When generative AI technology first emerged, there were instances where professionals used open-source tools for business purposes, neglecting their responsibility to exercise due diligence and relying solely on these powerful language engines. More recently, there have been plagiarism cases brought before the courts, further highlighting the potential drawbacks of this creative technology. This has led to scepticism in the business world about the implications of putting such tools in the hands of employees, despite the undeniable productivity gains. Concerns about brand reputation, credibility, consumer trust, and performance have understandably caused some hesitation in adopting this powerful technology. 

So, how can businesses responsibly harness the productivity and performance benefits of generative AI without facing these consequences? Here are some factors to consider when selecting a generative AI solution that is suitable for business:


Security is key

Ensure that the infrastructure security meets all your standard requirements, including necessary hosting, accreditations, and certifications.


Protect your content

Make sure that your intellectual property is not being used to feed open-source large language models (LLMs). It is common for software companies to enter into enterprise agreements with LLM owners to power their generative AI products. It is crucial to have a Zero Data Retention agreement in place to secure both the inputs and outputs of the system and prevent them from being used to feed the LLM. Additionally, it may be beneficial to know if multiple LLMs are used to ensure reliability and longevity.


Relevant inputs for relevant outputs

Verify that the text generation is relevant to your organisation. Look for a solution that allows access to your company’s knowledge base to generate customised content. This can be considered an additional feature that enhances the reliability of the generated content using the retrieval-augmented generation (RAG) method.


Generated text is backed by evidence

Ensure that the software generated text includes proper references and sources. The outputs should provide references and links to the source documents used for generating the content. This helps your team validate the accuracy and credibility of the generated text, that is a key principle of responsible use of generative AI.


Intuitive and set up for success

Choose a solution that is easy to use and does not require extensive training in prompt engineering. Prompting a language model to produce desired results can be challenging, so it is important to select an intuitive solution that offers user-friendly features and is intentionally designed to yield useful content without intensive effort. 

AutogenAI is revolutionising the way bids and proposal teams operate worldwide. Contact us to learn more about responsible generative AI for business, today.