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Generative AI Services – Do’s and Don’ts While Integrating GenAI

Generative AI services are offered by AI development companies to help organizations minimize risk and increase efficiency when implementing the latest technology. Here, we’ll discuss the do’s and don’ts to follow when integrating generative AI services with your business processes.

Generative AI has become the talk of the town in recent times. ChatGPT, Gemini, Bard, Microsoft Bing, etc., have become popular among individuals and businesses. It has also promoted the adoption of traditional artificial intelligence applications in many industries. According to a report, the global AI market is projected to reach $1,811.8 billion by 2030

Statistics show that the global generative AI market is $44.89 billion and is likely to cross $66.62 billion by the end of 2024. Another report indicates that the generative AI market could touch $1.3 trillion by 2032 at a CAGR (compound annual growth rate) of 42%. 

But what is generative AI? How can generative AI services boost your business? And most importantly, what are the do’s and don’ts to follow when adopting genAI into your processes? Let’s find out in this blog. 


How Generative AI Works

Generative AI is a type of artificial intelligence that can create content like text, images, videos, music, etc., based on the input prompt. It uses deep learning, NLP (natural language processing), and LLM (large language models) to process input provided in human text and deliver a relevant output in the desired format. 

Gen AI platforms are built on LLMs trained on large datasets to provide accurate or relevant results. Many organizations are investing in generative AI to streamline workflows and enrich products/ services. While the tech giants are building their models from scratch, other businesses are opting for cost-effective solutions like AI as a service (AIaaS) offered by third-party artificial intelligence development companies. This allows them to access the latest technology without affecting their budget. Moreover, AI service companies offer end-to-end solutions and take care of implementation, customization, and maintenance to save time and resources for the business. 

The working of generative AI is complex. However, the process can be broadly divided into three phases – training the foundation model, fine-tuning the model to suit the business needs, generating output, evaluating it, and re-tuning the model to increase accuracy. All this is done by the service provider so that the business can benefit from using the technology to achieve its goals. 


Generative AI Services – Do’s and Dont’s While Integrating Generative AI 

Integrating generative AI tools into your business requires proper planning and execution. That’s why many organizations partner with a reliable AI service company and let them take care of the process from start to finish. 

Consider the below-listed do’s and don’ts to effectively integrate genAI with your processes and overcome various challenges. 

What to do When Integrating Generative AI 

Define Clear Objectives and Goals 

Whether you want generative AI as a service or build the models from scratch, you should first clearly know what you want. Define your objectives – short-term and long-term. Determine what you want to achieve by investing in generative AI. Do you want to adopt the technology throughout the business at once, or do you want to proceed in stages by prioritizing individual departments? Clarity is vital when embarking on a new journey. 

Understand Capabilities and Limitations

This point applies at multiple levels. Firstly, you should be aware of the talent gap in your business. This will help in choosing the best method to adopt generative AI. Then, you should also understand what genAI can and cannot do. Though it is an advanced technology, it has its limitations. Generative AI is not a perfect solution for any problem. Hire AI consulting services to figure out if it can solve your issues and how. 

Partner with AI Development Company 

Many businesses don’t have the necessary expertise to work with generative AI tools. The most effective way to bridge this talent gap is to hire a service provider. AI development companies have experienced engineers, analysts, developers, etc., to build, test, deploy, integrate, upgrade, and maintain various artificial intelligence and machine learning models. They can customize the solutions to suit your specific requirements and provide long-term support services for cost-effective pricing. 

Maintain Clear Communication

Make sure your employees know what’s going on. Integrating generative AI into your business will change many operations and impact the work culture. Employees need to be aware of this. Address their concerns and offer educational resources. Provide training modules, take their feedback, and include them in the decision-making process. Talk to generative AI development companies about what you want and clearly explain your requirements. 

Start Small and Scale 

Start on a small scale and build prototypes before you integrate generative AI across the enterprise. This will reduce the risk of error, losses, and delays. You can monitor how the new systems are working and fine-tune the models before implementing them in all verticals. Additionally, the focus will remain on the specific project instead of being scattered everywhere. Even large organizations with huge budgets can benefit from taking baby steps with new technology. 

Create AI Adoption Policies 

Generative AI still has a lot of gray areas. Some businesses actively avoid using it to prevent legal complications. However, employees may still use genAI platforms for different reasons. It is crucial to have clearly defined policies for adopting artificial intelligence and generative AI in your business. State what employees can do with the tools. Highlight what they should avoid and mention the consequences of not adhering to the regulations. AI services companies can help in creating the guidelines. 

Data Preparation and Governance 

Generative AI will give better results when it is trained on high-quality proprietary data. For this, you should first prepare your business data and store it in a centralized repository. Luckily, AI service providers also offer data engineering and data management services. Eliminate bias and discrepancies from data. Make sure the data is inclusive and diverse. Then create data governance frameworks to establish standards throughout the organization. 

Be Innovative and Responsible 

Artificial intelligence promotes innovation. GenAI allows employees to get more creative with their ideas. You can experiment with marketing strategies, product development, etc., to gain an edge over competitors. AI/ML development services help in identifying the various ways genAI can streamline your operations. However, be responsible and consider the ethical complications of adopting generative AI in your business. 

What Not to Do When Integrating Generative AI

Ignore the Ethical Aspects of AI

Don’t ignore the ethical aspects when integrating generative AI tools with your systems. Whether it is how you use customer data, complying with data privacy regulations, copyrights management, etc., ask the AI service provider to set specific guidelines and follow them. Educate and create awareness among employees and stakeholders to avoid lawsuits. 

Avoid Responsibility 

Don’t avoid responsibility by letting AI handle everything. The technology is not advanced enough to replace human decision-making skills at all levels. Additionally, you will have to take responsibility for the actions performed by your genAI tools. Involve humans and use their expertise wherever necessary. 

Overestimate GenAI Capabilities 

One important tip AI services company shares is to never overestimate what generative AI can do. The technology is not invincible. It cannot miraculously solve all your business problems. If you overestimate its abilities, there’s a greater risk of incurring inaccurate results or higher expenses. 

Ignore User Feedback 

Don’t ignore feedback shared by employees and end-users who actually use the generative AI tools and applications. They share the inputs based on practical experience. It will help in improving the models and increasing their efficiency over time. 

Delay Data Protection 

Don’t delay setting up data protection guidelines and strictly implement them across the organization. Partner with a reputed artificial intelligence services company to develop data governance documentation and share it with your employees. 

Disregard Cultural Changes 

Don’t disregard the cultural changes that occur in your workplace. Your employees have to change their working styles, which will impact how they handle their jobs. Make the transition as stress-free and seamless as possible. Keep the communication channels open. Address the concerns raised by employees. Work in tandem with the partner offering AI development services to address these issues and prevent them from repeating.


Conclusion 

Generative AI has diverse roles in today’s world and will continue to help businesses streamline and digitalize their processes. Organizations from several industries like IT, FinTech, EdTech, healthcare, eCommerce, retail, hospitality, travel, media, etc., can opt for AI as a service (AIaaS) solutions to implement generative AI platforms in their business. 

Generative artificial intelligence services are tailored to suit the varied requirements of each business. The foundation models are trained on different datasets (public and proprietary) to ensure accurate output and increase overall business efficiency. 

Send us a message to schedule a meeting with our experts. 


FAQs

1. What are generative AI services?

Generative AI service is where a business uses Gen AI platforms belonging to third-party vendors for various business activities. AI development companies offer tailored AIaaS packages for businesses to choose what services they require and which technologies they want to access through cloud servers. 

2. Is ChatGPT generative AI?

Yes, ChatGPT is a generative AI chatbot developed by OpenAI to converse with humans and respond the way humans do. It is a user-friendly platform and an advanced version of AI chatbots. ChatGPT can provide more detailed and structured answers as well as handle follow-up questions. 

3. What is the most used generative AI?

Different generative AI solutions are available in the market for varied purposes. The most used platforms are DALL-E 2 for images, Synthesia for videos, and ChatGPT for text output. 

4. What are the two main types of generative AI models?

Generative AI applications are built to handle different types of tasks. The capabilities of the platform depend on the foundation model used. GenAI models are broadly classified into two types: 

  • Task-specific GEN (Generative Adversarial Network) 
  • General GAI (generative AI) 

GPT, LLaMa (Meta), PaLM (Google), BERT, BLOOM, etc., belong to general generative AI and are commonly used for personal and business purposes. 

5. Is Google a generative AI?

No, Google is not generative AI as it has been here even before the technology arrived. However, it uses artificial intelligence algorithms to provide powerful search engine results and recommendations. Google is offering generative AI content through platforms like Gemini. 

6. Is chatbot a generative AI?

No. A chatbot may or may not be generative AI. Chatbots have traditional AI and are designed for basic interaction with humans to answer generic queries and provide pre-defined answers. Generative AI takes things one step further and can generate its own content based on the data it has been trained on. It can also generate images, music, videos, etc. 

7. What is the difference between AI and generative AI?

Artificial intelligence commonly used is called traditional AI, weak AI, or narrow AI. It performs tasks based on pre-defined parameters and can carry out limited instructions. It is useful for automating simple yet repetitive tasks. Generative AI uses deep learning, neural networks, NLP, etc., to generate complex output like text, code, images, video, audio, etc. It can ‘converse’ with humans by replicating human language and behavior to a good extent. 

8. Is NLP part of generative AI?

NLP stands for natural language processing. It is a part of artificial intelligence that promotes interactions between a computer and a human by understanding, interpreting, and generating human language meaningfully. Generative AI uses NLP along with other models to create content the way humans do. It takes things further than NLP as it combines the technology with other AI models. 

Fact checked by –
Akansha Rani ~ Content Creator & Copy Writer

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