How is the approach to GenAI different from other technology investments you've made in the past?
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Director of Finance in Consumer Goodsa year ago
GEN AI is evolving very fast due to its capabilities of generating meaningful actionable insights in the form of text, image, audio etc. Its learns from any new developments due to complex use of algorithms. The earlier AI investments done on machine learning used to work on set parameters. Therefore, true potential of GEN AI will be unleased. India Head and Director of Global Finance Shared Services in Hardwarea year ago
The approach to technology investments so far has been covering research and due diligence, diversification, risk management and scalability. The unique aspect for GenAI is consideration of data security and network security. GenAI has potential to spread fake news, misinformation, manipulation of media, spam and phishing. So, regulatory guidelines will evolve in due course of time. The approach for GenAI will need to consider these aspects which are not so much prominent for normal technology investments. Director of Finance in Manufacturing8 months ago
We have yet to do any Gen AI in the finance space. As a company, we do not allow ChatGPT. We have banned many chat AI tools because realizing what's real or fake is difficult. From a corporate standpoint, we are selective on how we use GenAI tools. We have been looking at our technology in general and seeing what GenAI finance tools we already have. For example, we use other "Intelligence" tools for financial forecasting. We do use machine learning to help us process invoices and things like that. We've been in business for 157 years and have never been trailblazers in the technical space, but we're taking advantage of some AI tools. Truthfully, it's been hard adjusting to a different mindset. Even though we like being in the "safe space," it's been a leap of faith to acknowledge that machine learning is valuable, depending on how you use it. Our current model is progress, not perfection. We recognize that sometimes it is OK to fail and fix the issue versus wait until everything is perfect before you implement and try something new.SVP Corporate Audit in Energy and Utilities8 months ago
From an audit perspective, I think AI will be incredibly useful to organizations, however, I just don't know how at the moment. Within the audit, we are taking some very simple use cases, like putting the audit report's findings into AI and asking it to write the management summary. 90% of my audits are written in English by non-native English speakers and I now get AI to create the base-level report which is then refined by the auditor. It gives a great starting point for the auditor to use. We've already started using auto analysis on big data tools but we haven't fully developed it yet and there are other use cases in terms of training. Both we are trying to develop at the moment. Taking a pragmatic view, if you don't embrace it, you'll be left behind because other people will embrace it and they'll get to the finish line faster. I think you have to take a nontraditional view of the investment return in AI because people will come up with a return, but it will just be a made-up number in all honesty.
We think AI is a good thing and need to invest in the technology in the future and then see where it takes us. The size of change will depend on how big the investment is, which could be a difficult jump for some organizations where they can compare it to other traditional investment decisions with limited capital available.