Building AI: Understanding Development and Сalculating Costs

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Nowadays, artificial intelligence (AI) stands as one of the most impactful inventions. The widespread adoption of AI software is evident across various businesses, driving transformation, revenue growth, and a broader customer base. Accepted globally, AI appeals to both customers and tech enthusiasts. The fast-evolving tech scene, dominated by AI, has reshaped business operations throughout 2023 and continues to do so in 2024. As companies seek to leverage AI’s power, a crucial question arises: “How much does it cost to build software in 2024?” This article delves into the comprehensive expenses associated with artificial intelligence software development in the upcoming year. Join our long read! 

What AI is?

Artificial Intelligence is the technological marvel that empowers machines to mimic human intelligence – from learning and problem-solving to speech recognition and decision-making like in a Hospital app development. Essentially, AI equips machines with the ability to adapt, evolve, and perform tasks that traditionally require human intelligence, revolutionizing the way we approach challenges and innovate in the digital era.

How and for what AI is used in businesses?

AI is a versatile tool employed for automating repetitive tasks, optimizing processes, and extracting meaningful insights from vast datasets. From enhancing customer interactions through AI-powered chatbots to streamlining supply chain operations with predictive analytics, businesses harness AI to make informed decisions and gain a competitive edge. Its applications span across various sectors, facilitating improved efficiency, personalized customer experiences, software testing, and strategic decision-making for sustainable growth.

AI can enhance the accuracy of clinical diagnoses. In 2023, it is projected that AI will be utilized to diagnose medical conditions with an accuracy rate exceeding 90% (Forbes).

Unlocking Advantages: Key Benefits of Incorporating AI for You and Your Business

In the era of task automation, decision optimization, and elevated customer interactions, the allure of implementing AI solutions is irresistible for businesses. Yet, is the investment in AI justified for your specific business? How much does an AI cost?

The answer varies, and a nuanced understanding of its pros and cons is crucial. Consider the immediate Top Benefits AI offers:

  1. Increased Efficiency and Productivity: 

    Chatbots and AI. Automation liberates employees from repetitive tasks, allowing a focus on higher-level work.

  2. Improved Decision-Making:

    AI’s data analysis surpasses human capacity, providing insights for enhanced decision-making.

  3. Enhanced Customer Experiences:

    AI-driven chatbots and virtual assistants ensure 24/7 customer support, elevating satisfaction and retention.

  4. Competitive Advantage:

    AI implementation grants a competitive edge, optimizing business operations for efficiency and effectiveness.

The image below gives even more encouraging reasons:

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AI benefits for your business

Worldwide statistics of investment into AI

The following facts and numbers show the increasing importance of AI as a tool in healthcare. As technology continues to advance, we can expect to see even more innovative applications in the years to come. 

Here you can see the impressively consistent growth of the cost of AI investments with almost 188 billion USD forecasted in 2030.

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AI in Healthcare Statistics
Yet, according to Statista, during Q1 2023, global artificial intelligence (AI) startup funding experienced a significant decline, reaching a level not witnessed since early 2018, with a notable drop to USD 5.4 billion. This marks a correction from the unprecedented funding levels observed in 2021 and 2022 post the COVID-19 pandemic. The contraction in funding for startups, indicative of a broader economic downturn in 2023, particularly impacts less established and forward-looking projects.
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Global AI Startup Funding in US Dollars: 2011-2023
The researches show that in 2023, North America stands at the forefront of integrating Artificial Intelligence (AI) in healthcare. Graphical Research reports that the market size in North America exceeded USD 187.95 billion in 2030 and is anticipated to experience a remarkable 37% Compound Annual Growth Rate (CAGR) from 2023 to 2030. The region is poised to lead the global healthcare AI market due to its advanced healthcare infrastructure, widespread adoption of AI technology, and an increasing demand for personalized treatment options.
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AI in Global Market

Ready to start a project to implement artificial intelligence to grow your business?

What's The Average Cost For AI Solutions?

AI solution costs exhibit a wide range, with averages fluctuating between $0 and upwards of $500,000 for companies. Custom AI solutions, tailored to specific needs, span from $6,000 to over $500,000, contingent on project intricacy and resource demands. Third-party AI software, including pre-built solutions, ranges from $0 to an annual cost of $40,000. Notably, free solutions may not suffice for the extensive marketing needs of larger businesses. Consulting AI services, with fees varying based on hourly rates, typically range from $200 to $350 per hour. The diverse pricing landscape reflects the breadth of available AI solutions, catering to both customized, resource-intensive projects and more accessible third-party options.

AI Solutions Average Cost Range
Custom AI Solutions
$6,000 to over $500,000
Third-Party AI Software
$0 to $40,000 per year
Consulting AI Services
$200 to $350 per hour

This table summarizes the average cost ranges for different AI solutions, including custom AI solutions, third-party AI software, and consulting AI services.

How Expensive Is AI: Three Examples of Different Projects


    A healthcare tech firm asked Telemedicine software development experts to enhance a telehealth system used in multiple US hospitals, integrating video recording capabilities. The upgraded system employs facial recognition and natural language processing to analyze consultation videos, aiming to enhance doctor-patient interactions. Using Python and relevant frameworks, the team addressed potential technology barriers. The initial pilot focused on speech-to-text functionality, emphasizing linguistic analysis to identify changes in communication styles for improved patient care. The estimated cost for a basic video/speech analysis AI platform was $36-56 thousand.


    A tech entrepreneur had to infuse AI into a B2C platform linking users with local services. The concept aimed to replace traditional search filters with advanced ML algorithms for precise service provider suggestions. Amazon Personalize was chosen as the primary tech stack, offering personalized recommendations and a managed cloud infrastructure. Python would drive the backend, and user data would be securely stored on Amazon S3. The estimated artificial intelligence costs cost for developing a similar platform (MVP) ranged from $20 to $35 thousand.


    A renowned artist approached developers to make an AI-driven art generator creating new paintings inspired by the artist’s works and those of influencers. Aimed for an MVP for an upcoming exhibition, the team proposed a neural network using Python frameworks (PyTorch, TensorFlow). The system learns the artist’s style, generates similar paintings, and showcases them on the artist’s website. For the MVP, Instagram-like 1000×1000 resolution was offered, as well as local AI deployment, with a future option for cloud migration. Building a similar AI system MVP may cost $19-34 thousand, contingent on factors like training data and image resolution.
Project name Technology stack Key features Estimated cost (MVP)
AI-Enhanced Telemedicine
Python, NLP, Facial Recognition
Video recording, Speech-to-Text, Improved doctor-patient interactions
Smart Recommendation System
Python, Amazon Personalize, Amazon S3
ML-based Service Recommendations, Personalized User Experience
AI Art Generator
Python, PyTorch, TensorFlow
Neural Network-based Art Generation, Style Replication, Image Showcase

How much does Artificial Intelligence cost? Key Factors

AI project costs vary based on critical factors businesses must evaluate before investing. Key cost-affecting factors include:

1. Type of AI:

  • Pre-built solutions (e.g., chatbots, content writing AI, recommendation engines, fraud recognition, predictive maintenance) are generally more affordable due to less customization.
  • Custom-built solutions (e.g., analysis systems, supply chain optimization, process optimization, virtual assistants) tend to be pricier, requiring extensive design, development, and maintenance efforts.
Type of development Cost of AI development
Software Cost
$30,000 - $45,000
Manpower Cost
$25 - $49/ hour
Training & Maintenance Cost
$8,999 - $14,999

The stated AI cost is an estimate and can vary based on factors such as the company size for custom AI development and the complexity of the AI solution. 

In 2024, businesses may invest in AI software, with costs ranging from zero to over $300,000. These software options vary, encompassing third-party solutions to personalized platforms crafted by in-house or freelance data scientists.

AI Type Cost
Custom AI solution
$6000 to $300,000 / solution
Third-party AI software
$0 to $40,000 / year

The company’s size significantly influences the budget for AI development when hiring. 

Company Size Cost Personnel
Small Size Company
$20,000 to $ 45,000
Mid Size Company
$50,000 to $1,00,000
Large Size Company
$1,00,000 to $15,00,000

The image below shows some of the non-technical factors that are also important:

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Non-technical factors of artificial intelligence cost

2. Project Complexity:

  • The complexity of the AI project influences costs, with more intricate projects demanding additional resources, time, and expertise. Here we explored the extent of its impact on the development cost.
Complexity Level Cost Estimation
Low-Level Complex AI
$15,000- $35,000
Medium Level Complex AI
High-Level Complex AI

3. Size of the Data Set:

  • The volume of data processed affects the costs of AI, as handling larger datasets may require more advanced infrastructure and expertise.

Is AI justified in its cost?

It depends on your approach. While the value of AI in streamlining processes, leveraging data, and enhancing customer experiences is undeniable, the associated expenses may give pause. However, businesses need not solely opt for custom solutions; pre-built options, like chatbots, offer substantial benefits without straining budgets. For advanced AI applications, platforms utilize the power of IBM Watson, providing actionable insights and content analysis. These alternatives make AI investment more accessible, enabling businesses to reap the benefits without incurring the high costs of custom development. 

AI has proven effective in enhancing patient outcomes and reducing healthcare costs. For instance, AI-powered chatbots can assist patients with mental health issues by providing 24/7 support and reducing the need for in-person therapy sessions.

AI potential

AI potential
AI potential

From revolutionizing web page rankings to streamlining walk-thru orders via voice commands, AI has become integral to diverse business operations for compelling reasons.

Businesses universally aspire to optimize operations, seeking efficiency, accuracy, and convenience, all of which AI delivers. Its capacity to handle vast data sets and discern optimal actions is just the beginning.

The versatility of AI extends to every industry and business niche:

The extension of AI in the modern world
The extension of AI in the modern world

Why do I need AI for my business?

Here is a top 10 list to answer the question. 

  1. Efficiency: AI streamlines processes, automates repetitive tasks, and enhances operational efficiency.
  2. Data Analysis: Harness the power of AI to analyze large volumes of data quickly and derive actionable insights for better decision-making.
  3. Customer Experience: Improve customer interactions through AI-powered chatbots, personalization, and efficient support services.
  4. Competitive Edge: Stay ahead of the competition by leveraging AI for innovative solutions, optimizing strategies, and adapting to market trends.
  5. Cost Savings: Automate tasks to reduce labor costs, minimize errors, and make operations more cost-effective.
  6. Predictive Analytics: Utilize AI algorithms to predict trends, customer behavior, and market changes, enabling proactive decision-making.
  7. Customization: Tailor AI solutions to your specific business needs, whether it’s in marketing, supply chain, or customer relations.
  8. Scalability: AI systems can scale with your business growth, adapting to increased data volumes and operational demands.
  9. Risk Management: Enhance risk assessment and mitigation through AI algorithms that analyze patterns and identify potential threats.
  10. Innovation: Foster innovation within your business by exploring AI applications that could transform processes, products, or services.

Maximizing Income Growth: The Impact of AI on Business Revenue

Implementing AI can significantly boost your business income by enhancing efficiency, improving customer experiences, and enabling data-driven decision-making. Through automation of repetitive tasks, AI reduces operational costs, allowing resources to be allocated more strategically. The personalized insights generated by AI also contribute to better-targeted marketing and sales efforts, ultimately increasing revenue. 

Metric Without AI With AI
Operational Costs
Higher due to manual processes
Reduced with AI automation
Customer Conversion Rates
Standard rates
Improved through personalized AI-driven strategies
Marketing ROI
Standard returns
Enhanced with targeted AI-powered campaigns
Overall Revenue
Limited growth potential
Potential for substantial growth with AI-driven optimizations

Ready to start a project to implement artificial intelligence to grow your business?

How Long Does AI Development Take?

How long it takes to develop AI depends on several factors, with the primary determinant being the level of complexity involved. Development time varies based on complexity, and the approximate timeframes are as follows:

Complexity level Development time
Low-Level Complex AI
2-3 Months
Medium Level Complex AI
4-5 Months
High-Level Complex AI
5-7 Months

The delivery timeframe can vary based on demand and any additional requirements that arise during the development process.

Navigating Challenges

The allure of AI comes with its own set of challenges:

  • High Implementation Costs:

    The initial investment for AI implementation can be substantial.

  • Potential for Bias:

    AI algorithms may exhibit biases, posing challenges in fair decision-making.

  • Data Privacy Concerns:

    Businesses must navigate potential privacy concerns associated with AI-driven data processing.

One of the significant challenges is ensuring the security of patient data. By 2023, it is anticipated that 80% of healthcare organizations will have implemented AI-powered security systems to protect patient data (HealthTech Magazine).

Let’s look at this visual demonstration:

Business milestones of AI adoption
Business milestones of AI adoption.

Here we can see that challenges affect both people and technology as well as the very workflow processes. 

In weighing the benefits against the challenges, businesses can make informed decisions about the adoption of AI technologies.

Key Considerations: Understanding the Maintenance Costs of AI

Ensuring the sustained operation of a sophisticated AI model involves considering four key factors in maintenance costs:

  1. Hardware Maintenance:

    Regular upkeep, updates, and repairs are vital to prevent system malfunctions and downtime, preserving overall business productivity.

  2. Software Maintenance:

    Critical for AI algorithms, regular software updates, patches, and bug fixes are essential to keep the system current and functioning seamlessly.

  3. Data Maintenance:

    Data, integral to AI systems, requires ongoing cleaning, organization, and storage for accessibility and usability. Proper data maintenance is crucial for accuracy and effectiveness, preventing incorrect predictions and decisions.

  4. Expertise:

    Maintenance demands specialized technical expertise, with AI professionals commanding high salaries. While internal expertise is an option, many companies find it more practical to source externally.

Software Maintenance factors
Software Maintenance factors

Considering these factors, along with any niche-specific costs, is essential before embarking on AI system development to ensure a comprehensive understanding of associated expenses.

Strategies for Cost-Effective AI Maintenance:

  1. Outsourcing AI Development:

    Tap into the expertise of an external team to minimize the risk of errors and reduce labor costs associated with hiring and training.

  2. Leveraging Open-Source AI Technologies:

    Familiarize yourself with available open-source technologies, providing a cost-effective foundation for AI development and eliminating the need to build a proprietary system from scratch.

  3. Investing in Cloud-Based AI Solutions:

    Opt for cloud-based AI solutions for cost savings, enhanced accessibility, and scalability. These solutions are generally more affordable than on-premises alternatives, enabling quick access to new capabilities without significant investments in hardware or software.

Tips to reduce tech maintenance costs
Tips to reduce tech maintenance costs

Stories Of Success

Here are a few examples of companies and how they have benefited from implementing AI:

  1. Google:

    Benefit: Enhanced Search Algorithms and Personalized User Experience

    How: Google uses AI to refine its search algorithms, providing more accurate and relevant results. Additionally, AI is integrated into services like Google Maps and Gmail for personalized recommendations and smart features.

  2. Amazon:

    Benefit: Improved Customer Recommendations and Supply Chain Optimization

    How: Amazon employs AI for personalized product recommendations, increasing sales. In their warehouses, AI-powered robots help optimize logistics and enhance overall operational efficiency.

  3. Netflix:

    Benefit: Personalized Content Recommendations

    How: AI algorithms analyze user viewing patterns and preferences, enabling Netflix to suggest tailored content recommendations. This personalized approach improves user engagement and retention.

  4. Tesla:

    Benefit: Autonomous Driving and Vehicle Safety

    How: Tesla utilizes AI for its Autopilot feature, enabling semi-autonomous driving capabilities. AI algorithms continuously learn from real-world driving data, improving overall vehicle safety and performance.

  5. IBM:

    Benefit: Advanced Data Analytics and Watson AI Solutions

    How: IBM’s Watson AI platform is used for data analytics, helping businesses extract valuable insights. Industries ranging from healthcare to finance benefit from AI-driven solutions, enhancing decision-making processes.

  6. Facebook:

    Benefit: Enhanced User Experience and Ad Targeting

    How: Facebook employs AI to personalize the user experience, curate news feeds, and optimize ad targeting. The platform’s algorithms analyze user behavior to tailor content and advertisements.

These examples highlight how diverse industries leverage AI to improve efficiency, personalize user experiences, and drive innovation.

Ready to start a project to implement artificial intelligence to grow your business?

Key Factors for Consideration Before Investing in AI Development

Factor Description
Type of AI
Assess whether pre-built solutions or custom-built solutions are required, considering project goals and complexity.
Project Complexity
Gauge the complexity of the AI project, influencing development time, resources, and overall investment.
Size of the Dataset
Gauge the complexity of the AI project, influencing development time, resources, and overall investment.
Objectives and Benefits
Clearly define project objectives and expected benefits to align development efforts with business goals.
Technology Stack and Expertise
Identify the appropriate technology stack and ensure access to skilled professionals for effective implementation.
Data Privacy and Compliance
Evaluate and address data privacy, security, and compliance requirements to ensure ethical and legal AI development.

Understanding the scope, complexity, and requirements of the AI project is worth the gold. Factors such as the type of AI, project complexity, and the size of the dataset play crucial roles in determining the development approach and costs. Plus, evaluating the potential benefits, defining clear objectives, and identifying the right technology stack and expertise are fundamental steps. Collaboration with experienced AI developers can further streamline the development process and contribute to the project’s overall success.

Start your project with ZenBit

Estimating the artificial intelligence cost of projects can be challenging, especially without a clear project roadmap. For guidance, consult Web App Development Company specialists like ZenBit Tech developers who follow a systematic approach to estimating and implementing AI projects. They assess project scope, evaluate resource needs, and consider factors like data procurement and cloud expenses. While pricing AI projects involves numerous factors, taking a small initial step to validate the AI idea is crucial. This ensures informed decision-making before committing to a company-wide AI adoption, without requiring an unlimited budget. 

AI Development Process in ZenBit

Developing an AI software solution is a strategic process that we, at ZenBit Tech, navigate through confidently. Our approach encompasses key steps:

  1. Identify the Need: We understand user problems, focusing on delivering value through our solutions.
  2. Get the Right Data: Our team acquires and refines data, differentiating between unstructured and structured types, ensuring its optimal quality. Here also comes the estimation of AI app development cost.
  3. Create the Algorithm: Crafting a precise algorithm is a crucial task entrusted to our expert team at ZenBit Tech.
  4. Algorithm Training for AI: We optimize the algorithm during training, striving for the highest accuracy in AI operations.
  5. Choose the Perfect Platform: Selecting a suitable cloud platform is our expertise, enabling swift experimentation, development, and deployment of ML models.
  6. Choose the Programming Language: We choose from Python, R, Julia, C++, or C# based on specific development needs.
  7. Launch & Monitor AI: Concluding the process, we launch AI solutions and monitor for any post-launch errors, ensuring seamless functionality.

This structured approach reflects our commitment to delivering effective and tailored AI solutions.

Why Opt for ZenBit Tech for Tailored AI Software Development

  • Exceptional Developers

    ZenBit Tech boasts a team of experienced and high-skilled AI developers, with a cool portfolio ZenBit boasts years in delivering blockchain-based projects and rich expertise in software development.

  • Round-the-Clock Support

    Our dedicated team of project managers, designers, and developers is available 24/7 to assist with any concerns. Whether you want to add new features or enhance the project, feel free to reach out anytime, as our customer service representatives are ready to help around the clock.

  • Comprehensive Testing

    Ensuring our clients receive the finest AI solutions and an exceptional user experience is our priority. We rigorously assess the AI solution through meticulous multi-level testing, leaving no room for errors and ensuring a seamless performance.


  • What does artificial intelligence (AI) development include?

    AI development relies on algorithms and data.

    1. Developers design algorithms, which are step-by-step instructions or rules that guide the AI system in processing information and making decisions.
    2. Data plays a crucial role. AI systems require large sets of relevant and diverse data to train and improve their performance.

    As AI systems become more sophisticated, considerations like artificial intelligence pricing get crucial, involving the cost structures associated with developing, deploying, and maintaining AI solutions.

  • What are the key components and technologies used in AI development?

    AI development is based on algorithms and data. Its key technologies include machine learning, where algorithms improve through experience, and deep learning, which uses neural networks for complex decision-making. Natural Language Processing (NLP) facilitates human-computer interaction through language comprehension. Robotics integrates AI to control and automate physical systems. The development process also involves continuous testing, refining, and iteration.

    Balancing the AI cost with its benefits is essential for effective implementation and widespread adoption.

  • How to determine and estimate the cost of AI development?
    1. Define Project Scope
    2. Assess the data needs
    3. Choose appropriate algorithms
    4. Consider the computational power
    5. Estimate the time it takes to develop the AI system
    6. Hire skilled professionals
    7. Allocate resources for testing and validation
    8. Integration and Deployment
    9. Consider ongoing costs for maintaining, updating, etc.
    10. Allow your budget to accommodate unforeseen challenges.

    By evaluating these factors, you can develop a comprehensive estimate of the cost of AI development, helping you plan and allocate resources effectively.

  • What factors influence AI development costs?

    The cost of artificial intelligence is influenced by factors such as project complexity, data requirements, algorithm intricacy, computing resources, development timeframe, and skilled personnel expenses. The size and quality of datasets, chosen algorithms, computing infrastructure, and the need for specialized talent impact overall expenses. Testing, validation, integration, and ongoing maintenance are also important in the cost calculator. Plus, market trends, competition, and the evolving nature of AI technologies influence budget allocations, making AI development costs variable and project-specific.

  • Why is it important to realize the costs of AI development?

    Understanding the costs of AI development is crucial for effective project planning, resource allocation, and successful implementation. With a clear grasp of expenses, companies can avoid budget overruns, delays, and potential project failures. Accurate cost estimates aid in securing necessary financial resources and justify investments to stakeholders.

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    Dmitry Broshkov
    Dmitry Broshkov
    CEO of ZenBit Tech