Don't treat AI as merely a product feature or a productivity tool. Moonpig's tech chief views it as a fundamental infrastructure shift, like the electrical grid. Leaders should focus on fostering an adaptable mindset for systemic change, rather than fixating on today's specific AI applications.

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Don't view AI as just a feature set. Instead, treat "intelligence" as a fundamental new building block for software, on par with established primitives like databases or APIs. When conceptualizing any new product, assume this intelligence layer is a non-negotiable part of the technology stack to solve user problems effectively.

Instead of merely 'sprinkling' AI into existing systems for marginal gains, the transformative approach is to build an AI co-pilot that anticipates and automates a user's entire workflow. This turns the individual, not the software, into the platform, fundamentally changing their operational capacity.

Don't just sprinkle AI features onto your existing product ('AI at the edge'). Transformative companies rethink workflows and shrink their old codebase, making the LLM a core part of the solution. This is about re-architecting the solution from the ground up, not just enhancing it.

AI is a 'hands-on revolution,' not a technological shift like the cloud that can be delegated to an IT department. To lead effectively, executives (including non-technical ones) must personally use AI tools. This direct experience is essential for understanding AI's potential and guiding teams through transformation.

CMO Laura Kneebush argues that trying to "get good at AI" is futile because it evolves too quickly. Instead, leaders should focus on building organizations that are "good in a world that's going to constantly change," treating AI as one part of a continuous learning culture.

Using AI for incremental efficiency gains (10% thinking) is becoming table stakes. True competitive advantage lies in 10X thinking: using AI to fundamentally reimagine your business model, services, and market approach. Companies that only optimize will be outmaneuvered by those that transform.

Competing in the AI era requires a fundamental cultural shift towards experimentation and scientific rigor. According to Intercom's CEO, older companies can't just decide to build an AI feature; they need a complete operational reset to match the speed and learning cycles of AI-native disruptors.

Forcing an 'AI culture' is short-sighted. The real goal is to foster a culture that prioritizes continuous growth and learning. This creates an organization that can adapt to any major technological shift, whether the internet, mobile, cloud, or AI. The specific technology is temporary; the capacity to learn is permanent.

Successful AI integration is a leadership priority, not a tech project. Leaders must "walk the talk" by personally using AI as a thought partner for their highest-value work, like reviewing financial statements or defining strategy. This hands-on approach is necessary to cast the vision and lead the cultural change required.

The most successful companies are those that fundamentally re-architect their culture and workflows around AI. This goes beyond implementing tools; it involves a top-down mandate to prepare the entire organization for future, more powerful AI, as exemplified by AppLovin's aggressive adoption strategy.