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A long-term process that needs to be managed

Simon Osuji by Simon Osuji
February 20, 2025
in Artificial Intelligence
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A long-term process that needs to be managed
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robot using computer
Credit: Pixabay/CC0 Public Domain

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 organizational processes, despite widespread hype about its impact on the jobs of the future.

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The article, “Transforming organisations through AI: Emerging strategies for navigating the future of businesses,” argues that while organizations 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—which tend to occur at a slower pace than technological advances.

Such a transition, the authors say, historically takes decades rather than years—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 AI’s capabilities to avoid over-reliance and dispensing of human capital too soon.

“The current hype around mass displacement of jobs due to AI development is misguided,” he said.

“There is a common fusion and misunderstanding between AI being ‘productive’ and ‘transformative.’ The two are not the same, and while AI does already perform a number of tasks at the level of—or superior to—humans, it is still some way off being truly transformational to the way businesses operate.

“Automated 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—on the more creative side—can only be fully realized when it is used to transform organizations, 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.

“This 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 organizations must manage carefully.

“We 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 aren’t. These concerns have profound implications for policy and business strategy.”

More information:
Paper: Transforming Organisations Through AI: Emerging Strategies for Navigating the Future of Business

Provided by
City University London

Citation:
Using AI to achieve business transformation: A long-term process that needs to be managed (2025, February 20)
retrieved 20 February 2025
from https://techxplore.com/news/2025-02-ai-business-term.html

This document is subject to copyright. Apart from any fair dealing for the purpose of private study or research, no
part may be reproduced without the written permission. The content is provided for information purposes only.





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