Is GenAI Struggling with Hallucination Issues?

GenAI and Hallucination

First of all, I want to mention that AI has opened a brand-new world, addressing key challenges faced by sales teams, such as reducing time spent on research, communication, administration, and documentation of their daily work. Tools like call note takers, email content creation and correction using ChatGPT, and meeting administration solutions are transforming how salespeople operate, and the list could go on.

On my endeavor to transform iSEEit into a trusted AI companion, I have come across some interesting facts that we all need to be aware of.

One key observation is something that all generative AI (GenAI) solutions have in common: 

The hallucination factor

AI hallucination, a phenomenon where AI models generate information that sounds accurate but is fundamentally incorrect, poses significant challenges. A prime example of this occurred during a video call with a CRO. The AI note-taker, designed to capture key points, misinterpreted a 20 million growth target as a 15% increase.

The root of this misinterpretation lies in the AI’s misunderstanding of context. The CRO mentioned the current Annual Recurring Revenue (ARR) as 20 million and the need to double it. However, the AI, lacking the nuanced understanding of business terminology, misconstrued “doubling the ARR” as a 15% increase. This oversight could have led to significant miscalculations in business impact and ROI assessments.

Such instances highlight the importance of human oversight and critical thinking when working with AI. While AI can significantly augment human capabilities, it’s crucial to recognize its limitations and avoid relying solely on its output.

Another important factor is 

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Confidentiality and Data Sensitivity:

As we increasingly rely on Generative AI (GenAI) tools, it’s crucial to be aware of the potential risks to data privacy and security. A significant concern is the widespread practice of AI vendors, including operating system providers and social media giants like Meta and LinkedIn, utilizing user data to train their AI models.

This means that any information shared with these AI tools, including personally identifiable information, trade secrets, and proprietary data, could potentially be used to train the AI models. This raises serious concerns about data security and privacy.

Consider the following scenarios:

Accidental Data Exposure: Imagine a team of brilliant engineers at Samsung, diligently working on the next groundbreaking innovation. In a moment of haste, while using an AI debugging tool, a critical error occurred. Unknowingly, confidential source code was exposed to the tool’s servers. This incident serves as a stark reminder of the importance of data security, even when leveraging advanced AI technologies.

Unintentional Information Sharing: Imagine you’re having a secret meeting about a new product. You use an AI tool to help you create a presentation. But what if that AI tool accidentally shares your secret ideas with someone else? That’s why it’s important to be careful when using AI tools, especially when discussing sensitive information.

Data Privacy Risks in Translation: A multinational corporation, eager to expand its operations into new markets, decided to leverage AI translation tools to expedite the process of translating confidential contracts. While this seemed like a time-saving solution, it inadvertently put the company’s sensitive information at risk. The AI tool, designed to translate text accurately, lacked the ability to discern confidential information. As a result, it processed and translated the contracts, potentially exposing sensitive clauses, proprietary information, and financial details. This incident serves as a stark reminder of the importance of carefully considering data security when using AI tools, especially when handling confidential documents.

To mitigate these risks, it’s essential to educate sales and marketing teams about the importance of data privacy and security when using AI tools. They should be advised to:

Avoid Sharing Sensitive Information: Refrain from sharing confidential information about the company, partners, clients, or products with AI tools.

Use Anonymized Data: If necessary to use AI for specific tasks, anonymize sensitive data before inputting it into the AI tool.

Stay Informed: Keep up to date on the latest AI developments and best practices for data privacy and security.

Choose Reputable AI Providers: Select AI vendors with strong data privacy and security policies.

By understanding the potential risks and taking proactive measures, businesses can harness the power of AI while safeguarding their valuable data.

To maintain the anonymity of data you can use following tools –

OpenRefine: A powerful data cleaning and transformation tool that can be used to anonymize sensitive data. https://openrefine.org/

PrivacyBee: A user-friendly tool that can anonymize personal data and other sensitive information. https://privacybee.com/

Google Docs: Find & Replace feature of Google Docs help maintain the sensitive information by replacing them into generic terms. https://workspace.google.com/intl/en_in/products/docs/

Remain the Human Touch

In my test with automated communication with clients we came across a few factors, which showed some weaknesses like the 

Inability to really understand the conversion in depth: AI can help generate personalized messaging, but it doesn’t fully know your clients. The lack of deep personal understanding can lead to generic or even inaccurate personalization attempts.

Adapting to Client Feedback in Real-Time

While GenAI tools are excellent at providing template responses, they often struggle to adapt to real-time feedback or unexpected shifts in client conversations. Overreliance on AI-generated responses can lead to impersonal and robotic interactions, potentially missing crucial cues and damaging long-term relationships.

A funny note story from our sales team when our GenAI generated email met an automated responder it really showed how the “engines” talked passed each other.

Salespeople should remain actively engaged in conversations, leveraging AI as a tool for initial preparation and data analysis. By combining the efficiency of AI with their own interpersonal skills, salespeople can effectively navigate the dynamic nature of client interactions. Human intuition, empathy, and the ability to read between the lines are essential for building strong, lasting relationships.

Conclusion: Humans and AI – A Powerful Partnership

While GenAI is a game-changer for sales teams, making many tasks more efficient, it’s essential to remember that AI is a tool to support human expertise, not replace it. The human being touch—the ability to listen, empathize, and adapt in real-time—is irreplaceable in building strong client relationships.

AI has come to stay, but so have human salespeople. By combining the efficiency of AI with the creativity, intuition, and empathy that only humans bring, sales teams will thrive in this new AI-driven world. Together, humans and AI can create a future where sales are not only faster but smarter and more personalized. Let’s embrace both innovation and the value of human connections.