Artificial intelligence is rapidly becoming part of everyday business operations, but many organizations are still waiting for the “right moment” to adopt it. According to Julia White, Chief Marketing Officer at Amazon Web Services (AWS), that hesitation may be the biggest obstacle to success.

Speaking at VivaTech in Paris, White shared a simple but powerful message: companies will only become effective at using AI if they are willing to experiment, make mistakes, and continuously improve. Reading about AI is no longer enough. Real value comes from hands-on experience.

AI Delivers Bigger Results When Workflows Are Redesigned

Many organizations begin their AI journey by adding AI tools to existing processes. While this often delivers measurable productivity gains of 10% to 30%, White argues that the real transformation happens when businesses rethink how work gets done.

Instead of simply accelerating existing tasks, leading organizations redesign entire workflows around AI.

AWS has seen this firsthand. Creating a new webpage previously required several team members and roughly three hours of work. Today, AI agents complete much of the process, reducing production time to around 30 minutes. For a company that publishes thousands of webpages every year, those efficiency gains scale quickly.

The lesson extends far beyond marketing. Across software development, operations, customer support, and internal processes, AI creates the greatest business impact when organizations redesign workflows rather than automate isolated tasks.

Human Judgment Remains the Competitive Advantage

Despite rapid advances in generative AI, White believes creativity and strategic thinking remain fundamentally human responsibilities.

AI excels at generating ideas, organizing information, and accelerating execution. It can act as an intelligent collaborator that helps teams explore alternatives and iterate faster. However, it still struggles to produce authentic storytelling, emotional resonance, and the kind of creative judgment that defines strong brands and exceptional customer experiences.

At AWS, AI serves as a creative partner rather than a replacement for marketers. Human teams continue to make the final decisions around messaging, positioning, and brand identity while AI supports brainstorming and content development.

This reinforces an important principle for organizations adopting AI: competitive advantage increasingly comes from combining AI-powered productivity with human expertise, domain knowledge, and decision-making.

Building an AI Culture Means Accepting Failure

Perhaps White’s most valuable insight concerns organizational culture rather than technology.

She argues that companies cannot expect employees to master AI without giving them permission to experiment. To encourage this mindset, AWS introduced an internal “Be Brave” award that recognizes bold experiments, including those that fail.

Rather than treating unsuccessful AI initiatives as wasted effort, the company views them as part of the learning process.

White also emphasizes the importance of creating dedicated time for experimentation. AWS schedules meeting-free learning days that allow employees to explore new AI tools without the pressure of daily operational work.

For technology leaders, this highlights an often-overlooked aspect of AI adoption: successful implementation depends as much on organizational behavior as on selecting the right models or platforms.

Personalization at Scale Is Becoming Practical

One of the opportunities White finds most exciting is AI’s ability to deliver personalized experiences that were previously too expensive or complex to implement.

Marketing teams have long envisioned creating content tailored to every individual customer, but achieving that level of personalization at scale was rarely practical. AI is beginning to change that equation.

The same principle applies across software products, customer service platforms, and digital experiences. As AI becomes more capable of understanding context and adapting outputs, businesses can move toward highly personalized interactions without dramatically increasing operational complexity.

What This Means for Technology Leaders

AI adoption is entering a new phase. The challenge is no longer whether organizations can access powerful models, but whether they can integrate them into real business processes.

The companies creating the most value are not simply deploying AI tools. They are redesigning workflows, encouraging experimentation, investing in employee learning, and keeping human expertise at the center of critical decisions.

For CTOs and technology leaders, the message is clear: AI capability grows through practical experience. Organizations that create space for experimentation today will be far better positioned to scale AI successfully tomorrow.

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