privacy policy if they have not said explicitly, 'We're using AI,'" Wozniak warns.
He points to an industry cautionary tale of a company that gave an unvetted AI agent full database access. The agent inexplicably deleted their entire client database without warning, leaving the business without backups and completely destroying consumer trust.
Looking forward, marketers must also adapt to a fundamental shift in audience behavior: “marketing to the machine.” As consumers adopt personal AI assistants to filter inboxes and manage tasks, marketing copy will be evaluated by an AI gatekeeper before a human sees it.
In the near future, consumers will instruct personal inbox agents to automatically purchase items when specific parameters are met (ex: auto-buying a favorite apparel brand when a 50% off promotion hits the inbox). Campaigns structured for machine readability will capture this automated revenue first.
By unifying your internal AI context today and enforcing compliance guardrails, your team can build the machine-readable foundation necessary to win over the AI gatekeepers of tomorrow.
