57% of CEOs and CFOs plan to increase use of AI and automation in their companies. This is a cause of concern for people working across various industries. The true strength of generative AI is to augment, rather than replace, the work of human experts, writes Ravin Jesuthasan, Senior Partner at consultancy, Mercer, in blog post for World Economic Forum
He says a recent Mercer survey shows that 57% of CEOs and CFOs plan to increase use of AI and automation; nearly one-third are redesigning work to reduce their organizations’ dependency on people”, he writes
“The percentage of employees who say automation will significantly change how their work is done has jumped from 44% to 71% in the past two years.”
Jesuthasan writes that as we enter this new age of automation, companies should consider the following as they integrate this promising technology into their workflow:
Work model: How will you create a work operating model with the tools and disciplines to analyze work and sustainably and responsibly apply emerging AI and automation?
Talent model: Can you develop a talent model that ensures a sufficient pipeline of skills even as you progressively apply more AI to your work?
Developing future skills: As AI proliferates, ensuring employees do meaningful and sustainable work is critical. How will you find opportunities to automate tasks and free up time for new, value-adding activities while ensuring the seamless upskilling and reskilling of your workforce for the next iteration of work?
Mindset and culture: As AI continues to lower the premium on creativity and democratizes access, how will you ensure the perpetual reinvention of your business model and workforce?
“Unlike previous iterations of automation that largely impacted repetitive, rules-based work, generative AI will also affect low-volume, highly variable work, leading to what some have termed the “democratisation of creativity.”
“Work in numerous professions, including that of authors, researchers, lawyers and many others, will be significantly disrupted.”
There are four distinct potential outcomes associated with any body of work:
- Error elimination — think of some of the work of an airline pilot — where the consequences of a mistake are high and there is significant potential for negative value to the organization from any deviation from an acceptable level of performance.
- Minimising variance — such as transaction-processing work — where there is no value in improving performance beyond a target level.
- Improving productivity — the work of a salesperson, for example — where an improvement in performance yields a commensurate improvement in value to the organization.
- Achieving breakthroughs — think of highly creative work, such as data science — where a small improvement in performance has an exponentially large impact on value.