Blog | Aug 10, 2020

Intelligent Automation 2025 – The Cyborg Enterprise

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Welcome to 2025, where the most successful global enterprises have seamlessly augmented human workers with Digital Workers, who are even less distinguishable from their human counterparts in their capability to make judgement, learn from mistakes and create value. Welcome to the age of the cyborg enterprise.

As a generation X’er, the notion of computers embedded within the human body was purely in the domain of science fiction for me, how little did I know that within a few years my own daughter would be a real-life cyborg. Born profoundly deaf, she now wears computing processors that process sound into electric signals that connect via real wires directly to her auditory nerve. Her X-ray looks like science fiction, part human, part machine with circuitry directly attached to her brain. And so Elon Musk’s effort of Neuralink, developing ultra-high bandwidth brain-machine interfaces to connect humans and computers, feels closer to me than ever.

So here we are 2025 and what does the cyborg enterprise look like?

Auto discovery of processes are finally useful and robust enough to be in all successful enterprises, for smaller businesses process intelligence as a service runs on the cloud with tiny software agents running on laptops, servers and mobile devices all at the same time. Driven primarily through the desire to have real-time people analytics – whereas the enterprise IT used to have a dashboard showing the real-time utilization of servers and Digital Workers, the cyborg enterprise workforce now has a dashboard showing the real-time utilization of humans combined with their digital counterparts tracking cases, processes and tasks and measuring the outcomes. This total enterprise dashboard effectively quantifies the output of the organization in real-time. The impact of every business intervention, change to business processes, and newly implemented procedure can now be tracked and measured immediately. The heartbeat of the business is live, and it’s used as the spear productivity and competitiveness.

Attended automation and human-in-the-loop are just a part of daily life. The enterprise versions of Alexa and Google Assist have taken the concept of voice activated home assistance to the workplace. Human workers converse with digital workers through voice to instruct and handle exceptions because it’s more convenient and faster. Webcams watch the users’ eyes, track their hand and combine these with the views of screens and audio, constructing models of intent and operation. With neuromorphic hardware acceleration handling most of the recognition on device, the conversation and interaction flow as naturally as between people. These are not chatbots these are chat pals. At the same time AutoML, the automated machine learning that accelerates the time consuming, iterative tasks of training machine learning is baked right into core of how digital workers operate. This means unusual exception, no matter how infrequent, are either handled automatically using self-healing algorithms through computer vision and program synthesis, or if the human touch is required, these are dealt with as easily and as a quickly as a chat with a friend and will require no further intervention.

Process automation development, which used to follow a waterfall process of stages of discovery, design and delivery has transitioned through agile to become fully self-managed. The most advanced digital workers not only discover processes but through minimal interactions construct and run processes themselves, managing changes, self-organizing to scale and through predictive monitoring, prescriptive analysis and simulation verified control mechanisms operate without the need to call on developers. Digital supervisors leverage multilevel observation of human and system activities and relate these back to key enterprise metrics through process intelligence, orchestrating and marshaling individual cases, processes and tasks for digital workers and human workers to complete.

Sophisticated judgment, once considered as the critical component of human abilities particularly when faced with complex, dynamic domains turned out to be not much more complex than discovery of patterns of interactions through measure of relevant features and relationships between entities and information. Cognitive computing techniques now enable some Digital Workers to handle missing information, resolve conflicting inputs, make compromising decisions and adapt more quickly than their human counterparts.

The flow charts used for programming processes have evolved to a series of high level outcome instructions, where as once developers had to explicitly call out every action, the self-training models now use observation to derive the underlying set of actions required. Instead of relying on one or two subject matter experts to tell the developer how the Digital Worker should do what it needs to, the cyborg enterprise uses its’ wide-ranging sensors that spans, IoTs, screens, webcams, microphones, databases and network traffic to derive what to do more efficiently and to auto design its’ processes.

Five years earlier Nvidia had shown you can derive the entire software from simply watching the screen, now cases are derived and completed without needing to interact with much of the enterprise’s own human user interfaces. Today the routes and decisions across thousands of cases are analyzed automatically to derive the resolution, pushing only the unseen exceptions back to the human worker to make judgments on.

In the background the Digital Workers read and respond to requests from the vast majority of customers and partners and their own systems’ sensors, all the while dynamically balancing their work queues, self diagnosing blockages and orchestrating their activity to ensure the highest response times are achieved through elastic use of computing resources and prescriptive recommendations made through data driven ROI calculations for more resources.

The cyborg enterprise is a hybrid operating system interpreting the content of enterprise models according to the command from the business outcomes, orchestrating the enterprise operations through dynamically allocating and monitoring the enterprise resources be they humans, computers or external systems. In 2025 Intelligent Automation is no longer an add on, it is the beating heart of the enterprise, the cyborg workforce that delivers the enterprise.