What is the Difference Between AI & GenAI?

Traditional AI:

For businesses with strong technical savvy or support, Traditional AI involves leveraging your existing numerical data to build models that automate processes, optimize operations, and enhance decision-making. It includes predictive analytics, customer segmentation, and recommendation systems, all of which need sophisticated engineering and other AI capabilities.

Generative AI:

With Generative AI, businesses can move beyond traditional data analysis to create new content, ideas, and information learned from patterns from different types of data. It can learn from human language (text, voice), computer code, images, and music. It can therefore quickly produce similar or novel text, code, pictures and more.

In addition, whereas most AI can be a blank slate, requiring a company’s data to learn and improve the models to become effective for businesses, many generative AI models have already learned patterns from massive amounts of data and are ready to use once adopted.

Generative AI models quickly produce outputs when prompted with a few words or sentences, which is referred to as “prompt engineering”. Therefore, Generative AI can be used effectively by technical and non-technical professionals through certain platforms that allow prompt engineering.

 

The Value of Generative AI for Business

Generative AI and traditional AI differ significantly in how they provide revenue opportunities and cost reductions for businesses. While both maximize revenues and reduce costs, generative AI’s ability to create and innovate provides new opportunities that traditional AI typically does not.

1 – Revenue Opportunities

Product Innovation:

Given that generative AI can produce writing, art, music, images, or other materials, it means it can create entirely new products, product features, or services for businesses. This opens up new revenue streams by offering unique products/materials that wouldn’t be possible with Traditional AI.

 

Automated Creativity:

Businesses can use generative AI to automate creative tasks like marketing, design, and advertising, reducing the time to create new ideas and marketing content.

 

2 – Cost Reductions

Content & Process Automation:

By the same token of creativity, if it can create on its own, then Generative AI automates many outputs, whether it is for marketing, sales, and internal materials like reporting or meeting summaries. It is also well known to automate certain processes that previously required human inputs, from writing emails to customer support and experience chatbots.

R&D Efficiency:

By generating new ideas, designs, or prototypes simply through written prompts or other inputs, generative AI reduces the time and resources needed to bring new products to market or improve existing ones.

 

How to Use Generative AI: Implementation

Comparatively to AI, implementing generative AI in your business typically follows one of three approaches: buying a prepackaged solution, use/edit an existing model, or building from scratch. Each path has its own set of benefits and challenges, and understanding these can help you choose which type of generative AI could best fit your organization’s needs.

1 – Buy a Prepackaged Solution

As aforementioned, these are the Generative AI models that are ready to use and widely known to the public, such as ChatGPT, CLaude, and Gemini. Purchasing these prepackaged models is an attractive option for businesses seeking a quick and cost-effective AI solution. They offer less customization but can be easily accessed by non-technical individuals through prompt engineering.

They are powerful models, yet your competitors can just as easily access the same models, leveling the playing field. To gain a competitive edge, the following two implementation types offer appealing solutions.

2 – Use and Edit an Existing Model

Large providers of ready-to-use models like OpenAI’s ChatGPT, provide the models that can be accessed or implemented in your systems and software. Your business can use the model as is, or modify it with your data and intellectual property. Both options allow firms to tailor Generative AI to their specific needs, leverage their competitive edge (data & IP) and gain greater control over what the models will create.

3 – Build from Scratch

Creating a Generative AI from scratch offers the highest level of customization but is a complex and costly endeavor. This route is generally reserved for large organizations with substantial resources who can develop and maintain these systems. While the control and personalization are unparalleled, the investment in time, expertise, and financial resources make it impractical for most companies.

 

Risks & Challenges of Generative AI

Privacy/Security Risk

AI and Generative AI share similar privacy and security challenges, particularly when handling personal or proprietary information. From data collection to model deployment, organizations must ensure robust privacy protections are in place. The key difference with Generative AI is that prepackaged solutions, like ChatGPT, can store and utilize the data you input. This can potentially compromise data security as this information may be absorbed into ChatGPT, making it accessible to others.

Major Risk: Hallucinations

Generative AI introduces a novel risk: hallucinations. Unlike Traditional AI, Generative AI can produce content that appears accurate but is factually incorrect or logically flawed. Since it doesn’t reason like humans, it may generate convincingly false information. Therefore, it poses significant risks to companies relying on AI for decision-making, content creation, or customer interactions. Ensuring the accuracy and reliability of outputs is critical to avoid potential misinformation and its consequences.

 

Conclusion

Generative AI is a powerful evolution of Traditional AI, allowing businesses to create new content, innovate products, and automate creative tasks. This can lead to significant revenue growth and cost savings. However, understanding the best implementation strategy is crucial—whether buying a prepackaged solution, modifying an existing model, or building from scratch.

Each approach has unique advantages and risks—many not discussed in this article. To explore how Generative AI can transform your business and navigate the complexities of implementation, contact PlanAxion today. Our experts can guide you through the process, ensuring your AI strategy aligns with your goals.