
Build Trust & Enhance Quality in Business Proposals with XaitAI
22.08.2023
-3 min

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John Ingve Eielsen
22.08.2023
-3 min
In today's fast-paced business world, time is of the essence, and customers are always on the lookout for efficient solutions. When it comes to writing business proposals, the advent of Artificial Intelligence (AI) has revolutionized the way we approach content generation. Two prominent AI approaches for this purpose are Discriminatory AI and Generative AI. While both have their merits, understanding their differences and implications is essential for businesses seeking to build trust and increase proposal quality.
Discriminatory AI, also known as retrieval-based AI, is designed to identify specific information from a pre-existing corpus (i.e. a large selection of text on which the AI is trained) and deliver it with precision. For business proposal writers, this means the ability to access relevant content quickly, saving valuable time and effort. By employing powerful algorithms, discriminatory AI can swiftly sift through vast amounts of data to extract the most suitable sections or sentences for a particular proposal. This efficiency is particularly advantageous for customers who spend hours searching for the right content to include in their proposals.
On the other hand, Generative AI, operates by creating new content based on patterns and data from its training set. While this can be incredibly innovative and creative, it brings challenges related to trust and reliability. Generative AI tends to hallucinate, producing information that may not be factual or contextually appropriate. Additionally, the risk of generating irrelevant or incorrect content can raise concerns about the credibility of the business proposal.
Furthermore, security challenges play a significant role in the adoption of generative AI. With the potential for data leaks and malicious content generation, businesses need to be cautious about how they implement and control generative AI systems. This is especially crucial when dealing with sensitive information or confidential business data.
In light of the trust and security concerns associated with generative AI, businesses have found themselves relying more on discriminatory AI for content generation in their proposals. Discriminatory AI's ability to retrieve precise and relevant information from a trusted corpus ensures a higher level of accuracy and reliability in the content produced.
Building trust in AI-generated content is a gradual process, and discriminatory AI plays a pivotal role in this journey. By focusing on discriminatory AI to build a reliable corpus of approved content, businesses can instill confidence in both their AI systems and proposal writers. As the trust in AI grows, proposal writers can shift from content creation to reviewing and approving the suggestions provided by the AI.
Additionally, businesses can leverage a combination of both discriminatory and generative AI approaches to strike a balance between efficiency and creativity. Discriminatory AI can be used to propose content, which can then be reviewed and modified by human writers, harnessing the strengths of both AI and human expertise.
The evolution of AI has introduced significant advancements in content generation for business proposals. Discriminatory AI, with its ability to swiftly retrieve precise information, caters to the growing demand for time-efficient solutions. Furthermore, trust and security challenges related to generative AI have highlighted the importance of building a trustworthy corpus through discriminatory AI.
As businesses continue to explore the potential of AI in proposal writing, a cautious approach that emphasizes discriminatory AI and balances it with generative AI can pave the way for increased quality, efficiency, and trust. By empowering AI to support proposal writers rather than replace them, businesses can create a harmonious synergy between human creativity and AI's data-driven capabilities, ultimately leading to more successful and persuasive business proposals.
Related article: Beyond the Hype: Secure AI for Business
John Ingve Eielsen
John Ingve comes with 15 years of experience in developing software for the Oil & Gas and energy industry, where he has held roles from software developer to architect and manager. John Ingve is technology enthusiast, and is a believer in continuously improving to meet the demands of the future. He enjoys spending time with his family (including his two dogs), reading history books and hiking in the great outdoors.