Post by account_disabled on Dec 27, 2023 4:27:29 GMT -6
With other companies (such as telcos and ride-hailing companies), their customer base, institutions, social media, public domain and external data analytics providers. With data volumes doubling every few years , gaining privileged access to data is a non-stop work. What’s next? Is AI just one element of a company’s overall digital transformation – or does AI require new approaches? On the one hand, AI presents many of the same challenges as other digital The same issues and challenges of technology, there are many ways that companies can build their digital and analytics programs. However, AI also has its own distinct characteristics. Ensuring customer trust. AI capabilities are similar to many digital initiatives in that they rely on customer data as well as customers Trust that a company will respect and protect their personal data.
However ensuring the trustworthiness of AI differs from other data-reliant digital initiatives in several ways. First, managers may not be able to explain exactly how customers’ personal data will be used to AI products produce specific results. programs are opaque. Second, more and more Job Function Email List AI systems are able to imitate human agents, which puts the onus on managers to communicate clearly with customers, wherever they are. whether dealing with machine or human agents in a given environment. Third, some AI systems are capable of assessing emotions and discerning quite personal details at a distance.
This capability brings new information management issues, including which employees have access to such information and under what circumstances it is accessed. Perform AI health checks. There are some similarities to digital health checks, from applications across processes to supporting infrastructure, technical skills, agile processes and a fail-fast atmosphere. Like many digital initiatives, the success of AI depends on access to data sources, whether that’s existing internal or external data or investments in data infrastructure. Large companies may well have the data they need.
However ensuring the trustworthiness of AI differs from other data-reliant digital initiatives in several ways. First, managers may not be able to explain exactly how customers’ personal data will be used to AI products produce specific results. programs are opaque. Second, more and more Job Function Email List AI systems are able to imitate human agents, which puts the onus on managers to communicate clearly with customers, wherever they are. whether dealing with machine or human agents in a given environment. Third, some AI systems are capable of assessing emotions and discerning quite personal details at a distance.
This capability brings new information management issues, including which employees have access to such information and under what circumstances it is accessed. Perform AI health checks. There are some similarities to digital health checks, from applications across processes to supporting infrastructure, technical skills, agile processes and a fail-fast atmosphere. Like many digital initiatives, the success of AI depends on access to data sources, whether that’s existing internal or external data or investments in data infrastructure. Large companies may well have the data they need.