AI solutions are also increasingly being used in the world of finance. Many banks and other financial institutions are already integrating the technology into their business processes and are expecting a number of benefits from it - from image creation and innovative communication options for their customers to automatic anomaly analysis and prevention. The hope of cost savings is also often associated with the use of AI. Our experts experience in their day-to-day work that this is not necessarily the case.
Common assumptions about AI that are not necessarily true
In order to highlight potential cost traps and correct misjudgements, they examined five common assumptions about the cost situation when using AI in the white paper "Understanding the costs of AI". The result: many of these assumptions have turned out to be myths - but that doesn't mean that artificial intelligence can't lead to cost savings. Our experts identify common misconceptions when planning the use of AI and provide recommendations on which aspects should be taken into account when selecting, implementing and training AI to ensure that the use of technology has a cost-effective impact in the medium and long term.
Daniel Wagenknecht
Partner, Financial Services
KPMG AG Wirtschaftsprüfungsgesellschaft
We have examined these assumptions about AI in relation to costs:
- The cost-benefit analysis on the use of AI is always positive.
- The technical possibilities of the various AI applications are the decisive selection criterion for the associated costs.
- AI training runs "as if by itself" - without additional costs.
- After the technical introduction, nothing stands in the way of the successful use of AI.
With the cloud as a basis, introducing AI is child's play. Take the self-test before you download our white paper here: Which of the above assumptions do you think are true and which are myths?
