AI transformations and radical creativity

In this blog, I’ll draw on my experience to help: first by outlining a trajectory for building an AI-ready organization and executing transformation – then by sharing how radical creativity can help you break free from old patterns.  

No direct flights to transformation 

What does it take to orchestrate a successful transformation? At the strategic level, top management must strive to minimize turbulence during the journey. The first step is acknowledging that leadership enablement, employee engagement, and a supportive culture are all essential in turning transformation into reality. The second is leading synchronized changes across strategy, structure, processes, culture, and technology.   

Change strategies should address organizational conflicts rather than avoid them – and define a clear vision of key game changers, such as establishing a competitive cost structure and generating cash in constrained environments.  

True transformation begins with structuring around value. Organizations typically enhance value by moving from siloed departments to cross-functional teams overseeing entire service or product categories. Whether you choose this path or another, remember that customer experience isn’t always a primary driver of value; in aviation, for instance, optimizing routes, pricing, and operations certainly take precedence. It’s also good to keep in mind that though value stream charts can help optimize factors that truly drive value, they may not engage employees effectively.   

At the execution level, transformation requires adapting to new models, making tough decisions, and sustaining a performance-driven culture. Speed and communication are crucial. Strategy alone isn’t enough – it must be supported at every level of the organization. Experienced employees can provide valuable insights, and aligning leadership skills with the demands of the transformation can enhance progress.   

Innovation, ambition, and diverse perspectives are all also vital for fruitful transformation. Some industries, like oil and gas, must follow strict safety protocols that limit trial-and-error approaches, but there are still ample opportunities for rapid iteration in various processes.  

However, every gain comes with a risk. Digitalization and transformation can enhance efficiency and innovation, but they have psychological and ethical implications for employees. In my experience, there are three true drivers for sustainable change: respect, engagement, and empathy.   

Transformation thrives when employees embrace new ways of thinking and working. Resistance often stems from anxieties about job security or diminishing status. Engagement can help bridge knowledge gaps, but status concerns are more difficult to address. I have also witnessed how transformation fatigue impacts individuals involved in long-term or chaotic transformations.   

AI can fuel your transformation journey 

AI-driven transformation requires a solid business case. Understanding how your organization, customers, and competitors use AI is critical.  

Finding use cases may be easy, but if you want AI to have a transformative effect, there might be limited organization-level initiatives to drive the change. Moreover, competitive advantage is difficult to achieve if everyone uses the same models and tools. What will set you apart – your unique data set combined with AI?   

It’s a good idea to start with internal AI applications before customer-facing implementations to mitigate risks. Chevrolet’s chatbot is a great cautionary example. It was designed for car selection and service appointments but misused for everything from coding assistance to competitor recommendations because its capabilities exceeded its intended scope.   

In implementations, typical bottlenecks include data quality, availability, and AI output accuracy. Some issues improve over time as AI models learn (even if you don’t do anything). You can also leverage your AI capabilities by cleaning data sets. But there might be need for additional effort. For instance, AI output quality can be in technically appropriate format, but may not be suitable for the intended use.   

Chances are that your AI adoption relies on people without organization-level vision. You need to ensure you are collecting the right data, and that you have necessary structures to maintain and govern it, i.e., data management strategies and plans. While AI can help create inspiring visions, data may reveal past mistakes that need addressing. Understanding what AI vendors can provide versus what your organization must handle internally is essential.   

From a people perspective, AI increases workplace autonomy, reducing human interactions. This can boost short-term productivity, but long-term impacts are anyone’s guess. Only one thing seems clear: profound transformations are on the horizon. AI is poised to revolutionize industries, redefine professions, reshape organizations, and ultimately alter the very nature of work itself.  

Building the runway to integrated intelligence   

Competing in the age of AI means using a computer to model intelligent behaviour with minimal human intervention. It requires so much more than mere data collection – you have to enrich, contextualize, and structure data to power AI tools. Your organization also needs frameworks that enable timely and usable information flows.  

In essence, you need to orchestrate information to charge AI-driven decision-making. The companies that focus on making data usable (and wielding it with strategic precision and operational discipline) will be the winners of the data-driven economy.  

Is your organization ready for AI-driven transformation? When assessing AI readiness, key considerations include evaluating the current digital technology portfolio, such as AI-powered analytics and chatbots, and planning for future technology enhancements to add value. Identifying primary boundaries or weaknesses in AI readiness and exploring ways to improve them is vital as well. Expanding AI into the desired goals and activities can enhance human creativity, productivity, problem-solving, and idea generation, particularly through generative AI.  

If you are indeed ready, remember that fostering a culture of experimentation and psychological safety is essential. Investing in systems that minimize the costs of failure – such as controlled releases and automated rollbacks – encourages innovation.   

A key component of building a runway to integrated intelligence is effective AI governance operating across automation, augmentation, and data richness. When these dimensions are aligned, you can fully incorporate AI into your operations to enhance performance.   

Fundamentally, leading AI change from strategy to execution requires leveraging data and value at every stage of the (iterative) strategy cycle. A learning-by-doing approach strengthens dynamic capabilities, as insights often emerge from combining weak signals across multiple data sources. Generative AI enables faster, better informed decisions – and helps transform business questions into beneficial data-driven solutions.   

Reaching higher altitudes with radical creativity 

How can radical creativity and AI-driven transformation shape the future of your business? To provide context, digitization and digitalization revolve around two system categories:   

1. Rule-based systems – ERP, accounting, email, and social media rely on predefined rules to process and store data.   
2. Cognitive systems – AI, machine learning, and generative AI infer patterns from data for tasks like prediction and classification.   

Unlike rule-based systems, AI learns autonomously from data, operating as a ‘black box’ without predefined rules. AI transformation mirrors human cognition; modelling thought processes.  

ChatGPT, for instance, is a language model powered by transformers. While it doesn’t think like a human, it generates text based on patterns in data, mimicking certain aspects of human language processing. 

Likewise, creativity doesn’t follow strict rules; it thrives when boundaries are pushed. Creativity plays a crucial role in problem-solving – and it manifests in diverse ways. While incremental creativity builds upon existing ideas, radical creativity fundamentally changes or disrupts an existing system.  

Radical creativity challenges norms, boosting problem-solving and unconventional thinking – and considers failures as part of the learning curve. Fostering radical creativity helps organizations design structures that simultaneously prioritize data utilization and enhance human collaboration, ultimately cultivating a culture that reaps benefits from both data insights and employee engagement.  

You don’t have to look far to find examples of radical creativity. From the way we communicate to how we travel, it has led to life-changing inventions like the Internet, smartphones, electric vehicles, and 3D printing.   

Currently, AI is a major disruptor. Companies successfully leveraging AI gain competitive advantages, shifting market dynamics. In banking, AI-driven risk management and trading have revolutionized operations. Similarly, in the electric vehicle market, AI has set new standards for innovation.   

Both radical creativity and AI-driven transformation rely on innovative thinking and advanced cognitive skills. Companies must harness them to assess whether their business models remain competitive. Nokia’s decision to adopt the Windows platform in 2011 highlights how new entrants can challenge long-held assumptions and showcases the far-reaching impacts of a misaligned strategy.   

We all know that major market shifts elicit strong emotional reactions. Organizations often resist change to maintain the status quo, leading to missed opportunities. This underscores the need for companies to evaluate their competitiveness within new platforms and adapt to changing industry dynamics, rather than clinging to outdated models. 

In AI-driven transformations, radical creativity can help you find fresh manoeuvres to break traditional patterns – and shape organizational structures that foster a data- and human-driven future.