Where is the growth?

Why AI in retail is yet to deliver real marketing transformation, and how you can get ahead.

AI promises to help retailers create more content, personalize more experiences, move faster, and operate more efficiently than ever before. Yet despite all the excitement, a surprising number of organizations are struggling to translate that promise into measurable business value.

In fact, while 75% of leaders in retail and CPG cite AI as a top strategic priority, only 16.5% can actually measure a return on their AI investments.

That raises an important question.

If AI really is transforming retail, why are so many retailers finding it difficult to realize meaningful returns?

The technology itself isn't the issue. What's becoming increasingly clear is that AI has advanced faster than the operational foundations surrounding it. Across the industry, retailers are introducing powerful new capabilities into workflows still held together by manual processes, disconnected systems, and fragmented data.

The result is familiar. More tools. More content. More complexity.

What often gets overlooked is the infrastructure underneath. Because the retailers creating meaningful growth from AI are doing far more than simply adopting the technology. They're rethinking how ideas move through their business.

And that's where the real opportunity lies.

Most retailers are not short of creativity. They are full of talented marketers, imaginative creatives, rich customer data, and strong commercial strategies.

The challenge comes later.

Between the moment an idea is conceived and the moment a customer encounters it sits an increasingly complex network of channels, touchpoints, approvals, governance processes, technologies, and teams.

At the same time, the retail environment has fundamentally changed.

Customer journeys no longer follow a predictable path. They unfold across marketplaces, loyalty programs, retail media networks, mobile apps, ecommerce platforms, stores, social channels, and countless other micro-moments. Content has evolved from campaign collateral into commercial infrastructure, influencing everything from conversion rates and promotional outcomes to loyalty and operational performance. 

In this new reality, three dynamics shape performance.

Relevance determines whether content gets noticed. Customers increasingly respond to experiences that reflect their needs, context, location, and intent rather than broad, generic messaging.

Speed determines whether opportunities are captured or missed. Retailers today operate in an environment where inventory changes, promotions shift, and customer behavior evolves continuously. The organizations that can respond quickly gain a significant advantage.

Volume has become a permanent condition of modern retail. Every campaign now requires countless variations across audiences, channels, markets, products, and formats.

None of these challenges are solved by throwing more ideas at them.

The pressure comes from turning a single strong idea into thousands of relevant customer experiences without losing consistency, quality, or speed along the way.

This is where many AI conversations go wrong.

When I speak to retail marketers, I often get asked: How can AI help us create more content? But creating more content isn't the goal.

Creating more effective content is.

And that distinction really matters.

An organization can generate assets at unprecedented speed, yet still struggle to improve customer experience, marketing performance, or operational efficiency. That's because content doesn't create value on its own. Value is created when intelligence, execution, timing, and relevance come together.

Too often, AI is introduced into operational models that are characterized by disconnected data, fragmented workflows, manual adaptation, governance bottlenecks, and siloed technologies. The technology accelerates output, but the friction remains.

The truth is that AI only magnifies the system around it. If the system is already efficient, then great — you get more efficiency. But too often, AI is exacerbating chaos. ‘Garbage in, garbage out’ still applies. Without fixing your marketing ecosystem first, AI just means you’ll deliver higher volumes of bad content, faster.

Teams produce more variants that still need to be reviewed, approved, localized, distributed, and managed. New tools get introduced while legacy processes remain untouched. Complexity overshadows capability.

The retailers seeing the greatest returns from AI have approached things differently.

Rather than treating AI as an additional step in the process, they've embedded it into a connected operating model, closing the gaps in workflows where inconsistency and inefficiency traditionally occur. 

The technology becomes part of the flow of work itself, helping teams make better decisions, automate routine tasks, and respond to customer needs more effectively.

Now, you’re getting faster, greater output and better execution.

The retailers creating real value from AI have discovered a simple but powerful truth.

Competitive advantage is increasingly determined by how effectively an organization moves from insight to action.

I've said it before, and I believe it more strongly than ever:

The brands that win in retail today aren't the ones producing the most content. They're the ones with systems that allow great ideas to travel faster.

Those systems don't diminish creativity.

They extend its reach.

A powerful idea should not need to be reinvented every time it encounters a new channel, market, store, audience, or format. It should be able to move through the organization with clarity and consistency, adapting where necessary while retaining its core value.

That's why the conversation around AI should begin with flow, not generation.

How do ideas move from customer insight into execution? How do teams access the information they need? How quickly can content adapt to changing conditions? How easily can performance data influence the next decision?

The organizations answering those questions well are the ones turning AI into measurable growth.

At ITG, we increasingly think about this challenge through three connected capabilities: Knowing, Flowing, and Growing. These represent the foundations of a modern AI-powered content operation.

Everything starts with intelligence.

Before content is created, businesses need a clear understanding of what should be created, for whom, when, and why.

That requires connecting signals that traditionally sit in different systems: customer behavior, inventory levels, loyalty activity, promotional calendars, pricing information, and performance insights. Through our proprietary Halo Intelligence®, the objective is to translate those signals into decisions that guide action.

In this environment, AI becomes less of a content generator and more of a strategic advisor, helping teams identify where their effort will create the greatest impact.

Intelligence creates value only when it can move.

Many organizations already possess the information they need. The challenge is making that information accessible and actionable across the business.

Connected, fully integrated content ecosystems play a critical role here.

Technology such as our Storyteq Content Marketing Platform serves as the backbone that links workflows, governance, assets, teams, and channels together. As content moves through the organization, bottlenecks are reduced, governance becomes embedded, and ideas travel with far less friction.

More than just efficiency, what you’re targeting here is momentum.

Technology creates potential, but it’s your people who unlock value from it.

The organizations generating the strongest results from AI are those that align technology, process, governance, and talent around a common operating model. Transformation happens when teams understand how to use new capabilities confidently and consistently across the business. 

Growth, ultimately, is the outcome of intelligence and execution working together, underscored by a close, collaborative, people-first partnership.

One of the clearest examples of this principle comes from our work with Kroger.

The transformation wasn’t achieved through a standalone AI initiative or a single automation project. It came from rebuilding the operational foundation behind weekly promotional activity — the same weekly cadence that anchors circular programs across the industry.

Before that foundation existed, the work looked familiar to any team running a circular today: merchandising and pricing data lived in one system, promotional content lived in another, and connecting the two meant manually matching thousands of SKUs to their promotional placements, division by division, week after week. Errors were often caught late, and every new division meant repeating the same manual work from scratch.

By creating a unified, data-driven content engine powered by Storyteq and connecting content directly to product and promotional data, Kroger changed what that weekly cycle required. Promotional content no longer had to be rebuilt by hand for each division — it inherited pricing, product, and promotional data automatically, was validated before it reached shoppers, and moved into market as fast as the promotional calendar itself changed.

More than 90% of promotions became shoppable across 24 divisions, while workflow touchpoints were significantly reduced.

What’s particularly interesting about that outcome is what it reveals.

The commercial impact didn’t come from a smarter circular, a personalization layer, or a measurement dashboard added on top of the old process. It came from connecting intelligence, content, and workflow into a single operating system first. Once that foundation was in place, personalization, shoppability, and AI-driven automation weren’t separate initiatives bolted on afterward — they were things the system could now support at scale, across every division, without adding headcount or complexity.

That’s a lesson many retailers — including those still running largely manual weekly circular programs — can learn from.

Adding yet another personalization tool, measurement layer, or AI feature on top of a disconnected process rarely unlocks significant returns. It just adds one more disconnected step. True ROI comes from strengthening the environment those tools operate in — connecting the promotional calendar, the product data, and the content itself before asking any tool to move faster.

The next decade of retail won't be defined by which companies adopt AI first. Nor will success belong automatically to those deploying the greatest number of AI solutions.

The retailers that pull ahead will be the ones that create connected operating models capable of transforming intelligence into action.

They will understand what to create and when to create it. They will enable ideas to move seamlessly across channels and customer moments. They will remove friction from workflows while maintaining governance and control. And they will equip people with the tools, processes, and confidence needed to scale personalization in meaningful ways.

Great ideas have always mattered. What's changed is the environment around them.

Today, competitive advantage comes from turning insight into execution faster, adapting content more intelligently, and creating relevance at scale. AI can accelerate that journey dramatically.

But AI’s greatest contribution isn't the content it generates. It's the way it helps your great ideas travel.