This post was originally published on this site.
Bayes Associate Dean for Research & Innovation warns of a long road ahead towards unlocking the full potential of artificial intelligence.
A new paper co-authored by Professor Feng Li, Associate Dean for Research & Innovation at Bayes Business School, has warned businesses that artificial intelligence (AI) is not yet advanced enough to transform organisational processes, despite widespread hype about its impact on the jobs of the future.
The article, āTransforming organisations through AI: emerging strategies for navigating the future of businessesā, argues that while organisations are beginning to use AI more widely to automate certain tasks and enhance services, it is not able to reach its full transformative potential without complex institutional changes ā which tend to occur at slower pace than technological advances.
Such a transition, the authors say, historically takes decades rather than years ā dismissing the idea that AI is ready to displace humans in the workplace. Errors that still exist in Generative AI (GenAI) mean that it is not yet advanced to the point of being able to fully automate entire operations. Without reinventing regulatory frameworks and educational systems, plus the creation of ethical standards, AI development will be limited to performing basic tasks rather than helping businesses map out strategic transformation of processes and business models.
The article also suggests that this process will take a lot longer than many are anticipating. Using the Industrial and Digital Revolutions as reference points, the authors predict the transition will likely take longer than anticipated as institutional changes are slow and iterative, taking time to fully align with faster-moving technological advancements.
Professor Li claimed businesses needed to have realistic expectations of AIās capabilities to avoid over-reliance and dispensing of human capital too soon.
āThe current hype around mass displacement of jobs due to AI development is misguided,ā he said.
āThere is a common fusion and misunderstanding between AI being āproductiveā and ātransformativeā. The two are not the same, and while AI does already perform a number of tasks at the level of ā or superior to ā humans, it is still some way off being truly transformational to the way businesses operate.
āAutomated AI is already in use for a number of rule-based individual assignments where data can inform its outcomes, but the potential of Generative AI ā on the more creative side ā can only be fully realised when it is used to transform organisations, their operational processes and business models. Fundamental issues with GenAI, which currently include hallucinations, lack of reliability and poor dependability will improve over time, but this will only happen alongside major technological breakthroughs which often take place over many years.
āThis significant barrier will continue to restrict large scale deployment of activities in business and government, and any such transition will be a long-term process that organisations must manage carefully.
āWe must balance excitement about what AI could achieve in future years in terms of business efficiency and innovation, with an awareness of business ethics and accessibility. Failure to do so could lead to business failure through lack of readiness, and also widen societal inequalities between those who are able to afford and adapt to new technologies and those who arenāt. These concerns have profound implications for policy and business strategy.ā
āTransforming organisations through AI: emerging strategies for navigating the future of businessesā, by Professor Feng Li and Harvey Lewis, Partner, Ernst & Young, is published in the Journal of Financial Transformation.