So far Marketing has become AI‘s most widespread commercial field of application. It enables to deepen merchants‘ knowledge about their clientele. Of course effectiveness is a matter of setting the right criteria for what is needed to be known. And it helps tailor the offered merchandise and services fit for highest customer satisfaction. This is a race that has already begun several years ago and bestowed sound market leaderships to its early adopters like Google, Amazone, Alibaba or Facebook.
Where else will we see disruptive increases of productivity? I would guess that any knowledge work segment of our economies could benefit from delegating detailed analysis and search for prior experiences to AI. Especially in the fields of doing things a first time AI could help reduce the risks of failure by providing the more comprehensive failure possibilities statistically weighted by their potential influences on expected performance results. Operations Research Analysis methods applied so far in many fields of absolutely failure intolerant applications will experience a game changing accuracy and help to prioritize any issues to be addressed in more detail almost simultaneously at concept definition shortening time to launch of new solutions .
The reality of modern product and process development already is by the creation of digital twins. Of course simulation models require validation by real experimental champagnes to be sure results are matching. Reflecting back into times of beginning Computer Added Manufacturing it is just a matter of time until we will see complete implementations of Innovations developed and tested digitally before seamlessly evolving into Computer Added Manufacture by Robot factories, getting their work orders directly from the server hosting the fully developed digital model. Whether by 3D printed or tool dependent shaping processed components assembled by robots. No utopiasm for today anymore! But who will develop such practice first? In who’s interest could this be? Why not robot manufacturers? Their market share potential can benefit from how universal their machines may become applicable. But maybe they don‘t think of that yet, as business is soaring today anyway. It wouldn‘t be the first industry that neglects to do the right things at the right time.
Unfortunately we are living in a world lacking ambitions for excellence. Most larger companies only aspire to just become the fastest second in their markets and keep waiting for a trailblazer one could follow but then hope to overtake him. The problem of such a strategy is that it can‘t work without the kind of Human Resources needed when wanting to start the pursuit of a pioneer. For success it is necessary to be best prepared for opportunities that may come up. And that starts with the capabilities of companies‘ employees. Champions develop from their strength in relevant fields by improving them faster than their rivals can. Of course, if you have a team that can catch up with a pioneer faster than anybody else can, chances are you will really surpass the pioneer. Simply by means of improving the strengths at a faster pace than the challenged party can. It is easy to observe in sports and not any different in business.
With Innovation Implementation risk minimization by means of ubiquitously outspread of AI the entry barriers into the contest for the best solutions will be significantly lowered. Those who know best how to use AI and where to get the most suitable experience data from, will prevail. The big boost for that will be borderless communication possibilities and room for shared knowledge collaboration. However, in order to handle such liquid workflows among undefined collaborators in diverse locations in a fair manor, identification of origin for knowledge contributions will be required by some sort of Distributed Leger Technologies. What a pity, block chain being today mostly associated with crypto currencies, in particular Bit Coin, currently discredited by excrescences of greed for financial lewdness of to just relying on the greater fools theory. Of course it works as long as there are new buyers for unique data-sets at the prices offered by the current owners of those. As tempting as the idea may have been at the beginning of applying block chain in the field of crypto-currencies, the real Clue however is the genuineness of a unique data-set at  it’s currentness with the link to all its history and that may be allocated to an exact user at literally no cost. To be indestructible it is usually saved at each interaction on a determined multiple of specific decentral physical locations, for which only the data-set itself can deliver the key to decrypt it properly.
Once World Intellectual Property Office will issue a bill of rules how to manage such a Distributed Leger archive between innovation collaborators, each contribution or use identified by a check-sum made unique via encryption combining the transaction time seal and user fingerprint with it. By doing so International Patent Offices would become able to trace compilations of relevant information that led to new patent applications evidencing whether something was really new or not. It could be analyzed by AI without extra manpower. But even if that led to a reduction in patents, it will further Copyrights and help to define brands in the future. Once such a system would be used to entice shared creativity all over the globe, it will become possible to let the creators and enablers benefit from the commercialization on a fair shared basis.