Managing Director, Americas
The rise of generative AI has transformed the way people work. We’ve seen amazing tools for generating text, images, and even software that should be integrated into our work. But the most important next frontier for us and for our clients is actually: What can we do differently as a result of that?
And that is creating an “impossible strategy” – a strategy for AI-powered growth that leverages innovations that were previously impossible.
The next wave of growth isn’t going to come from digital transformation, or doing the same things faster and cheaper with AI. It’s going to come from autonomous transformation, uncovering entirely new possibilities.
Companies are already carving out new markets through autonomous transformation, applying AI in ways unimaginable just a few years ago.
Intel: Building the first autonomous factory for chip production.
NotCo: Creating an autonomous food generator, Giuseppe, that designs novel food combinations, such as a plant-based milk containing pineapple and cabbage to mimic dairy milk.
Shein: Pioneering autonomous fashion with an automated model that launches and tests thousands of products daily, bypassing traditional human-driven analysis.
The benefits of this approach are of course efficiency, but also the ability to develop entirely new, and better products and services, enabling innovation departments to stay ahead of the curve and maintain a competitive edge.
It’s important to shift focus from individual AI tools, like a tool that helps you write an email, to holistic, transformative applications that piece together new business models and new products that take all of those capabilities together and figure out something that was completely unimaginable and impossible before.
If we think about the ways you can capture the opportunity around autonomous innovation, you can think about it in terms of the products and services, and the operating model:
AI Efficiencies: Improvements to existing products or services, making them faster and cheaper using AI without changing the operating model.
Example: AI-enhanced customer service that automates routine tasks.
AI Systems: Innovations that implement a new AI-native operating model to run the business differently.
Example: NotCo uses AI (Giuseppe engine) to optimize plant-based milk production.
AI Experiences: AI-native products or services that offer a different user experience but maintain the same core business structure.
Example: Adobe Firefly enhances Photoshop by generating and editing images using AI.
AI Breakthroughs: Entirely new products or services built on AI-native models, transforming both the experience and business operation.
Example: Showrunner allows users to create personalized TV episodes using generative AI.
It’s important to shift focus from individual AI tools, like a tool that helps you write an email, to holistic, transformative applications that piece together new business models and new products that take all of those capabilities together and figure out something that was completely unimaginable and impossible before.
If we think about the ways you can capture the opportunity around autonomous innovation, you can think about it in terms of the products and services, and the operating model:
Materials companies have struggled to implement circular reuse models while maintaining quality. Variability in recycled material quality typically meant having to use a large amount of virgin material. AI now enables them to create new formulations every single time – something that was previously impossible.
Duolingo uses generative AI to create personalized learning experiences, adapting to each learner’s progress. This enables real-time feedback, customized practice, and targeted lessons, dynamically adjusting to strengthen weaknesses and provide a level of tailoring that was previously impossible.
In pharmaceutical research, AI can now design millions of potential drug molecules, predict their properties and optimize them for safety and efficacy. Researchers at McMaster and Vanderbilt University used AI to identify new treatments for bacterial infections that were previously impossible to find by traditional methods.
The first thing is to make sure you’re thinking about the fundamental capabilities of AI that can enable these (im)possible innovations.
To capture the potential of autonomous innovation, businesses should embrace a future-back mindset and go beyond mere automation.
Four key steps:
Hunting for maximum complexity
Hunt for problems and situations in your business and industry where complexity is incredibly high and that overwhelm human capabilities, such as optimizing hospital systems or construction projects.
Questions to ask yourself:
Mine the previously impossible
Look back to find previous solutions and business models that were previously deemed impossible due to economics, capabilities, lack of data or other constraints. For example, peer-to-peer car sharing faced challenges with identity verification, damage assessment, and cost management. AI could address these issues and potentially revitalize this business model.
Questions to ask yourself:
Imagine beyond today’s AI models
Imagine beyond what today’s LLMs and tools can do. Envision future possibilities like models with 3D spatial awareness, emotional intelligence, and advanced robotics.
Imagine your AI native operating model
Identify ways in which you will need to transform your operating model to deliver these innovations – and how they can help you capture as much value as possible. For example, AI could revolutionize museum archival processes, which are often understaffed and underfunded due to their tedious nature.
Questions to ask yourself:
By embracing a future-back mindset and leveraging the transformative power of AI, businesses can achieve previously impossible outcomes and unlock unprecedented growth. As AI continues to evolve, the potential for innovation will only expand, making (im)possible strategies not just a possibility, but a necessity for businesses looking to thrive in the age of autonomous transformation.
To help companies get started, we’ve developed a new approach called the “(Im)possible Strategy Sprint.”
In these sprints, we collaborate with clients to set a clear vision and understand their growth goals. We conduct competitive and industry analysis through various lenses we’ve discussed. We also bring in experts from our AUTONOMOUS summit for fresh insights.
Together, we identify revenue growth opportunities—whether optimizing existing streams, exploring new adjacencies, or uncovering previously “impossible” innovations. Finally, we create a blueprint for the organizational changes needed to fully capitalize on these opportunities.
The Impossible Strategy Sprint can help companies unlock both efficiencies in existing operations and groundbreaking new ventures.
Keen to learn more about the Impossible Strategy Sprint? Drop us a note and let’s chat
