Advancing innovation | Paul4innovating Innovation Views

Innovation thinking in Ecosystem and Generative AI design.

Innovation thinking in Ecosystem and Gen AI design

I believe there is a real need to construct a different innovation process. We are rapidly seeing the past of innovating simply in terms of operating on our own.

We must question partnerships we have seen work in the past and ask if they are suitable for the future.

Innovation is undergoing a radical change, in opening up to technology, collaborative thinking and the value of generative AI thinking.

For me, ecosystem innovation and generative AI have arrived at that pivotal point to significantly influence future innovation design. It is where we need to question workflows and processes, as openness has become increasingly central to our thinking and development-building process.

Innovation needs reinventing. There are new ways to capture, extract and deliver value. Adopting ecosystem thinking combined with Generative AI will augment, automate and rapidly scale innovation.

I have been exploring this to support those recognizing change is happening to support this innovation transformation. This follows from several posts in building this into a new approach and thinking over innovation designs.

Diving deeper…..

Embrace AI-driven innovation, it is the future.

Embrace the future of AI-driven innovation.

It has been amazing how AI generative thinking (GenAI) has taken hold. It has only been one year since the launch of ChatGPT, then with a follow-up of GPT-4. In a really fascinating routine or guide to how Generative AI developed, then you should read Bernard Marr’s post It is well worth the read.

As he points out, “Today, Generative AI stands as a testament to the power of human imagination and technological innovation. It has grown from humble beginnings into a sophisticated technology capable of producing remarkable output.”

As Barnard Marr opens his post “Generative AI has the unique ability to create. It can generate new content like audio, art, and text, all by learning from a set of data without explicit instructions.” I feel “explicit instructions” need to be carefully managed.

For me, the last six months or so I have been working with ChatGPT to learn different ways to look at focus areas I spend in advising and mentoring and where innovation links into my different work.

This is rethinking the innovation process, how ecosystem thinking and design can shape our collaborative worlds differently, looking much harder at innovation ecosystems and applying different triggers of thought in how AI generative thinking will influence and shape much of the Energy Transition, as my endpoints.

Recently, I have been looking specifically at the way the (traditional) innovation management process will change. The deployment of AI-driven thinking utterly alters my perspective of “delivering” innovation.

Working together to shape innovation for meaningful change

Shaping Innovation for a Meaningful Change

Following on from my initial post, “Our Need is to Shape Innovation Dynamically, ” this post outlines the eight value-adding points that I can help build out and deliver alongside you in different delivery modules to fit your circumstances and budgets.

My value proposition is to work together to create something that shapes innovation for a meaningful change. To support you in building out your innovation competencies, capabilities and capacity that requires a deeper investment in skill development in a culture of continual learning.

It’s a journey, but it promises the rewards of being at the forefront of industry evolution and transformation. It is a journey of building innovation, fitness and dynamics drawn out in a new way of thinking and design within innovation ecosystems.

Within the value proposition, we actively shape these journeys, building adaptability, agility and innovation for long-term success in the changing business environment we all face today.

Our Need Is To Shape Innovation Dynamically.

In today’s rapidly changing business landscape, the ability to build a strong case, stay informed, and think critically is the key to unlocking success and driving innovation.

For me, this landscape is marked by its dynamism. Here, market trends evolve, new technologies emerge, and consumer preferences shift lightning-fast.

In this environment, success isn’t just about being prepared for change; it’s about actively shaping it. But how can you empower those responsible for innovation to not only navigate this terrain but thrive within it?

We need to navigate a very different terrain that requires a deeper investment in skill development in a culture of continual learning.

Building Innovation Ecosystems need to be connected.

During this week, commencing 15th October 2023, I am discussing and explaining a framework for building innovation ecosystems on my ecosystem4innovators.com posting site.

I have been exploring for some time a transformative concept to move innovation into the world of ecosystems. I outlined my proposed innovation framework in the building blocks necessary. The extended series of posts over thirteen or so, are all here on this posting site, summarized in this post of “The building out of the Composable Innovation Enterprise Framework.”

The focus was on proposing to single entities, and now I want to extend this into the future need to build innovation ecosystems that enable and connect the essential components required.

Innovating the future by combining humans, technology, and AI

The interplay potential in exploring the combination of humans, technology and AI

This interplay between humans, technology, and AI is dynamic and involves continuous interaction, collaboration, and feedback between these elements. The future of innovation, by combining these, offers a very rich promise to provide a fascinating and different future.

Firstly, this interplay needs some higher-level thinking to put some insights into what this interplay might look like and lead to:

The future interplays between design thinking, technology and AI

Exploring the interplay between Humans, Technology and AI for design thinking

Why is design thinking regarded as so crucial to the future of innovation in a world of accelerating interplays between humans, technology and generative AI?

By embracing Design Thinking principles differently in the future of innovation, organizations can foster a more profound culture of creativity, empathy, collaboration, and user-centricity. This can lead to the development of innovative solutions that address real-world problems while considering the interplays between humans, technology, and generative AI.

Firstly, we have the interconnected global marketplace as our context

The change toward an interconnected and conscious global marketplace has been of significant importance, reshaping business strategies, consumer expectations, and societal values.

Has innovation changed over the last ten years?

Innovation is certainly a complex and dynamic process that involves many factors and actors and I certainly feel it has been shifting in its focus. I have been thinking of where we have been placing the emphasis over the past ten years.

I decided to ask GPT-4 what major shifts have occurred in how we approached innovation ten years ago and today. It was suggested that these were the following.

Do you agree, what do you feel is missing? I like the broad shifts indicated but what has been missed?

Fusing Human and Technology to Enable Innovation Ecosystems to Thrive

“Making something harmonious” often means we have to reconcile differences to balance out the tensions and issues to enable and make them compatible to work.

“Fusing” human engagement with technology enablement involves creating a harmonious integration of human collaboration and technological tools to enable an ecosystem’s successful development and operation. Is that possible?

How do we go about evaluating all the possible needs of customers, as they are mostly our success arbitrators? We must gain insights and refer through multiple information sources- digital data and direct human responses – than ever before; these insights are becoming essential to our businesses.

Calibrating the right way to use technology to create mutual benefit is an increasing theme across businesses, which means we need high levels of interdependence.

Focusing on the Learning Components of the Composable Innovation Framework

Within the Composable Innovation Enterprise Framework lies the core, the different innovation stacks, and the learning components. Here, I want to briefly talk about the importance of the learning components that support the innovation design and especially the different innovation stacks.

The elements of the innovation stack are designed to support innovation’s core tasks, including learning, absorbing, assessing knowledge management, creativity, design, experimentation, and testing. By modularizing these tasks and their interfaces, organizations can assess their innovation progress by having a complete innovation system available to them, designed on specific stack elements to address knowledge operation requirements in the stage of development to commercialization.

The Innovation Stacks are ready to support different steps in the innovation engagement process

Additionally, with the upgrade in technology and platform approach, we can support the rapidly emerging human-AI collaboration needed for each building block and component and provide a step-by-step validation.

Yet it is the sequence of how we learn that becomes vital to “feed” and build the innovation stacks.