Moving forward to AI-driven automation
The argument for AI in automation is clear . But what is not yet decided is the shape it will take .
With advances in large language models , Urmila anticipates that automation will move towards optimisation for “ higher-quality experience ”, which will provide users with more relevant , personalised interactions .
This evolution will allow AI not only to complete automated tasks but to suggest optimisations within workflows , further enhancing productivity . Small businesses , in particular , stand to benefit from these advances , as they gain access to sophisticated automation tools without requiring expert intervention .
In addition to quality , the concept of ‘ human-in-the-loop ’ will play a prominent role in the future of automation . Nick stresses the importance of involving human touchpoints in AI processes , noting that organisations need “ stepping stone ” workflows that empower humans to monitor and adjust autonomous systems .
This practice is already evident in emerging Agentic AI applications , which allow for real-time adaptations and adjustments in response to complex business challenges .
And in preparing for the future of AI in automation , Luiz advises that organisations “ develop a clear AI strategy ” and “ focus on proven technology ” to drive successful AI adoption .
This approach includes setting up pilot programs and training employees to work effectively with AI tools . By building a robust foundation for AI-driven automation , companies can mitigate the risks associated with rapid implementation while enhancing employee buy-in and user trust .
AI-driven automation is becoming integral to business operations , allowing them to improve operations and free up resources to focus on further value-added services .
Aligning how to implement it with a clear strategy will allow organisations to harness its full potential while fostering a culture of trust and adaptability .
108 January 2025