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Leveraging ChatGPT for Business Success: Understanding the Potential and Limitations

Chief of AI

Artificial Intelligence is transforming the way businesses operate, and one of the most promising technologies is ChatGPT, powered by GPT-4. ChatGPT has the potential to revolutionize customer support, content generation, and many other tasks. However, it’s essential to bypass the overwhelming hype of the past months and understand the limitations of this advanced technology before adopting and relying on it for critical business functions. In this blog, we’ll discuss the potential use cases of ChatGPT in the business world and address the main limitations that enterprises should be aware of.

Beyond the hype, towards real applications

The immense hype around ChatGPT and Language Models can be overwhelming for most businesses because it makes it hard to separate the “wheat from the chaff”. Identifying practical business applications can be difficult given the constant releases of new ideas, experiments and products that look impressive on Twitter but fail to cover business needs.

You can think of ChatGPT as a high-performing engine in a race car. Just like a race car needs a well-designed body and a high-quality suspension to make it top=performing, a business needs a whole system of supporting technologies and processes on top of ChatGPT to make it useful in real-world applications. Without these supporting components, the power and potential of ChatGPT cannot be fully realized, and it may not be practical or useful for real-world applications.

ChatGPT, when used out-of-the-box for business applications, suffers from lack of Explainability, Controllability, Improvement and Safety as analyzed below.

The solution to these challenges lies in incorporating ChatGPT to a broader AI platform that provides safeguards and enterprise-grade guarantees necessary for practical business use cases.

Môveo’s 1-click AI uses the power of GPT-like alongside proprietary AI technologies to revolutionize customer experience and provide businesses with the opportunity to incorporate the latest technologies. Môveo was built around solving core business problems and tackling the challenges described above is the reason many companies use the platform for their essential business operations.

1-click AI: The perfect blend between conversational AI agents and ChatGPT

Unlocking the Potential of ChatGPT

ChatGPT can be a game-changer for businesses that implement it strategically. From customer support and virtual agents to content generation and data analysis, this AI-driven technology can automate mundane tasks and help organizations scale efficiently. However, to make the most of ChatGPT, businesses must be aware of its limitations and plan accordingly.

ChatGPT for content generation: The Ubiquitous Writing Assistant and the Need for More

One of the most straightforward and widely adopted applications of “ChatGPT for work” is the writing assistant, which generates content for emails, blogs, or social media posts. In this setting, a human user receives the AI-generated response that is typically 70-80% accurate, and they can then edit the remaining portion to fit their needs. This powerful application can significantly boost employee efficiency and productivity. However, there is a noticeable gap in the availability of other practical business applications beyond writing assistants. Enterprises must explore and develop innovative use cases for ChatGPT that can help them unlock its full potential and address a wider range of business challenges, thereby maximizing the return on investment in this cutting-edge technology.

The Hype and Reality of ChatGPT in Business Applications

The growing hype surrounding ChatGPT has led to the development of numerous toy applications, which may appear impressive when showcased using cherry-picked examples, but fail miserably in actual applications.

Consider the trending AutoGPT application, which is a tool that relies on AI agents to make decisions and take actions based on predefined goals and rules. For example, you can define a goal like “order 2 large pepperoni pizzas from Dominos”. AutoGPT will use a browser to click on the necessary buttons to login, pick the pizza, fill the address and payment details and then complete the order! Sounds impressive, but would you really trust ChatGPT with this task? The obvious answer is no! What if ChatGPT mistakenly orders 20 pizzas instead of 2? What if it enters an incorrect address? The current technology is very far from performing tasks like these and businesses need to bypass the hype surrounding ChatGPT and focus on practical applications.

These toy applications often fail to scale in real-world business settings due to the lack of thorough consideration of ChatGPT’s limitations. It’s vital for businesses to look beyond the hype and carefully evaluate the technology’s capabilities and limitations before integrating it into their operations. By doing so, they can avoid investing resources in applications that may not deliver the expected results or create additional challenges in the long run.

The Challenge of Explainability

One of the main limitations of ChatGPT is its lack of explainability. It can be challenging to understand why the model generates specific responses, which can make it difficult for businesses to fully trust the AI’s output. This limitation should be considered when deploying ChatGPT for high-stakes tasks, where complete transparency is necessary. As an example shown below, for the same question, ChatGPT will output a different response. Hence, it is hard to anticipate which response ChatGPT (or any other Language Model) will generate.

In many business settings the question “Why did the system generate a specific response?” is crucial and important. For industries like Fintech or Banking, it’s important to have the ability to interpret and understand why the AI system approved or declined a loan application, such that possible biases or shortcomings can be understood and eliminated by the human employee who ultimately takes the final decision.

The Challenge of Controllability

Controllability is another concern when using ChatGPT for business applications. Constraining the AI to not hallucinate is a challenge that prevents many customer facing use cases. Additionally, it can be difficult to ensure that the AI follows specific instructions and processes without deviation, particularly in high-stakes environments such as finance or sensitive customer support situations.

For instance, consider a scenario where a customer requests assistance in rescheduling a delivery. The company might have a well-defined procedure for managing such requests, involving verification of customer details, coordinating with the logistics team, and updating the delivery date in the back-end system.

In this case, ChatGPT might provide helpful responses initially but could struggle to follow the exact steps outlined by the company. It may skip some critical steps, like verifying the customer’s information or confirming the availability of the new delivery date with the logistics team, leading to an incorrect rescheduling and potential customer dissatisfaction.

This example highlights the need for businesses to be cautious when implementing ChatGPT for tasks that require strict adherence to specific processes. Ensuring that the AI can effectively follow these processes is crucial for maintaining a high level of customer satisfaction and preserving the company’s reputation.

The Challenge of Continuous Improvement and Adaptability

One of the key difficulties in using “ChatGPT for work” is its limited ability to learn and improve based on prior conversations or new business-specific data, such as updated processes, questions, scenarios, and use cases. Businesses often need their AI systems to adapt and evolve over time to ensure that mistakes are not repeated and that the system remains up-to-date with the latest information. However, due to the inherent complexities of the ChatGPT model, incorporating feedback from prior interactions or integrating new data can be challenging. This limitation can hinder the AI’s effectiveness and growth, making it less suited for dynamic business environments that require ongoing improvement and adaptation. It is crucial for businesses to consider this challenge when implementing ChatGPT and develop strategies to address it effectively, ensuring that their AI-powered solutions continue to deliver consistent and reliable results.

In the financial sector, improving ChatGPT is crucial for applications like fraud detection, where companies need to identify and prevent fraudulent activities quickly and accurately. Financial fraud is constantly evolving, with criminals developing new tactics and techniques to deceive businesses and exploit vulnerabilities in their systems.

For instance, a bank might use ChatGPT to analyze transaction patterns and identify suspicious activities that could indicate fraud. If the AI model fails to adapt and learn from new data or recent fraud cases, its ability to detect and prevent emerging threats becomes limited. In this scenario, the bank might experience increased financial losses and damage to its reputation due to undetected fraudulent activities.

The Challenge of AI Safety and Responsibility

As enterprises grant more freedom and responsibility to ChatGPT, AI safety becomes a critical concern. Applications that allow the AI to interface with back-end systems via APIs or have complete control over specific tasks increase the risk of severe mistakes and other vulnerabilities, such as unauthorized data access or unintended actions.

For example, consider a ChatGPT implementation that has access to sensitive customer information and the ability to process transactions. If the AI encounters a carefully crafted malicious input or prompt injection, it could potentially expose confidential data, execute unauthorized transactions, or cause other adverse effects on business operations.


ChatGPT offers immense potential for businesses that can harness its power effectively. Understanding the limitations of this AI technology is crucial for success in implementing it across various functions. By being aware of the challenges surrounding explainability, controllability, continuous improvement, and AI safety, businesses can make informed decisions, mitigate risks, and successfully adopt ChatGPT to drive growth, efficiency, and innovation.

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