The IG operating model

The operating model behind every AI startup we run.

Most AI marketing agencies pitch decks about how they use AI. We operate AI-orchestrated marketing programs with named human owners on top of a multi-agent stack. The proof is in our portfolio, not our pitch.

See the five workstreams Book a discovery call

LLM-referred traffic conversion vs organic search (Stackmatix, 2026)

60%

of B2B vendor research now AI-mediated (iTMunch, 2026)

90%+

task improvement of multi-agent over single-agent systems

AI startups currently operating on the IG stack

The line in the sand

In 2026, marketing agencies fall into two camps. The ones who use AI to write copy faster, and the ones who orchestrate AI agents to run an entire marketing program with humans in the loop. The first camp will be commoditized by GPT-5. The second camp will compound.

Innovative Group is the second camp. Our portfolio companies don't hire us for ChatGPT prompts. They hire us because five named owners (Michael Sykora on paid media, Ashlesha Khond on SEO and content, David Garcia on site and landing pages, Chris Salazar on CRM and lead routing, IG team on analytics and instrumentation) run an AI-orchestrated workstream each, and the work ships by Friday, not by month-end.

The five-workstream operating model

Each workstream has one named human owner and an underlying multi-agent stack. The human owns judgment and the final call. The agents own production volume and pattern matching at scale.

Workstream	Named owner	Agent stack handles	Human owns
Paid media	Michael Sykora	Campaign architecture, audience builds, bid optimization, creative variant testing	Strategy, channel mix, budget allocation
SEO + content	Ashlesha Khond	Keyword research, topic clusters, AEO formatting, schema, llms.txt	Pillar editorial direction, brand voice, citation strategy
Marketing site + LPs	David Garcia	Page generation, A/B variants, copy iteration, schema injection	Design system, conversion architecture, brand consistency
Analytics + instrumentation	IG team	Event taxonomy, GA4 + GTM, attribution model, weekly dashboards	What questions get answered with the data
CRM + lead routing	Chris Salazar	Lead scoring, nurture sequences, InMail flows, pipeline review prep	Sales judgment, prioritization, customer relationships

Why this beats the alternative

An AI marketing agency that pitches "we use AI" is selling you GPT-4 wrappers with a Slack channel attached. You'll get ten landing pages a month that all sound the same and convert about as well as your last agency's.

Agentic marketing as an operating model is structurally different. The agents don't produce a deliverable, they produce options. The named human owner picks the option that fits the brand, the audience, and the goal. Multi-agent systems outperform single-agent setups by more than 90% on complex tasks (Improvado, 2026). Specialized agent teams beat general agents on every benchmark that matters.

The structural difference shows up in unit economics. Year 2 cumulative ROAS on the IG operating model lands at 8x for AI startups taking the network play. Year 3 hits 17x as the enterprise data layer compounds.

Customer Zero proof

Every claim above is running in production right now, in a customer engagement we operate end-to-end.

AI funding platform (anchor in stealth): $3.5M raise at $20M valuation with patient capital, two-step ratchet, founders retain 80%+. Y2 cumulative ROAS modeled at 8x against real channel KPIs.
All Voice AI: Customer Zero of the IG fractional CMO model. Voice AI for SMBs, $349+/mo MRR per customer. Recognized as the #1 voice AI for SMBs.
20twenty Willow Glen: Local engagement running the Beat product as the client-side dashboard. SMB hospitality category.

The IG agent stack, named and accountable

Inside each workstream sits a multi-agent system. The agents are not a black box. We name them, version them, and pin which model they run on so audit and rollback are straightforward.

A research agent canvasses category sources and pulls statistical anchors. A draft agent produces the first long-form piece against an editorial brief. A schema agent inspects every published page and patches the JSON-LD. A citation agent runs Share of LLM queries quarterly and reports which surfaces are pulling our work and which are missing us. An ops agent watches the analytics layer and flags anomalies before the human owner walks into Monday standup.

The agents do not ship anything to a customer-facing surface without a named human signing off. Every workstream has a human as the last gate. Every workstream has a fallback playbook for the day the model misbehaves. The audit trail is the deliverable, not the marketing copy.

What a Monday morning looks like

Operating cadence matters more than the tooling. The IG week runs on a predictable rhythm so the agents stay in their lane and the humans stay accountable to outcomes.

Day	Cadence	Owner who signs off
Monday 9:00	Workstream standup, 25 minutes. Agents drop a synthesized weekly status into the channel before the call.	Chris Salazar (program lead)
Tuesday	Paid media review. Campaign-level diagnostics, audience refresh, creative variant calls.	Michael Sykora
Wednesday	Content + SEO build sprint. Two pieces ship to staging. AEO snippets reviewed.	Ashlesha Khond
Thursday	Site + LP review. Conversion checks, schema audits, mobile QA on the week's ships.	David Garcia
Friday	Customer-facing ship day. Everything that survived QA goes live. Weekly board update written.	IG team collectively

How we measure agentic marketing performance

Four KPIs travel together. Each one tells a different story about the program and they only mean something in context.

Cumulative ROAS, by year. Year 1 is investment-heavy and ROAS is usually below 1x. Year 2 should land at 6x to 10x. Year 3 compounds to 15x or higher when the network effects engage.
Blended LTV / CAC, across tiers. Founder tier, investor tier, and enterprise tier each behave differently. The blended number lives above 5x in healthy programs and above 10x in great ones.
Payback period, in months. We aim for 6 months or shorter. The faster the payback, the more aggressively the operating model can scale.
Share of LLM, by category query. The leading indicator for everything else. When citation share crosses 25% on the priority query set, organic and direct traffic re-accelerate.

FAQ

Frequently asked questions

What is agentic marketing?

Agentic marketing is an operating model where multiple AI agents (each specialized for a task like research, content production, paid media optimization, or analytics) are orchestrated by named human owners. It is not the same as marketing automation or "we use AI" tooling. Agentic marketing requires multi-agent systems, human-in-the-loop accountability, and a clear ownership model. Innovative Group runs this play across multiple AI startups in production.

How is agentic marketing different from marketing automation?

Marketing automation in 2010 meant rule-based triggers ("if email opened, send follow-up"). Marketing automation in 2020 meant ML-based personalization at scale. Agentic marketing in 2026 means multiple specialized AI agents collaborating on a marketing workflow, with a human strategist owning judgment. The agents are not making predetermined choices, they are evaluating goals like "increase qualified investor leads by 20% this quarter" and autonomously coordinating the work to get there.

Who runs agentic marketing at Innovative Group?

Five named owners. Michael Sykora runs paid media. Ashlesha Khond runs SEO and the content engine. David Garcia runs the marketing site and landing pages. Chris Salazar runs CRM and lead routing. The IG team owns analytics and instrumentation collectively. Each owner runs their workstream with an underlying multi-agent stack, and the human owns the final call.

Is this the same as Next Best Action (NBA)?

NBA is Innovative Group's product. It's the Status / Ask / Approve agentic workflow OS that sits underneath the operating model. Where IG provides the operator service, NBA provides the productized workflow. Customers who want the operating model run by IG hire the fractional CMO engagement. Customers who want to run it themselves use NBA.

How do you measure agentic marketing performance?

Cumulative ROAS by year, blended LTV / CAC across customer tiers, payback period in months, and Share of LLM (citation share across ChatGPT, Claude, Perplexity, and Google AI Overviews). Year 2 cumulative ROAS on the IG operating model lands at 8x. Year 3 scales to 17x as the enterprise data layer compounds and Share of LLM matures.

Do you replace our existing marketing team?

No. We replace the fractional consultancy model that ships decks. We slot into your team as five named workstream owners with an agent stack underneath. If you have an in-house head of marketing, we report to them. If you do not, the IG program lead acts as the interim CMO with named handoff criteria.

How fast does an agentic marketing program show results?

Paid media moves first, usually inside 30 days, because the agent stack accelerates campaign variant testing. SEO and the content engine show results in 60 to 90 days as citation share builds and AEO snippets index. Pipeline impact typically lands in months 4 to 6, on par with traditional fractional CMO engagements but with a steeper compounding curve thereafter.

What tools and models do you run on?

Multi-model by design. Claude for long-form writing and reasoning. GPT for breadth and quick iteration. Gemini for specific Google integrations. Open-source models for tasks where data privacy matters. We pin model versions per agent and version the prompts so we can roll back if a model update changes behavior. The customer never has to think about which model is doing what.

Related at Innovative Group

The metric

Share of LLM: how to measure AI citation visibility

AEO services

Answer Engine Optimization (AEO) for B2B

Vertical

Fractional CMO for AI startups

Comparison

Agentic marketing vs AI marketing agency

POV

The Customer Zero marketing playbook

Operating model

How we work, fractional CMO engagement

Run the operating model. Don't pitch it.

If you're a founder or CMO ready to stop hiring agencies that send decks and start operating with a team that ships, we should talk. Four to five AI startups a year. Patient capital welcomed.

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