Automation has been at the forefront of nearly every country, enterprise, individual, educational curriculum and society. There can hardly be any intellectual discussion, business forum or program in today’s world where automation does not take center stage. We work, live, breathe, follow and preach automation in today’s application programming interface (API) economy and generative artificial intelligence (Gen AI)-obsessed world, which is leading us to the Fourth Industrial Revolution (Industry 4.0).

Like Industry 4.0, automation also has a very wide spectrum and canvas to operate upon. Automation in a manufacturing enterprise consists in broadly three areas:

1. Corporate systems and business processes. This includes various aspects such as supply chain management, customer relationship management (CRM), enterprise resource planning (ERP), human resources, legal and finance. Large ERP and workflow vendors have played a significant role in this domain. However, in recent years, the emergence of robotic process automation (RPA), integrated/intelligent process automation (IPA) and now Gen AI has further driven automation in these areas (Figure 1).

2. IT processes. Automation has revolutionized information technology (IT) processes starting from the software development lifecycle (SDLC) and extending to continuous integration and continuous delivery (CI/CD). IT operations have also transformed from siloed applications, infrastructure, data and security operations into an integrated cloud operations model, which incorporates the principles of the DevSecOps value chain which is further fueled by Gen AI.

3. Operational technologies (OT) processes. The automation of operational technologies focuses on the entire lifecycle of manufacturing systems—from concept and design to distribution and delivery. This involves leveraging technologies such as computer-aided design (CAD), computer-aided manufacturing (CAM), distributed control systems (DCS), programmable logic controllers (PLC) and ultimately, product lifecycle management (PLM). Through automation and Gen AI, the entire journey from ideation to disposal is streamlined and optimized.

Emergence of automation skills

Automation skills are emerging from the three core areas: corporate systems and business processes, IT processes and OT processes. It is evident that numerous streams of specialist automation skills are emerging within each category from those specialized in large ERP, supply chain management (SCM) and customer relationship management CRM systems to standalone workflow experts focused on business processes.

For example, there is a growing demand for specialists in IT service management (ITSM), tooling, SDLC process automation as well as advanced Agile and DevSecOps experts for IT processes. Other specialized roles include CAD automation experts and facilities process automation professionals who work on shop floor environments and systems such as PLCs, DCS and PLM.

Industry 4.0 encompasses more than just the evolution of new technologies like machine-to-machine (M2M) communication, Internet of Things (IoT), machine learning (ML), augmented reality (AR) or blockchain. It represents the convergence of multiple technologies aimed at making enterprise manufacturing more efficient, effective and predictive. This leads to the development of “smart factories.” A classic example of this convergence is the concept of “digital twins.”

Digital twins enable the creation of world-class design and enable quick and defect-free prototyping, which reduces time, cost and improves the quality of products from concept to launch. These digital twins can then be used to generate multiple variants and scale production, which results in greater flexibility and responsiveness.

This convergence of multiple technological domains is referred to as “convergence of convergence.” It encompasses the integration of enterprise business processes that range from SCM to CRM; the convergence of IT systems that encompasses infrastructure, applications, data and security; as well as OT convergence spanning from warehouses to the last mile, which includes shop floors and facilities.

Ultimately, the convergence of business processes, IT and OT is what drives Industry 4.0—with data acting as the common denominator. Data derived from various business systems (both structured and unstructured), IT systems (including infrastructure and application logs) and operational systems (in different formats and protocols) allows for intelligent data correlations, which provide predictive insights that enable proactive actions. The integration and utilization of data fuel the development of next-generation smart manufacturing, thereby granting organizations a competitive edge in the industry.

Industry 4.0 demands a holistic understanding of technology integration, automation and data-driven decision making across business, IT and OT processes. These changes require individuals in these fields to adapt and acquire new knowledge, skills and responsibilities to remain relevant in the evolving landscape. Industry 4.0 impacts each of the following professions.

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Business process automation

Industry 4.0 impacts business process automation through knowledge, skills and responsibilities.

• Knowledge. Those in business process automation will need to gain a deep understanding of digital technologies such as IoT, cloud computing, edge computing and connectivity protocols. This knowledge will enable them to integrate these technologies into SCM, ERP and CRM systems.
• Skills. Those in business process automation will need to acquire programming and software development skills to develop and integrate applications for automation systems and IoT devices. Additionally, proficiency in data management and analytics will be crucial for deriving insights from the vast amounts of data generated in Industry 4.0 environments.
• Responsibilities. Business process automation professionals will have a more strategic role in shaping digital transformation initiatives. They will identify opportunities for automation, optimize processes and develop roadmaps for implementing Industry 4.0 technologies. They will also be responsible for data-driven decision making by leveraging insights to drive continuous improvement and innovation.

IT automation

Industry 4.0 impacts IT automation through knowledge, skills and responsibilities.

• Knowledge: Those in IT automation will need to stay updated with the latest advances in Agile methodologies, continuous integration/continuous delivery (CI/CD), orchestration tools like Kubernetes, service automation tools and observability and telemetry automation. Additionally, knowledge of digital technologies and cybersecurity will be crucial for securing connected systems.
• Skills. IT automation professionals will need to develop programming skills to automate processes and implement IT automation tools. They will also need expertise in data analytics and interpretation to analyze and visualize data for insights. Acquiring cybersecurity skills will be necessary to protect industrial networks and systems from cyber threats.
• Responsibilities. IT automation professionals will play a key role in implementing and managing automation tools, orchestrating CI/CD pipelines and automating ITIL processes like configuration, change and release management. They will also collaborate with other departments, such as data scientists and cybersecurity specialists, to integrate technologies and drive digital transformation.

OT process automation

Industry 4.0 impacts OT process automation through knowledge, skills and responsibilities.

• Knowledge. Those in OT process automation will require a deep understanding of warehouse management systems, shop floor manufacturing technologies, MES and PLM solutions. Additionally, they will need to grasp digital technologies; and advanced concepts like digital twin technology, artificial intelligence, machine learning, collaborative robotics and additive manufacturing.
• Skills. OT process automation professionals will need to acquire skills in environment automation, shop floor manufacturing technologies and MES implementation. Proficiency in controls and automation programming languages will be necessary, as well as expertise in data management and analytics for data-driven optimization.
• Responsibilities. OT process automation professionals will lead projects involving the integration of digital technologies, implementation of collaborative robotics and development of digital twins. They will be responsible for optimizing processes, reducing downtime and improving productivity through data-driven approaches. They will also play a crucial role in implementing cybersecurity measures to protect connected systems.

Looking ahead

Overall, Industry 4.0 will require professionals to upskill and adapt to the changing demands of automation and digital transformation. They will need to embrace new technologies, develop programming and data analytics skills and take on strategic roles in driving innovation, data-driven decision making and cybersecurity implementation. Collaboration with experts from other disciplines will be essential to successfully integrate technologies and achieve digital transformation across departments and functions within organizations.