Inside AI with Steve Shaw: 

AI transformation isn't about the technology, but changing how your business works

I've spent my entire career around technology. 

I started coding when I was 12 years old after becoming fascinated by computers that my father would bring home. I built websites during the early days of the internet, worked across software and technology businesses, helped scale SaaS organizations from startup stage to more than $100 million in revenue, and today I lead Product and Technology at ITG powered by Storyteq. 

Over that time, I've seen several major technology shifts reshape the way businesses operate. The rise of the web. Digital transformation. Cloud computing. Mobile technology. 

AI is the first technology since the internet that genuinely feels as transformative. But despite all the headlines, hype, and anxiety surrounding it, I think many organizations are focusing on the wrong question. 

The question isn't whether AI will change business. The question is whether businesses are prepared to change themselves.

Everyone keeps talking about AI as though it's something entirely new. In reality, we've been here before. 

When digital emerged, businesses had to rethink processes, operating models, and customer experiences. When cloud technology arrived, organizations had to rethink infrastructure and software delivery. Every significant technology leap has required organizations to change the way they work in order to realize the benefits. 

AI will be no different. 

Technology has leapt forward. New opportunities for automation now exist, whether that’s content itself or the processes behind it. The challenge for businesses is working out how to transform their operating models to make the best use of that technology and become as efficient as possible. 

That's why I don't see AI transformation as a technology program. I see it as a change program. 

Every organization will move at a different speed. Some will take a cautious approach, using AI with significant human oversight. Others will strive for highly automated, agentic workflows with minimal human intervention. There isn't one right answer. 

The important thing is recognizing that successful AI adoption isn't about deploying a tool. It's about redesigning the way work gets done.

One of the biggest challenges I see today is perception. 

Everywhere you look, somebody appears to have solved AI. Open LinkedIn and someone claims they've replaced entire departments with agents. Open Instagram and you'll find stories about businesses running themselves with autonomous marketing, sales, and operational teams. 

It's easy to look at that and feel like you're already behind. The reality is very different. Nobody has fully cracked this yet. 

The technology is moving so quickly that organizations across every sector are still figuring out what works, what doesn't, and what meaningful transformation actually looks like. 

Pricing is just one area of AI that has completely transformed in the last six months or so. To me, it’s reminiscent of the first data on mobile phones — at first, providers gave us ‘all-you-can-eat’ data, but when everyone started using it more frequently, limits were introduced, and that’s the standard we still see today. 

AI vendors have done the same thing. Limits were pretty hefty to start with, people got used to how much they could use, and then suddenly those limits were squeezed. One of the most popular LLMs and AI assistants is now roughly five times more expensive for the same usage versus 2025. Brands are having to reevaluate their investments because suddenly it doesn’t feel so cheap. 

The point being that even when you think you’ve cracked AI, it changes again — seemingly overnight. 

Of course, there are companies doing some incredibly interesting things. We work with organizations that are actively exploring how agentic workflows and generative AI can radically reduce content production times. Businesses that once measured output in weeks are beginning to think in days, and increasingly in hours. 

But even the most advanced organizations are still learning. There is no universally accepted playbook. Every business is having to find its own path.

One of the reasons there is so much uncertainty is because AI is evolving at an unprecedented rate. Historically, transformative technologies have taken years, and often decades, to be fully embedded across enterprise organizations. 

AI is different. Capabilities are improving almost weekly. New models emerge constantly. Costs change. Infrastructure evolves. Entirely new approaches appear seemingly overnight. 

The technology is currently moving faster than most organizations can realistically adapt. That's not a criticism of businesses. It's simply the reality of organizational change. 

Businesses need governance. They need training. They need new skills. They need new operating models. They need people to understand how to work differently. 

Technology can evolve in a matter of weeks. Transformation rarely can. 

That's why leaders need to stay grounded. The temptation is to chase every new development. The smarter approach is to focus on where AI can create meaningful value and then build a practical roadmap around those opportunities. 

Ask yourself, is this AI for AI’s sake, or are we actually focusing on our customers’ real challenges? That’s the north star, and we can’t afford to lose sight of it.

I remember learning a phrase when I was in my early computing classes as a teenager:

Garbage in, garbage out.

Decades later, it's still true. Despite all the sophistication of modern AI, it is not a magic bullet. If your data isn't in good shape, AI won't fix it. If your processes are broken, AI won't magically make them efficient. If your teams don’t have time to work on creative and strategy, AI won’t make your content land with any greater impact. If your operating model is fundamentally flawed, AI will simply help you move faster in the wrong direction. 

Too many organizations are searching for AI to solve problems that actually stem from poor foundations. Successful AI transformation starts with good data, clear processes, and a strong operational backbone. Only then can automation deliver real value. 

AI can help check, balance, and optimize. But it still needs something strong to build upon.

Another mistake I see regularly is organizations approaching AI task by task. They look at a workflow and ask:

"Can we put AI here?" 

"Can we add an agent there?" 

"Can we automate this step?" 

Those aren't bad questions. But they're rarely transformational questions. The more important question is:

That's a completely different conversation. 

When you take a holistic view, you often discover entire steps in a process that no longer need to exist. Systems that can be simplified. Handoffs that can be removed. Activities that can be automated end-to-end rather than improved in isolation. 

Sometimes the answer isn't adding more technology. Sometimes it's removing complexity altogether. That's where the biggest opportunities tend to emerge.

Perhaps the most visible impact of AI today is the speed at which work can happen. This is particularly clear in marketing and content operations. 

Just six to nine months ago, the idea of taking separate assets — a model, a product, and a background — and instantly combining them into a photorealistic campaign asset would have felt unrealistic. The ability to animate that content and generate countless variations at scale felt even further away. 

Today, those capabilities exist, and the implications are significant. 

What does that mean for photoshoots? What does it mean for creative production? What does it mean for scaling content into hundreds or thousands of variations? Are there any no-go areas for AI, where the perceived lack of authenticity may compromise brand values? 

Leading organizations are already exploring these questions. Their ambition is clear: move from weeks to days, from days to hours, and ultimately from an idea in the morning to content ready for activation by the evening. 

That level of speed changes the economics of marketing, production, and customer engagement. And speed, increasingly, is becoming a competitive advantage.

When I look at organizations genuinely at risk of falling behind, it isn't because they haven't implemented AI everywhere. It's because they aren't exploring what's possible. 

If an organization is restricted to a single provider, a single model, or a highly controlled experiment, I think that's a warning sign that you might be on the wrong path. If AI adoption begins and ends with basic productivity tools, that's another indicator that you’re not fully understanding this conversation. 

The organizations making meaningful progress are experimenting. They're evaluating different models. They're learning where various technologies excel. They're exploring agents, integrations, and new ways of connecting systems and data to unlock the full potential of their content. They understand the way they work currently, the way they’ll need to work with the tech in play, and the outcomes they want to achieve. 

Because understanding is ultimately what creates competitive advantage. Not hype. Not headlines. Not fear of missing out.

The real divide emerging today isn't between organizations that believe in AI and organizations that don't. Most businesses already recognize AI's potential. 

The divide is between organizations that treat AI as another piece of software and those that recognize it requires genuine transformation. 

The technology will continue to evolve. Costs will change. New models will emerge. New capabilities will appear. But the businesses that succeed won't necessarily be the ones with access to the most advanced technology. 

They'll be the ones willing to rethink how work gets done. The ones willing to challenge old processes. The ones willing to build strong foundations. And the ones willing to focus on the simple questions: 

Where is the waste? 

Where can we be more efficient? 

Where can we create a competitive advantage? 

If you start there, AI becomes much more than a technology initiative. It becomes a catalyst for building a faster, smarter, and more effective business.