Dan Birks, ITG’s Chief Growth Officer (EMEA), explains why a Content Marketing Platform must form the backbone of your operations if you want AI to drive real ROI.
At ITG, we work with clients to create the marketing backbone they need to scale content operations and enable the effective use of AI tools. Getting this backbone in place is an important challenge given how much AI relies on solid structural foundations — but it’s one that the wider industry is only just beginning to understand.
Recent research from McKinsey shows that only 39% of brands are seeing EBIT impact at enterprise level from AI, attributing the gap not to issues with the tools themselves, but to weak operational integration.
And earlier this year, Gartner predicted that 60% of brands will be utilizing AI agents for streamlined one-to-one interactions by 2028, strongly advising businesses to prepare by “integrating agentic systems into martech stacks to enable secure, ethical personalization at scale.”
With the pace of change accelerating, scaling AI and content operations is only becoming more difficult, especially for larger brands. Below, Dan Birks further explores why prioritizing a Content Marketing Platform as their operational backbone will enable brands to drive meaningful ROI from their AI tools.
AI has moved well past the “can it?” stage. The real question is “how do we get the most out of it — consistently, safely, and at scale?”
The blunt truth is that you won’t unlock meaningful ROI by throwing more tools at the problem. If your content ops are disorganized, AI just magnifies the chaos. What you need first is a content backbone — a Content Marketing Platform (CMP) at the center of your ecosystem — so that AI becomes a powerful weapon in your arsenal, not a loose cannon.
The challenge brands are wrestling with
Most marketing organizations didn’t design their operating model for an AI‑accelerated world. They’re juggling dozens of disconnected apps, ad‑hoc workflows, and shadow tools cropping up in every team. Add generative AI into that picture and you amplify the good or the bad — faster. Without a unifying platform, you get:
- Fragmented tools: teams easily end up touching 20+ tools, meaning context switching and duplicated effort become the norm.
- Risk to brand integrity: more people creating more assets increases the likelihood of off‑brand outputs and compliance slips.
- Wasteful duplication: if nobody can find or trust what already exists, AI gets used to recreate assets that should have been reused or adapted. That burns budget, wastes time, and means you never maximize content value.
In short, AI without operational discipline doesn’t save you time or money — it just produces more inconsistent content, faster.
Two halves of the AI game: Operational and Generative
Here’s what the two offer, and how they differ.
- Operational AI
Wherever humans are checking objective rules — CTAs, legal copy, logo placement, mandatory terms — AI can support or automate those tasks. This is the “efficiency engine” that tightens QA, accelerates approvals, and reduces rework. - Generative AI
GenAI democratises creation so more people can produce more assets. That’s a feature and a risk. You only see the upside when generative tools plug into a coherent ecosystem with human oversight, otherwise you just get volume while quality suffers.
Why a CMP is the backbone
A CMP brings work into one place to brief, create, adapt, approve, govern, and distribute — connecting seamlessly with your DAM, channel tools, and AI services. Think of it as the stable core that every other capability plugs into. When AI is routed through that backbone, three things happen:
- Governed creation at speed
AI outputs flow straight into standardized review and approval, so you get the best of both worlds: fast generation with brand, legal, and regulatory control. - Reuse before (re)create
Agentic workflows can trigger a natural‑language search in the DAM before generating new assets, surfacing content with the correct rights, branding, and messaging. That reduces duplication, speeds up production, and leaves teams with more space to focus on strategic and creative imperatives. - Future‑proof interoperability
With the tool landscape evolving weekly, your backbone must integrate today’s models and tomorrow’s. The CMP is where you enforce process while swapping or adding AI utilities as needed.
Discover more about ITG’s Storyteq CMP here, and find out why Gartner has named it a Leader in its Magic Quadrant for CMP three years running.
What “good” looks like in practice
- Standardised intake and briefing
Every request lands in one place. Templates capture mandatory elements (audience, messaging, brand rules) and trigger AI‑assisted checks early, before bad work starts to snowball. - Agentic “search‑then‑create”
When someone prompts for a new asset, the workflow first queries the DAM using natural language to find reusable or adaptable content. Only if nothing suitable exists does generation proceed. - Policy‑as‑guardrails
Brand, legal, and channel rules are embedded in the platform so AI can apply them automatically: approved CTAs, mandatory disclaimers, logo usage, aspect ratios, retail promo terms, and so on. Humans focus on judgment calls, not box‑ticking. - Review, approval, and audit
All AI‑assisted work follows a consistent path with trackable decisions, comments, and rights metadata. That reduces compliance risk and accelerates governance at scale. - Continuous optimization
Operational data (cycle time, rejection reasons, reuse rates) feeds back into prompts, templates, and rules, making the system smarter over time.
The payoff you should expect
When AI is treated as a tool (rather than a catch-all solution) inside a CMP‑led ecosystem, you can deliver:
- Faster speed‑to‑market through automated checks, templated adaptations, and fewer back‑and‑forth loops.
- Greater content value because teams find and adapt what exists instead of starting from zero.
- Lower production waste by eliminating duplication and over‑versioning, which is good for budgets and sustainability metrics.
- Reduced brand and compliance risk via governed generation and auditable approvals.
- Significant savings as operational AI automates manual versioning, localization, and production tasks at scale.
How to get started
The first thing to do is map what you actually need. Inventory your content workflows and tools, and see where Operational AI could be implemented to save you time.
Then, select a CMP that forms the backbone of your operations, one that can integrate cleanly with your DAM, plays nicely with AI tools, and is future-proofed against changes. With the pace of change in marketing right now, this is essential. Our vision for the AI-enabled future of marketing is a big reason our Storyteq platform was named a 2025 Leader in the Gartner Magic Quadrant for both CMP and DAM — so there’s a good place to start!
From here, it’s as much about mindset as technology, and how these two work together. You want a ‘reuse-first’ model that maximizes content value, and doesn’t end up generating new content for the sake of it — detracting from asset value while putting brand integrity and compliance at risk.
And as always, you must keep people in the loop. AI can handle objective checks and rules-based tasks, but for those crucial creative and strategic judgement calls, there’s no substitute for human intuition.
Get the backbone right, and you’ll be well on your way to creating better content, while reducing costs and boosting ROI.
The bottom line
If you try to make AI the strategy, you’ll chase shiny tools and wonder why you’re still not unlocking ROI. Make the content operations backbone the strategy. Then let AI plug in as a force multiplier across creation, adaptation, governance, and distribution.
Get the processes right, put the CMP at the center, and you’ll magnify the good — speed, quality, and consistency — without amplifying the noise.