Innovation Ecosystem Understanding through an AI-driven approach

I always find it interesting when different though-strands seem to collide. You can put that down to serendipity, fate, luck or just being in the right spot at that time. I have always been a fan of the book “The Medici Effect; breakthrough insights at the intersections of ideas, concepts and culture” by Frans Johansson.

I like to think I am often colliding at the innovation intersections where I keep finding lots of synergies that feed my research and innovative curiosity to support others.

For the past six or so weeks I have been looking into Ecosystems and one of those (famous) strands took me to “Natural Language Understanding” and I read an article by Mark Seall, Head of Digital Communications at Siemens called “How AI is shaping the future of marketing communications” and it got me curious.

Now I am part of Siemen’s SIEx community (link to some published work from the community) that has a group of “savvy” individuals offering outside-in thinking trying to influence and shape different conversations taking place in and about Siemens. In this group are different voices bringing in their expertise and insights. We look to engage in issues and challenges that give value and impact, sometimes it works, other times less so!

So I approached Mark Seall and we had an initial discussion on the use of AI and this natural language tool they have been using. Siemens has a collaboration with Storyroom.ai. Storyroom provides a set of unique datasets and AI to meaningfully connect concepts, ideas or thoughts, to drive awareness and engagement.  Storyroom is a venture-backed AI startup, based in California.

Mark offered me an opportunity to “play with the AI tool” and I initially did some knowledge understanding around the topic of “Digital Factories” which provided an interesting set of keywords and different visuals or possible conversation maps.

I have provided some feedback on this to his team and hopefully, as this tool is in Beta it will give them some helpful points to improve their next round in developing the tool.

What I decided to do was go a whole lot deeper and apply my topic expertise in “Ecosystems”

Now comes the second Serendipity recently. I am a great admirer of the work that Itonics offers around Innovation Management. Recently they have also been exploring AI-Driven Innovation and in a very recent post “Why AI-Driven Innovation Should Be On Your Radar”  they are highlighting a recent Hype Cycle graph for Innovation Management Techniques,2021.

That got my interest up as I show here in this adopted visual of the Hype Cycle for Innovation Management

It seems the current peak of expectation and the emerging innovation trigger are in my present research focus. Now that I liked!

According to Gartner, “AI-driven innovation refers to the use of artificial intelligence technologies in the process of innovation.”

” AI-driven innovation is positioned on the rise of an innovation trigger, Gartner believes, AI-driven innovation is considered to hold potentially transformative means to “drive high-impact innovation at scale through the discovery of new ideas and rapid progress through the innovation pipeline”.

Gartner says, “this suggests that the innovation management technique will enable new ways of doing business across industries, resulting in significant shifts in industry dynamics.”.  “AI-driven innovation could either be in the form of new inventions like new drugs or material discovery in specific domains or could be used to boost agility and efficiency in an end-to-end innovation process pipeline across use cases and industries.”  

Back to the AI tool and my “Ecosystem” work 

So my work, at the beginning of applying AI has been to interrogate this tool on the following aspects of “Ecosystems”. I generated different results for:

• Ecosystems
• Innovation Ecosystems
• Business Ecosystems
• Sustaining Ecosystems, and recently back to
• Ecosystem Management.

Initial output for “Ecosystems”

I found the general use of “Ecosystems” narrowing down the searches to more Ecosystem-related or orientated to Business are still providing interesting triggers like “Novel Ecosystems”, “Ecosystem Models”, “Ecosystem Service”, “Ecosystem Thinking” and “Ecosystem Design”

In my early rounds, I decided in taking out “Sustainability”, “Circular Economy”, “Life-Cycle Assessment,” to gain a better amplification of the points above. These different searches have given some good food for thought on future approaches to “Ecosystems” Both outputs or rounds offer different approaches to Ecosystems.

Then investigating the Outputs for “Innovation Ecosystems”

As for “Innovation Ecosystems” that yielded a veritable host of strands of associated thinking. These included “Value Networks”, “Transferring Knowledge”, “Diffusions of Innovation”, “Network Design and Theory”, “Co-creation, “Platform Design”, “Competitive Positioning,” “Dynamics of Innovation” and “Innovation Impact” among some others that have taken my thinking in new directions. More on those in the weeks ahead.

Then I found comparing “Innovation Ecosystems” with “Business Ecosystems” really separated the two in some unique ways.

What I did find was that much as “Innovation Ecosystems” was certainly a rich data set, the “Business Ecosystems” one was much richer. I will discuss this in a further post over at my Ecosystems4innovating posting site in the coming days.

A time to absorb and reflect on what I am learning here

I am still absorbing each search and revision, so as to understand changes and potential value points for part of my Ecosystem work ahead.

I have found applying this “natural language generation” technique as helpful, it has accelerated and streamlined my research, making any analysis faster, it has been sometimes puzzling but I feel you are gaining from “real-time” data and keyword associations that provide new insights. The end results will certainly help shape my thinking into the future of Ecosystem Management.

AI can enhance value and provide signals to emergent trends

I do think Siemens, in pioneering this technique, does give them a very interesting edge in the marketing communication area, which they have been applying this tool to.

There are many future possibilities they can explore and it is giving me a whole different level of understanding of Ecosystems and what has a positioning, value. It is giving me greater confidence in what makes up the different Ecosystems I have so far investigated, and applied this tool.

In the work, so far, I have undertaken I have found growing insights and triggers. Applying this learning and converting this into “future understanding” is my next step.

The next steps get interesting………..

In my second post on AI-driven innovation, I looked closer at the differences for building an Innovation Ecosystem against focusing on a Business Ecosystem. One seems on the first investigation “richer” than the other. The link to the post is here