Are you curious about starting your own business powered by Artificial Intelligence?

In this article, we'll show you how to turn your vision into reality and what you need to build a website or app with AI. We will discuss what are the benefits, best startup ideas, and our own experience in this area. And of course, we’ll give you a ballpark estimation of building such an app.

Discover the exciting journey of embracing technologies of the future.

What is AI

Artificial intelligence (AI) is the simulation of human intelligence in machines, particularly computer systems. Various applications of it include expert systems, natural language processing, speech recognition, and machine vision.

Such systems learn by analyzing large amounts of labeled training data, identifying patterns, and making predictions about future scenarios. This enables chatbots to engage in lifelike conversations and image recognition tools to identify objects in images. AI programming focuses on these cognitive skills:

  • reasoning,
  • learning,
  • self-correction,
  • creativity.

What types of Artificial Intelligence exist

Artificial Intelligence can be classified into various types, each with distinct characteristics and applications. Such categorization of systems helps us better understand and harness their capabilities.

artificial intelligence classification

There are 4 types of Artificial Intelligence, based on the development stage or simply - how smart they are. They range from task-specific intelligent systems to potentially sentient systems:

  • Reactive machines - are task-specific and lack memory. They can perform specific tasks, but they cannot use past experiences to inform future decisions. An example is IBM's Deep Blue, which defeated Garry Kasparov in chess but had no memory of previous games.
  • Limited memory - have memory and can use past experiences to make future decisions. Some self-driving cars use this type for decision-making functions.
  • Theory of mind - would possess social intelligence and understand emotions. It could infer human intentions and predict behavior, which is essential for Artificial Intelligence to work effectively alongside humans. This type is still being worked on but some models like GPT show results that can be compared to a 9-year-old human.
  • Self-awareness - would have a sense of self, granting them consciousness. They would be aware of their own current state. However, self-aware systems are currently only theoretical and do not exist yet.

As science progresses, it is likely that we will see advancements and developments in these different types.

As for the way how it all works and what machines can do, let’s look at some of AI technologies:

  • Automation: AI-driven automation tools, like robotic process automation (RPA), streamline repetitive data processing tasks and can adapt to process changes using machine learning.
  • Machine learning: This science enables computers to act without explicit programming (direct code with precise instructions). It includes supervised learning, unsupervised learning, and reinforcement learning for pattern detection and action feedback.
  • Machine vision: Allowing machines to see through visual information via cameras, digital signal processing, and analog-to-digital conversion. It has applications in signature identification and medical image analysis.
  • Natural language processing (NLP): Machines process human language, with applications like spam detection, text translation, sentiment analysis, and speech recognition.
  • Robotics: Focuses on designing and manufacturing robots, which perform tasks difficult or consistent for humans, such as car assembly or space exploration.
  • Self-driving cars: Autonomous vehicles use computer vision, image recognition, and deep learning to pilot themselves while avoiding obstacles.
  • Generative AI (text, image, and audio generation): This technology creates diverse media from text prompts, including photorealistic art, email responses, and screenplays, revolutionizing content creation.

Most of these technologies can be interconnected. For example, generative AI technology utilizes NLP and ML to produce fresh data resembling human-generated content. Unlike search algorithms that recognize and classify data, it focuses on generating new content.

Generative AI

In this article, we will concentrate on generative AI because it is the hottest trend right now. Most likely, you want to build your product using exactly this technology.

Generative AI is immensely popular today and is expected to grow further due to its ability to create realistic content across various domains, thanks to advancements in deep learning and neural network models. Its applications in content creation, art, and personalization have captured businesses' attention, making it a sought-after technology for innovative solutions.

According to statistics, the global generative AI market is currently worth over $13 billion, expected to reach $22 billion by 2025. It is growing at a remarkable CAGR of 27.02%, with North America holding a significant 41% revenue share. Transformer models account for 42% of generative AI revenues in 2022.

And of course you’ve heard about one of these transformer models called GPT. ChatGPT, a chatbot released by OpenAI in 2022 and built upon the GPT-3.5-turbo model, employs generative AI and natural language processing to mimic human-like conversations within a chat interface. Users can interact with the bot, seeking assistance for various tasks like composing emails, essays, code, and more.

Another hot topic of generative Artificial Intelligence is Bard. It is a conversational chatbot developed by Google. It was initially based on the LaMDA family of large language models and later transitioned to the PaLM LLM. Its API became available in 2023.

DALL-E and DALL-E 2, developed by OpenAI are deep learning models designed to produce digital images based on textual descriptions known as "prompts." DALL-E utilizes a modified version of GPT-3 to accomplish its image generation capabilities.

Midjourney is a program developed by Midjourney, Inc. This innovative system creates images from textual descriptions, known as "prompts," much like OpenAI's DALL-E and Stable Diffusion.

Why to create AI software

The statistics also show great reasons to start a business using Artificial Intelligence.

AI market statistics

The market of Artificial Intelligence is expected to grow significantly, reaching nearly $2 trillion by 2030. An annual growth rate of the industry is expected to be 37.3% from 2023 to 2030. It is predicted to boost the United States' economy by 21% by 2030.

Forbes statistics also show that many businesses believe machines can increase productivity, and 25% of companies are adopting them to address labor shortages. Over 60% of business owners see machines as a tool to improve customer relationships. Business owners are highly optimistic about the potential, with 97% believing that ChatGPT will positively impact their businesses. The manufacturing industry can benefit most significantly, with an estimated gain of $3.8 trillion by 2035 through AI adoption.

But not only business owners see those advantages. 65% of consumers trust businesses that use Artificial Intelligence, demonstrating that its responsible implementation can enhance customer trust and experiences. 50% of U.S. mobile users use voice search daily, indicating the growing importance of virtual assistants.

These numbers underscore AI's positive influence on various aspects of business, from productivity and customer relationships to financial gains, making it an attractive proposition for forward-thinking entrepreneurs.

The hottest ideas of AI application development

AI startups have experienced remarkable growth in funding from 2017 to 2021. Before the COVID-19 pandemic, investments in such startups steadily rose from $18 billion in 2017 to $26 billion in 2020. However, the pandemic's impact accelerated investments, reaching over $65 billion in 2021, particularly in solutions catering to remote work and cybersecurity needs. The growth is driven by the tremendous potential Artificial Intelligence offers to the global economy, with projections estimating a contribution of $15.7 trillion by 2030.

Major players in the industry are actively investing billions of dollars in AI startups, fueling the sector's impressive performance. Here is a list of some of these companies and their respective investment amounts:

  • Salesforce Ventures plans to give $500 million for startups that develop generative AI technologies.
  • Workday added $250 million to its existing VC fund specifically for Artificial Intelligence and machine learning startups.
  • Microsoft invested $10 billion in OpenAI’s GPT models development and became one of the first adopters of ChatGPT technology.
  • OpenAI, at the same time, raised a $175 million fund to invest in AI startups.
  • Dropbox created a $50 million AI-focused venture fund.
  • AWS (Amazon Web Services) promises to put $100 million into a program funding generative AI initiatives.
  • Accenture is going to invest $3 billion in Artificial Intelligence.
  • PwC plans to invest $1 billion in AI.

With the rosiest predictions pointing towards transformative gains, the AI startup landscape holds promise for innovation and prosperity in the years to come. In 2023, several startups emerged as leaders in the industry, each specializing in different applications of artificial intelligence. These startups are making a great difference in their sectors, including customer service, workplace efficiency, content creation, design, and traffic analytics. Here are top AI startups  for 2024 with the most notable growth:

top startups 2024

  • DeepL: A neural machine translation platform offering accurate translations across over 30 languages using advanced algorithms, neural networks, and NLP for various content types.
  • Frame AI: A customer success platform utilizing AI to solve numerous customer challenges, enhancing customer experience and engagement.
  • Uizard: An AI-driven tool that converts sketches into functional website and app designs with minimal coding, streamlining the prototyping process.
  • Moveworks: An AI platform improving workplace experiences through NLU, conversational AI, and machine learning, automating employee support processes.
  • Tome: A cloud platform for creating interactive, multimedia documents with ease, supporting text, images, videos, and interactive elements.
  • Synthesia: Enables businesses to create personalized, realistic video content at scale using AI, suitable for e-learning, marketing, and more.
  • Jasper: Evolved from an AI writing tool to a collaboration platform for marketing teams, facilitating campaign development and content creation.
  • Accubits: An agency providing customized AI solutions across various industries, working with governments, Fortune 500 companies, and more.
  • Soundful: Offers AI-powered custom soundtracks for digital content, analyzing emotions and context to enhance viewer experience.
  • GoodVision: Uses AI for traffic analytics from cameras and drones, offering real-time insights and suggestions on traffic patterns.

These startups are contributing to the rapid advancement and integration of machines in various aspects of daily life and business operations.

Challenges of AI startups

Despite continuous evolution of technologies, not everything goes so smoothly. AI startups face several significant challenges on their journey to success:

  • Acquiring the right talent with expertise in Artificial Intelligence and related fields can be difficult, as the demand for skilled professionals often exceeds the supply.
  • If you want to create your own model from scratch or to adopt a model which you need to train using substantial computational resources, this leads to high infrastructure costs.
  • Data access and quality can also pose challenges, as machine’s algorithms heavily rely on large, high-quality datasets for training and validation.
  • Such startups often encounter regulatory hurdles and ethical considerations, especially concerning data privacy and bias. That is why ChatGPT was banned in several countries.
  • Gaining user trust in AI applications and convincing potential customers of the technology's value can be another obstacle. Even business owners are prone to think that machines can be dangerous. For example, a quarter of entrepreneurs think they can impact website traffic.
  • Becoming obsolete before even reaching the market: Vinod Khosla, one of OpenAI investors, points out how important it is to focus on ideas that can stand the test of time, as the speed of change in the industry can quickly render concepts obsolete. Relying solely on current technologies may not ensure long-term success; startups need to create robust and adaptable solutions to keep up with advancements in the field.
  • Generative AI can be difficult to understand. Due to its complexity it might be not appropriate for small businesses that are not ready to deal with technical issues.
  • User personal data might be in danger. AI technologies can be a gray area in terms of data security, e.g. who records and has access to users data.

Despite these challenges, successful startups can achieve remarkable advancements and disrupt industries, making the pursuit rewarding and worthwhile for those who navigate these obstacles efficiently.

Steps to build an AI app

Here steps you will need to take to create a successful AI business:

steps to build an AI Startup

1. Conduct a Discovery phase

The first step is to find a real-world problem or a valuable application where Artificial Intelligence can make a difference. This could be automating repetitive tasks, improving decision-making, or providing personalized recommendations.

Conduct thorough market research to understand the potential demand for your solution. Identify your target audience and competitors in the industry. Knowing what similar products or services are already available will help you refine your value proposition and find unique selling points.

2. Hire a skilled team of experts and engineers

Building a competent team with expertise in Artificial Intelligence, machine learning, data science, and software engineering is essential. Look for individuals who have experience in developing AI solutions and are passionate about tackling the specific problem your startup aims to solve.

3. Choose an AI platform for your project

Choosing the right platform is crucial for successful implementation of your app. There are several top platforms for applications with Machine Learning, such as Azure, IBM Watson, Tensorflow,,, Amazon AI, and Clarifai. These platforms streamline the AI implementation process, offering advanced features and tools to create robust and innovative applications.

To make the best choice, consider factors like compatibility, ease of integration, scalability, security, and community support. Additionally, leveraging third-party Artificial Intelligence and Machine Learning platforms, as well as deep learning frameworks, can optimize development costs and accelerate the adoption of these technologies in various industries.

4. Develop a basic version of the product to gather feedback (MVP)

Create a Minimum Viable Product (MVP) to launch a basic version of your solution. This allows you to test your idea in the market, gather user feedback, and identify areas for improvement.

5. Address legal and ethical considerations

AI startups must be aware of legal regulations, especially concerning data privacy and security. Additionally, be conscious of potential biases in algorithms and strive to ensure fairness and transparency in your application.

6. Stay updated with the latest trends and innovations

The field of Artificial Intelligence is constantly evolving, with new breakthroughs and advancements. Encourage continuous learning within your team to stay updated with the latest developments and maintain a competitive edge in this landscape.

AI app development cost

The cost of developing an AI startup can vary significantly depending on several factors: chosen technology, complexity of the app, team’s expertise, and hourly rate.

Team's hourly rate can be influenced by their reputation and location. Hourly rates typically range from $20-40 in Asia and Africa, $30-50 in Latin America and Eastern Europe, $75-100 in Western Europe, and $90-150 in North America. However, it's important to consider that the team with the lowest rate may not always be the most cost-effective choice in the long run. A cheaper team might result in the need for extensive rework or even a complete redo of the product.

At Greenice we have extensive experience in developing custom AI-powered projects and chatbots, including those powered by GPT and Dall-E models. That allows us to offer comprehensive services from idea creation to post-launch maintenance.

Based on our expertise, the development cost for an AI-chatbot can start from $10,000 for a minimum viable product (MVP). It's important to consider the quality and expertise of the development team when determining the cost, as investing in a capable team can lead to a more successful and efficient project in the long term.

Also, consider the price of the model used for such a chatbot. For example, utilizing GPT-3.5-turbo will cost you $0.002 per 1,000 tokens, while GPT-4 will cost $0.06 per 1,000 prompt tokens and $0.12 per 1,000 sampled tokens. The more powerful model capabilities are - the more expensive it is. However, the price for GPT-4-Turbo is 3x lower than for previos version, while it can be even more capable.

As for image-generating technologies like Dall-E. There are also 2 components: model price and work rate. Model pricing depends on resolution:

$0.020 per image
$0.018 per image
$0.016 per image

But based on our experience such an AI project may be fulfilled for $30,000-50,000 for basic functionality, including dashboards.

Our experience

We, at Greenice, have gained valuable experience in the AI application development services. Here are a couple of our projects.

GPT-powered virtual assistant

Greenice GPT-powered virtual assistant

At first, we used GPT-3 to enhance the capabilities of our chatbot and fine-tuned it to our needs. Training GPT-3 required expertise in machine learning and natural language processing, making it essential to collaborate with experienced engineers and data scientists for successful implementation.

We trained the bot using our knowledge base and website content. After the training it was able to answer questions acting as a consultant and collect user data to contact them and book a call.

Later, we switched to the ChatGPT API for our website's chatbot. The integration of ChatGPT has brought a breakthrough in analyzing unstructured data from conversations, allowing the chatbot to collect essential information such as user names, emails, and meeting times, significantly improving its efficiency in providing personalized responses to our clients.

The switch to ChatGPT API proved to be more suitable and cost-effective, enabling the chatbot to answer questions about Greenice and its services while also facilitating interactions with human managers when required.

Mobile app with Dall-E integration

image generating app with Dall-E integration

We created an app that lets you edit images using words. With Dall-E integration, you can upload an image and choose what you want to add or change - like adding an accessory or drawing a cat. It's an easy and fun way to make your images look exactly the way you want them to be. The user just types your request, and the Artificial Intelligence will do the rest.


In this article we discussed how to build an AI app. Despite some challenges creating an application or a website with Artificial Intelligence integration is truly beneficial for your business. And it becomes possible with the outlined steps, which include Discovery Phase, choosing skilled team and right technologies, and launching MVP.

As for costs, it is crucial to consider factors such as development time, data acquisition, and infrastructure. Our experience in building AI systems has shown that with the right team and a well-defined strategy, the results can be truly transformative.

Are you ready to unleash the potential of artificial intelligence in your projects?

Looking for an AI app development company?

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Inna Lebedeva

Inna Lebedeva is a market researcher and writer at Greenice web development company. She investigates IT niches and writes articles for entrepreneurs who want to launch their business in those niches. Utilizing our experienced Greenice team, and intensive market research, Inna provides in-depth analysis to business owners, enabling them to make informed decisions.

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Yevhen Saveliev

Yevhen is a Chief Operating Officer at Greenice. He has previously worked at Area Sales Executive at Reikartz Hotel Group, the biggest hotel chain in Ukraine. Yevhen is enthusiastic about the hotel industry and can come up with non-standard ideas on improving sales processes with the help of technologies.

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