Recently, I had the privilege of attending two prominent HR Tech conferences, Transform 2023 and IAMPHENOM, held in Las Vegas and Philadelphia, respectively. Despite market uncertainties, it was encouraging to see an increase in companies’ investments in HR software, except for tech companies.
Generative AI solutions were a hot topic, with chatGPT being mentioned in almost every conversation. While vendors are preparing to provide chatGPT-powered solutions, I listened carefully to the customers’ feedback, which overwhelmingly expressed hesitation and apprehension before jumping in.
Quick survey on using chatGPT at work
During the events, I surveyed 72 HR leaders with three questions, and the results are shown in the chart below:
Q1) Did you try chatGPT to create content?
Almost 100% of people tried chatGPT at least once, they used it to create some pieces of content. It really helped them get over the writers block, or got them a draft to start with. It’s awesome is the phrase I heard them say most often.
Q2) Are you going to use chatGPT for your work?
Only 40% said they would use chatGPT for work, but mainly for personal use when researching a topic to get quick content recommendations. However, many are still figuring out how they can use chatGPT directly for work.
Q3) Is your company thinking of using chatGPT at enterprise level?
90% said their company is not yet considering using chatGPT at an enterprise level. The overwhelming majority are treading cautiously and running early pilots before deploying a solution. The following are the four key concerns for enterprise-level adoption:
Concerns before chatGPT can be deployed at enterprise level
While everyone recognises the transformational power of having powerful generative AI models creating content, people also feel that it is as good as having a fantastic scribe in your team. But, there are four key concerns before companies start using the AI at the enterprise level:
1) Branded Awareness
Content recommendations need to be brand aware. This means, the tone, language used, compliance to standards need to be completely aligned with the brand. This means, additional level of supervision, configurations and learning about the brand is required.
2) Personalized content
Most of the content generated needs to be personalized for the context. Typically this is driven through data insights locked up in various HR Tools used in the company (ATS, CRM, HRIS, L&D, Surveys etc). Only when the AI learns from the events, triggers and insights from these platforms, the content recommendations become personal and truly unlock the power of AI at scale.
3) Bias
Every leader I spoke to was concerned about unconscious bias in content recommendations and how it can impact their brand value adversely. Companies are concerned about the additional layers of bias verification they need to put in place before they can start using the AI generated content at scale.
4) Data Privacy and Security
AI learns from user data and actions. However, enterprises are really concerned about their proprietary and sensitive information leaking to the generativeAI models and in-turn to the public.
About ishield.ai
Ishield.ai is the first generative AI platform built specifically for talent communications. We created proprietary AI models (patent filed) that make personalized content recommendations.
This means the content we create are:
1) Specific to the brand.
2) Personalized for the context by integrating into almost all HR software.
3) Verified to eliminate bias.
4) Works across text and images content.
Our retrained AI models works specifically for the customers, hence no data is sent back or retained with the large language models (such as chatGPT), thus addressing the data privacy and security issues.
HR leaders now have a platform that truly unlocks the power of generative AI and makes it work for you, thus helping you create content 10X faster.
If you would like to learn more about our platform, please schedule a demo using the following link.