9 Things Start-up Leaders Should Know About Generative AI

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9 Things Start-up Leaders Should Know About Generative AI

Generative AI uses deep learning algorithms and other technologies to generate output based on the user input. It is an advanced form of general AI capable of handling versatile tasks. Here, we’ll discuss the various aspects startup leaders should know about generative AI to implement the technology in their businesses. 

Artificial intelligence has been revolutionizing various industries in recent times. Statistics show that the annual AI adoption rate will grow by 37.3% from 2023 to 2030. Artificial intelligence is integral in our personal, social, and professional lives. 

However, we know that AI is still in the initial stages of exploration. Generative AI is a prime example of this. ChatGPT has changed the way we look at AI. It has created many discussions across the globe. The top companies have been working hard to release their versions of generative AI tools. Other SMBs and multinational organizations are hiring AI consulting firms to understand the importance of generative AI and adopt relevant tools to boost their business. 

But what is generative AI? What does it do in today’s scenario? How can CEOs and entrepreneurs use generative AI in their businesses? 

Let’s find the answers to these questions. 

What is Generative AI, and How Can it Help Your Business?

Generative AI is a set of algorithms that can generate new content (text, image, video, audio, etc.) from the training data. The generative AI models are built on models trained using large datasets with unlabeled data. The algorithms learn to self-supervise themselves and identify the underlying patterns. It uses deep learning to complete tasks effectively compared to other AI models. 

The generative AI landscape covers a range of applications that optimize business processes, create content, brainstorm ideas, write and debug codes, etc., to reduce pressure on employees and complete tasks effectively. 

Enterprises can use generative AI in various ways to revamp their business model, reduce costs, increase productivity, and generate higher ROI. Generative AI is a subset of machine learning and is different from discriminative AI, which deals with data categorization. 

Generative AI models help businesses in the following ways: 

  • Customer engagement
  • Speeding up research and development 
  • Accelerating clinical trials 
  • Developing new business models 
  • Assisting employees to complete complex tasks 
  • Content creation, editing, and summation 
  • Generating art, images, audio, and multimedia
  • Streamlining marketing and promotions, etc. 
Generative AI

What are Various Techniques Used for Generative AI?

Generative AI is not based on any single technique but is a combination of several techniques, such as: 

  • Artificial Neural Networks (ANN)
  • Generative Adversarial Network (GAN)
  • Variational Autoencoder (VAE)
  • OpenAI’s Generative Pre-trained Transformer (GPT)
  • Bidirectional Encoder Representations from Transformers (BERT)
  • Google AlphaFold
  • Transformers, etc.  

These techniques allow generative AI to process input data and generate output as required by the user. This is why generative AI can create versatile types of texts, images, videos, 3D designs, etc. It is highly useful in the medical and healthcare industry as it generates 3D visualizations of DNA structures, proteins, crystals, drug combinations, and so on. 

However, all of them are not in every generative AI model. AI leaders choose the necessary techniques based on the type of model they want to create and its purpose. 

Should Start-Ups Explore Generative AI?

The answer is yes. Startups, small businesses, and growing companies should explore generative AI to survive in competitive markets. Using the latest technology to streamline internal processes and increase ROI will strengthen the foundation and allow startups to stand alongside established enterprises. Furthermore, startups can directly develop agile and scalable IT infrastructure and save money on replacing legacy systems. 

However, it’s vital to make informed decisions when bringing major changes to the business model. AI consultants recommend that CEOs understand the following aspects to know how generative AI can benefit their business. 

Generative AI

1. Fast Developments in Generative AI 

Generative AI is evolving at a rapid pace for the last few years. From OpenAI’s ChatGPT to Google’s Med-PaLM, Meta’s LLaMA, Amazon Bedrock, Google Bard, and Microsoft’s integration of ChatGPT 4 with Office 365, the developments are occurring frequently. 

Entrepreneurs should understand that generative AI and the future are not fixed but constantly evolve. They need to create an infrastructure and work culture where technology and talent can keep up with the developments and adapt to the changes quickly time. Constant investment is necessary to stay up to date. Generative AI is not a one-time investment. 

2. It’s More Than a Chatbot 

Even though we know of generative AI as an advanced chatbot, it is a lot more complex and capable. However, generative AI takes things ahead. It can classify, edit, and summarize almost any type of content. It can answer questions, draft letters, code, outline, strategy, and more. 

As the models evolve, generative AI can be integrated with enterprise workflows to automate and perform specific tasks. Some AI tools are already providing these services. 

3. Scalability and Competitive Advantage 

Generative AI is versatile and scalable on various levels. Firstly, it is different from other deep learning models that can perform only one specific task. Generative AI can handle multiple types of tasks, resulting in greater efficiency and productivity. This makes it easier to use a single model to perform all the necessary tasks at work and gain a competitive advantage in the market. It can also be scaled to suit the growing business needs. 

4. Identifying the Right Use Cases 

The success of any technology or development can be seen when it is used for the right purpose at the right time and in the right manner. CEOs should ensure that they know why, how, where, and when they want to use the tools in their startups. The budget of the project will also depend on these aspects. 

For example, generative AI in the customer service department can assist representatives in quickly solving customers’ complaints and speeding up ticket closing. Similarly, the sales and marketing team can brainstorm strategies and use generative AI to create a foolproof promotional campaign and relevant content without spending too much time and resources. CEOs have to identify where to use generative so that they can decide on the next step. 

5. Reworking Existing Model vs. Training New Model

Is generative AI rewriting your business model? The answer depends on the use cases you finalize and how you want to achieve the results. If you already have accurate ML models, you can customize them and set up integrations with generative AI. 

For example, using generative AI as a SaaS (software as a service) tool is cost-effective compared to building software with API layers or training a foundational model. Moreover, not all tasks require a fresh model with extensive investment and research. AI leaders can help CEOs make the right decisions. 

6. Preparing the Workforce 

One of the biggest perceived generative AI implications is that the models will replace the human workforce with computers and robots. This can make your employees resist the changes. Startups can suffer financial losses in such instances. It’s the top management and CEO’s responsibility to prepare, educate, train, and assure employees about adopting generative AI tools. 

Redefine their roles and responsibilities to help them use generative AI for day-to-day work. For example, employees in clerical roles can use the tools to create drafts, fine-tune their written content, etc. Software developers can use generative AI to quickly create the code for a new application or debug existing code to get rid of errors and executive the program correctly. 

7. Changes to the Operational Model 

Using generative AI tools require centralized systems and database. It’s common for businesses to have data silos in individual departments. This makes it hard to correctly implement advanced technologies in the present and ensure their scalability for the future. Having a chief AI officer to oversee the entire process will keep the data scientists connected with the rest of the business and have access to the necessary data at all times. 

8. Risk Mitigation, Social Responsibility, and Ethical AI 

CEOs should be aware of the risks that come with using generative AI tools. It’s crucial to establish robust data governance that establishes the necessary guidelines to use the tools and also experiment with them. 

Data security, data quality, data privacy, etc., are a common concern in today’s world. The management has to make sure that the business doesn’t violate the global regulations for data privacy or use generative AI for something that could harm mankind. Fairness, intellectual property rights, reliability, user consent, etc., should be considered to prevent inadvertent misuse of generative AI. 

9. Developing an Ecosystem 

Generative AI models don’t work in isolation. CEOs should consider the role of a value chain supporting the systems at multiple levels. This also makes it easier to strengthen the business processes and be proactive in adopting the latest technologies. Startups can achieve this by working with experts from offshore generative AI companies

What are Generative AI Tools? 

Though generative AI is still being explored, there are numerous tools already available in the market. Some are free to use, and others come with paid subscriptions to explore full features. Here, we’ve classified the tools into three broad categories: 

AI Chatbots 

ChatGPT by OpenAI is a revolutionary chatbot that interacts with humans as another human would. It goes beyond the generic AI chatbots as it uses the input as feedback to provide better responses. According to Statista, ChatGPT broke all NLP records to have one million users in the first five days of release. The latest GPT-4 offers more advantages, such as creating websites based on images, creating and improving code, generating recipes based on the input image of ingredients, etc. It is much more powerful than the original version. 

Google Bard is considered a rising competitor to ChatGPT and is called a creative and helpful collaborator. It works similarly to ChatGPT and provides relevant responses to the given input. From streamlining search to debugging code, brainstorming ideas, summarizing text, or creating outlines, it can be used for an array of tasks. 

According to the latest announcement, Google Bard has several big updates scheduled over the coming months. It will be able to create AI images with integration with Adobe Firefly. It provides image search results with more information by using Google Lens. It can also code in 20+ programming languages with citation links to Github (isn’t that awesome?).

Another important update is the export button, where you can automatically send the data to Gmail or Google Docs. You can combine Google Maps with images and use the chatbot to plan and book your trip to any destination. And finally, Bard has Dark Mode too! There’s no longer a waiting list for Google Bard. It’s open to everyone.

AI Visual Generators 

DALL-E and DALL-E are deep learning models developed by OpenAI to generate images for the given text input. Users can ask the platform to create different types of AI art by providing the guidelines as text input. DALL-E 2 is an API that can be integrated with third-party apps and used by enterprises. 

Synthesia AI is a video generator platform that converts text to speech for 120 languages and generates videos in just fifteen minutes. Users can choose avatars from the existing 140+ collection and customize the videos to make them appear professional and real. It’s a great tool for converting boring presentations into attractive videos. 

AI Audio and Music Generators 

Replica is an AI voice generator trained by professional voice artists. It copies the voice, tone, speech patterns, etc., of real people and replicates them. The platform currently has 40+ voices (with more being added regularly) to choose from. Users can select an AI voice actor and customize the bites to produce natural-sounding audio files. 

Soundraw is an AI music generator platform to create royalty-free music using artificial intelligence. Users have to select the mood, genre, and length of the track. The platform will automatically create a track for them. These songs can also be customized and used with podcasts and video content. 

It is tempting to ask- what are the best generative AI apps to try? However, there is no standard answer to this question. The best app depends on your requirements and budget. For example, ChatGPT is free (with certain limitations), but ChatGPT4 needs a subscription (tokens) and offers better results. 


The benefits of using advanced technology and digital transformation will depend on how CEOs approach generative AI in their startups. Leaders and C-level executives deal with various unknown elements and challenges to ensure their adoption of generative AI is successful and gives the expected results. 

Here, it is helpful to partner with companies offering end-to-end AI consulting services tailor-made to suit the varying specifications of each startup and enterprise. From aligning business vision to workplace culture, internal processes, and long-term goals, AI consultants will assist CEOs at every stage and boost business revenue. 

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