The Age of Invisible Machines: A Practical Guide to Creating a Hyperautomated Ecosystem of Intelligent Digital Workers

The Age of Invisible Machines: A Practical Guide to Creating a Hyperautomated Ecosystem of Intelligent Digital Workers

Hyperautomating for a Better Tomorrow

Hyperautomation is the key to unlocking a future of efficient, personalized, and seamless experiences. New technologies like conversational AI, machine learning, and process mining are enabling organizations to automate tasks and processes in new ways. By strategically combining these disruptive technologies, companies can achieve “better-than-human” experiences that go beyond what humans or machines could accomplish on their own.

In his book The Age of Invisible Machines, Claude Aldridge provides a practical guide for companies looking to implement hyperautomation. He outlines a strategy for designing and building an “ecosystem of intelligent digital workers” (IDWs) — software programs that can handle increasingly complex tasks with a high degree of autonomy. According to Aldridge, hyperautomation will be crucial for businesses to remain competitive in an increasingly digital world. With the COVID-19 pandemic accelerating the trend of digital-first interactions, now is the time for companies to start building their hyperautomated ecosystems.

Aldridge believes conversational AI is the key technology for creating IDWs and orchestrating hyperautomation. Chatbots and voice assistants are just the beginning - advanced conversational AI will enable seamless and personalized interactions between humans and technology across any channel or device. When combined with other technologies like machine learning, process mining, and robotic process automation (RPA), conversational AI can be used to automate processes end-to-end.

However, successfully implementing hyperautomation is not as simple as just deploying a few chatbots. It requires an organizational shift towards “extreme agility” and cross-departmental collaboration. Hyperautomation needs to start small but internally, with a shared vision of how automation could transform the business. Companies should focus on automating specific pain points and inefficiencies, then building on those successes. Trying to overhaul too much at once often leads to “plan fluting” where nothing gets implemented.

Aldridge outlines four key steps to building a hyperautomated ecosystem:

  1. Develop a hyperautomation strategy. Identify key priorities and how automation could provide value. Get buy-in from stakeholders and determine key performance indicators.

  2. Build a “minimum viable ecosystem.” Start with a few core IDWs and interactions, then iterate and build on them. Use an open platform that allows you to easily create and deploy new skills.

3.Establish an analytics framework. Put tracking in place to measure how people are using the ecosystem. Use data to make continual improvements to the experiences.

4.Create human oversight and collaboration. Have people monitoring conversations and helping solve edge cases. Promote a culture of collaboration between people and IDWs.

A well-designed hyperautomated ecosystem should aim to produce “better-than-human experiences” that are efficient, personalized, and seamless. However, humans should still remain very much involved - they are needed to help handle exceptions, provide oversight, and make critical decisions. The key is finding the right balance of human and machine.

When it comes to tools and platforms, Aldridge argues companies should look for options specifically tailored to facilitating hyperautomation. The platform should make it easy for non-technical users to create, deploy and improve automated skills and conversations without needing to know how to code. It should also provide a shared library of skills and best practices that users can build upon. Analytics and reporting features are important for tracking the performance of the ecosystem and making data-driven improvements.

Hyperautomation raises some important ethical questions surrounding privacy, bias, job disruption and more. Companies need to consider these implications seriously and make AI safety and ethics a priority. If used responsibly, however, Aldridge believes hyperautomation can have an overwhelmingly positive impact - driving efficiency, customer satisfaction and new opportunities for human achievement.

The age of invisible machines is here, and hyperautomation is the process that will turn science fiction into reality. By crafting a thoughtful strategy and practical design approach, companies can harness the power of technologies like conversational AI to transform their business and build a better future. The Age of Invisible Machines provides a compelling vision and helpful guide for leaders looking to remain on the cutting edge of digital transformation. Overall, this book makes a persuasive argument that hyperautomation, when implemented strategically, could benefit both businesses and humanity.

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