Introduction
Automation helps people focus on work that needs human skill—listening, problem solving, and empathy. In daily life we already use automation: email filters, calendar assistants, and phone features that suggest replies. In organisations, automation handles repetitive tasks like data entry, approvals, and scheduling. The result is faster service and fewer errors when it is done with care (Brynjolfsson and McAfee, 2017; Davenport, 2018).
Types of automation
Three types are common. First, task automation: scripts or bots that copy routine clicks and keystrokes. Second, process automation: workflows that move a case from step to step with rules and approvals. Third, cognitive automation: tools that read documents, classify messages, and summarise text using AI. Many solutions mix all three. The best results come when processes are simplified before automation to remove waste (Aguirre and Rodriguez, 2017).
Finding the right candidates
Good candidates are high‑volume, rule‑based, and low‑risk. Examples include invoice data capture, appointment reminders, ID checks, and stock updates. Avoid automating unstable processes or steps that change every week. Aim for quick wins of four to eight weeks, then scale to harder areas with what you learn (Davenport, 2018).
Human oversight and quality
Keep people in charge. Design clear exceptions for cases the system cannot handle. Show confidence scores and explanations so staff know when to review. Track key quality metrics—turnaround time, error rate, and rework—and review them weekly. This creates a feedback loop that keeps quality high as volume grows (Brynjolfsson and McAfee, 2017).
Security and privacy
Automations often handle sensitive data. Protect it with role‑based access, encryption, and secure storage of secrets. Keep detailed logs so you can investigate issues. Train teams on phishing and safe handling of files. In healthcare and finance, align with sector rules and record a simple safety case that explains scope and limits (WHO, 2021).
Impact on people
Automation removes repetitive work but can also cause worry. Be open about goals and involve teams early. Offer training so staff learn to supervise and improve automations. Most teams find that job roles shift rather than disappear—people move to quality checks, customer contact, and continuous improvement (Autor, 2015).

Everyday examples

• Email triage suggests replies and flags urgent items.
• Calendar assistants propose meeting times automatically.
• Document AI reads forms and fills systems with the right fields.
• Voice bots schedule simple appointments after hours.
• In hospitals, e‑referral processing checks safety rules and books the right clinic slot.
  These examples show that small, clear automations deliver daily value without complex change (Davenport, 2018; WHO, 2021).

Conclusion
Automating everyday work is about respect for people’s time. Start with simple, visible tasks, keep humans in control, and measure quality. With this approach, organisations gain speed and staff get time back for meaningful work (Brynjolfsson and McAfee, 2017; Davenport, 2018).

References (Harvard style)
Brynjolfsson, E. and McAfee, A. (2017) Machine, Platform, Crowd: Harnessing Our Digital Future. New York: W. W. Norton & Company.
Davenport, T. (2018) The AI Advantage: How to Put the Artificial Intelligence Revolution to Work. Boston: MIT Press.
Aguirre, S. and Rodriguez, A. (2017) ‘Automation of Business Processes using Robotic Process Automation (RPA)’, in 2017 Workshop on Engineering Applications. IEEE.
World Health Organization (2021) Ethics and Governance of Artificial Intelligence for Health. Geneva: WHO.
Autor, D. (2015) ‘Why Are There Still So Many Jobs? The History and Future of Workplace Automation’, Journal of Economic Perspectives, 29(3), pp. 3–30.