Well, what's next? Always the million dollar question, especially now as artificial intelligence (AI) is in the midst of the tech hype. Since our own FIBRES' development will entwine with AI, it's due time to take a look into some of the concepts and terminology. I'll try and outline at least how we approach these from our business point of view.
How we think of artificial intelligence
In Gartner's insights on the tech trends for 2017 AI, inclusive of machine learning, has reached its tipping point, and is now rapidly expanding into various applications and services. Forerunners are using the likes of IBM Watson for their intelligence and innovation purposes.
Forbes published an article based on Forrester Research's and IDC's research, saying that compared with 2016, there will be a +300% increase in investments in AI in 2017. At the same time, IDC estimation for AI market growth is from $8 billion in 2016 to more than $47 billion in 2020. Staggering numbers! There's certainly some business to be made there ;)
Now, our main domain is to provide a simple tool that helps organizations and networks to create a better understanding of the future. We look at artificial intelligence as an enabler that will help in finding new opportunities and a new strategic direction for our customers, and - ultimately - in planning the organization-specific strategic roadmap itself. And just to clarify, I am talking about (big) data analysis, yes, but "data" in unstructured forms. In short, that's about extracting new understanding from masses of text-format data rather than numbers.
From hybrid foresight to smart strategies
Some of our followers may have noticed that we are now toying around with the term 'hybrid foresight'. It sounds a bit sci-fi and a bit, to be honest, a hype word. But, what we see behind that pair of words is a real combination of human capabilities and machine-generated semantic analysis. In addition, it is about machine learning of human judgment over subject matter correlations and significance. How all this will then manifest itself in our software, is another thing. As an end goal, hybrid foresight basically helps in finding new clusters of emerging phenomena, based on a big amount of written data. Our platform will learn from its users, therefore providing a breeding ground for truly discovering something new. It serves for innovation purposes. It serves for market insight and foresight purposes. It will ultimately help you plan and execute your strategy.
Also, I want to mention crowd collaboration, which in our terms, can mean, well, exactly that. We want to provide a platform for discussion, writing up insights and strategic steps with your preferred "crowd". Whether the "crowd" consists of groups of people internally, of partners or perhaps other networks. It's people that use the insight to take those business decisions. And as a general rule for hybrid foresight also, the machine learning part gains more value from bigger crowds.
Intelligent strategies, or simply smart strategies, is something that taps into the insight, and constantly lives and breathes with the crowd creating it. From the strategy planning and execution points of view, 'simply smart' stands for crafting truly insightful strategies, yet simultaneously communicating an actionable and transparent roadmap.
Obviously, some of these elements are a bit further down the road. During 2017, we are taking the first very concrete steps into introducing real hybrid foresight capabilities: combining the power of human and artificial intelligence for discovering something new. All said, it's good still to remember that software and tools can do an awful lot - but it is in the hands of humankind to choose what we do with them.
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