2024 started as a banner year for Organizing4Innovation. Our client success stories were compelling – two recent case studies show how our Steering Wheel platform had helped teams navigate complex innovation journeys with remarkable results. Yet beneath this success, subtle warning signs were emerging that I initially struggled to interpret.
Email response rates were declining. Was this just normal market fluctuation, or something more fundamental? The answer came unexpectedly – as a result of a technical challenge with our platform's editor.
The Wake-Up Call
While troubleshooting issues between our editor and automated reporting system, something clicked. As we explored using Large Language Models (LLMs) to enhance our report generation, a bigger realization hit: LLMs could potentially replicate much of our platform's core functionality. To test this theory, I created ten prompts that potentially could help a team getting started with Microsoft Copilot, by defining the goals and setting up a pilot to test the new AI-enabled workflows. The outcomes weren't perfect, but overall the results were good enough to be concerning.
The implications were staggering. Our Steering Wheel platform – six years of development, our pride and joy – had suddenly lost its competitive edge. I remember sitting at my desk, staring at these prompts, feeling a mix of fascination and dread. My go-to comfort food, chocolate, became a frequent companion during those days of processing what this meant for our business.
The Innovator's Dilemma - From the Inside
The irony wasn't lost on me. I'd been working with LLMs since their public debut in 2022, yet I'd failed to see this coming. At first, their occasionally bland or inaccurate responses had lulled me into a false sense of security. Later, I simply didn't want to acknowledge what was happening – a classic case of the innovator's dilemma, something I'd consulted on countless times but was now experiencing firsthand.
Looking back, my journey with LLMs followed a pattern I should have recognized:
- Initial dismissal due to their limitations
- Cognitive disconnect as capabilities improved
- Ego-driven resistance to acknowledging their potential impact
- Finally, the uncomfortable recognition of their transformative power
Practicing What We Preach
The breakthrough came when I realized that what was happening to Organizing4Innovation wasn't unique – it was the leading edge of a wave that would impact countless professionals. LLMs now possess a knowledge base of tools and methodologies that far exceeds what any human could accumulate in a lifetime, available 24/7 with customized responses.
Instead of fighting this reality, it probably is better to embrace it. Those who fought the book press, windmills, steam engines, electricity, and the World Wide Web usually drew the short straw in the end.
Fortunately for me, all those principles we'd taught others – the innovator's dilemma, technology scouting, running experiments, customer discovery – became our lifeline. They weren't just consulting frameworks anymore; they were our survival tools.
Charting a New Course
Durig this challenging transformation, a powerful motivation emerged: If we, as innovation experts, were struggling with this transition, what about other managers and innovation teams facing similar disruption?
This realization helped forge our new direction. The role of innovation consultants isn't disappearing – it's evolving. We're no longer just process guides or methodology experts. Our value lies in:
- Helping teams frame the right questions for AI tools
- Navigating the human elements that AI can't address
- Ensuring real-world impact of AI-powered solutions
- Supporting others through their own AI-driven transformations
Join Us on This Journey
AI forced us to reinvent how we innovate - and in doing so, we found our edge.
Through the ΔX approach, we now help organizations create agentic workflows that make AI adoption real, human-centered, and ROI-driven. Because success with GenAI isn’t about more tools — it’s about making what works visible and repeatable.
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