Digitalization or more precisely the "digital transformation" has led us to the "digital enterprise". It strives to deliver on its promise to leverage previously unused data and the information it contains for the benefit of the enterprise and its business. And although these two terms can certainly be described as buzzwords, they have found their way into our way of thinking and into all kinds of publications, so that they will probably continue to exist in the future.
Thought leaders, analysts, software and service providers and finally practically everyone in between have been proclaiming the "cognitive enterprise" for several months now. This concept - and the mindset associated with it - promises to use the information of the already digital company to achieve productivity, profitability and high innovation for the company. And they aim at creating and evolving next-generation business models between converging technologies and data.
So what is special about this “cognitive enterprise“? Defining it usually starts with the idea of applying cognitive concepts and technologies to data in practically all relevant areas of a corporation. Data includes: Open data, public data, subscribed data, enterprise-proprietary data, pre-processed data, structured and unstructured data or simply Big Data). And the technologies involved include the likes of Artificial Intelligence (AI), more specifically Machine Learning (ML), Blockchain, Virtual Reality (VR), Augmented Reality (AR), the Internet of Things (IoT), ubiquitous communication with 5G, and individualized 3D printing.
As of now, mainly concepts from AI and machine learning are grouped together as "cognitive", although a uniform understanding of the underlying concepts is often still lacking. They have already proven to do the “heavy lifting” either on behalf of humans, or autonomously. They increasingly understand, they reason, and they interact, e.g. by engaging in meaningful conversations and thus delivering genuine value without human intervention.
Automation, analytics and decision-making, customer support and communication are key target areas, because many tasks in today’s organizations are in fact repetitive, time-consuming, dull and inefficient. Focus (ideally) lies on relieving and empowering the workforce, when the task can be executed by e.g. bots or through Robotic Process Automation. Every organization is supposed to agree that their staff is better than bots and can perform tasks much more meaningful. So, these measures are intended to benefit both the employee and the company.
But this is only the starting point. A cognitive enterprise will be interactive in many ways, not only by interacting with its customers, but also with other systems, processes, devices, cloud services and peer organizations. As one result it will be adaptive, as it is designed to be learning from data, even in an unattended manner. The key goal is to foster agility and continuous innovation through cognitive technologies by embracing and institutionalizing a culture that perpetually changes the way an organization works and creates value.
Beyond the fact that journalists, marketing departments and even analysts tend to outdo each other in the creation and propagation of hype terms, where exactly is the difference between a cognitive and a digital enterprise? Do we need yet another term, notably for the use of machine learning as an apparently digital technology?
I don't think so. We are witnessing the evolution, advancement, and ultimately the application of exactly these very digital technologies that lay the foundation of a comprehensive digital transformation. However, the added value of the label "cognitive" is negligible.
But regardless of how you, me or the buzzword industry really decide to call it in the end, much more relevant are the implications and challenges of this consistent implementation of digital transformation. In my opinion two aspects must not be underestimated:
First, this transformation is either approached in its entirety, or it is better not to do it at all, there is nothing in between. If you start doing this, it's not enough to quickly look for a few candidates for a bit of Robot Process Automation. There will be no successful, "slightly cognitive” companies. This will be a waste of the actual potential of a comprehensive redesign of corporate processes and is worth little more than a placebo. Rather, it is necessary to model internal knowledge, to gain and to interconnect data. Jobs and tasks will change, become obsolete and will be replaced by new and more demanding ones (otherwise they could be executed by a bot again).
Second: The importance of managing constant organizational change and restructuring is often overlooked. After all, the transformation to a Digital/Cognitive Enterprise is by far not entirely about AI, Robotic Process Automation or technology. Rather, focus has to be put on the individual as well, i.e. each member of the entire workforce (both internal and external). Established processes have to be managed, adjusted or even reengineered and this also applies to processes affecting partners, suppliers and thus any kind of cooperation or interaction.
One of the most important departments in this future will be the human resources department and specifically talent management. Getting people on board and retaining them sustainably will be a key challenge. In particular, this means providing them with ongoing training and enabling them to perform qualitatively demanding tasks in a highly volatile environment. And it is precisely such an extremely responsible task that will certainly not be automated even in the long term...
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AI for the Future of your Business: Effective, Safe, Secure & Ethical Everything we admire, love, need to survive, and that brings us further in creating a better future with a human face is and will be a result of intelligence. Synthesizing and amplifying our human intelligence have therefore the potential of leading us into a new era of prosperity like we have not seen before, if we succeed keeping AI Safe, Secure and Ethical. Since the very beginning of industrialization, and even before, we have been striving at structuring our work in a way that it becomes accessible for [...]