Category: Business

AI in Business Intelligence: Reveal the Best Practices of Data-Driven Decisions

Posted on by Volodymyr Marynenko

In today’s fast-paced world, companies receive vast amounts of data every minute: clicks, views, transactions, interactions, and more. However, most businesses lack the resources or time to process all this information manually. That’s where Artificial Intelligence (AI) comes in.

According to Exploding Topics, 48% of businesses already use some form of AI to manage big volumes of data effectively. Moreover, when combined with Business Intelligence (BI), AI fundamentally enhances companies’ data analysis and decision-making processes.

At Devtorium, we have outstanding Data Science and Business Analytics experts who specialize in enhancing companies’ data processing. With extensive experience in providing AI-driven BI tools, our leading specialist, Olena Medvedieva – Head of the Data Science Department, has prepared a blog on the efficient application of AI in BI.

AI Modernizing BI Tools

AI Modernizing BI Tools

At its core, Business Intelligence is about transforming raw data into valuable insights that help businesses make better decisions. BI tools help companies track performance, monitor key metrics, and analyze past data to understand trends. But while BI has been great at showing what happened, AI is now stepping in to show why and what might happen next. So, how exactly does AI fit into the BI picture?

    1. Smarter Data Analysis

    Traditional BI tools focus on structured data, such as sales numbers or customer demographics. However, AI can analyze all types of data, including unstructured ones like emails, social media posts, or audio recordings. By examining a fuller picture of data, businesses can uncover hidden insights and make more informed decisions.

    2. Predicting the Future

    AI isn’t just good at analyzing what happened; it’s great at predicting what will happen next. Using machine learning, AI can examine past data to forecast trends, customer behavior, and potential risks. For example, a retailer could predict which products will be in high demand next month, helping avoid stock shortages or overstocking – ultimately saving time and money.

    3. Natural Language Processing (NLP)

    One of the most impressive aspects of AI in BI is its ability to interact with data in a more natural way. With Natural Language Processing (NLP), you can ask your BI system questions in plain language, just like you would ask a colleague. For example, you could ask, “What were the top-selling products last week?” and get a quick, clear response—no need to be an expert in data or learn complicated commands.

    4. Automating Insights

    AI can also identify and highlight essential insights. By continuously scanning data for trends or anomalies, it can alert you to unusual occurrences, such as a sudden drop in sales or a spike in customer complaints. These insights help businesses stay on top of critical real-time changes and react faster.

    5. Improved Data Visualization

    By recommending the best way to visualize data, AI makes it easier for businesses to see trends and patterns. Whether through bar charts, line graphs, or heat maps, AI ensures that presented data is in the most insightful and accessible way possible.

    The Strategic Advantages of AI in BI

    The Strategic Advantages of AI in BI

    Adding AI into the BI area drives businesses to an entirely new level. By doing so, companies benefit from various fields, empowering them to stay ahead in today’s data-reliant market. Here’s how:

    • Faster, Smarter Decisions by processing enormous amounts of data quicker and more accurately than doing that manually.
    • Cost Savings by automating tasks that traditionally require manual effort, such as data analysis and report generation. AI can free up employees to focus on more strategic tasks, ultimately saving money and boosting efficiency.
    • Scalability by scaling solutions as the business grows. It helps companies handle more extensive datasets and complex analyses, ensuring that data-driven decision-making remains possible even as the business expands.

    Challenges to Consider

    Of course, integrating AI with BI isn’t all smooth sailing. There are a few challenges businesses need to consider:

    • Data Quality: AI is only as good as its fed data. If the data is inaccurate, incomplete, or biased, the insights AI provides may not be reliable. Businesses need to ensure that their data is clean and high-quality.
    • Cost and Expertise: While AI-powered BI tools are becoming more accessible, they still require a significant investment. Not to mention, finding professionals who can integrate and manage these tools requires specialized skills.
    • Ethics and Privacy: As with any technology, AI raises ethical concerns, especially regarding data privacy. Businesses must be transparent about collecting, storing, and using data to avoid privacy violations or bias in their AI models.
    AI is the Perfect Fit for Business Intelligence

    Bottom line: Why AI is the Perfect Fit for Business Intelligence?

    Overthinking the future of AI in BI, it is predictable how manageable and robust working with data will become. Moreover, their combination will help businesses quickly uncover trends, predict future outcomes, and automate repetitive tasks, freeing time for more strategic thinking. With user-friendly AI tools, even those without technical backgrounds can gain valuable insights from data.

    To see how AI and BI tools transform your business in practice, book a free consultation with the Devtorium Data Science team!

    More on AI from Devtorium:

    Healthcare MVP Development: Top Mistakes to Avoid for Successful Product Launch

    Posted on by Volodymyr Marynenko

    A minimum viable product (MVP) is a product development approach that allows startups to realize their potential. This method has demonstrated excellent results in social media, marketplaces, and entertaining ventures (like Instagram, Amazon, or Spotify). Currently, one of the most profitable spheres of startuping is healthcare. According to Crunchbase, this industry still accounts for over 50% of U.S. Series A funding in 2024.

    However, developing an MVP healthcare product in today’s highly competitive market is no easy task. There are plenty of risk factors that can be easily forgotten or underestimated. Moreover, MVP development in this niche is particularly challenging due to regulatory requirements, data sensitivity, and scalability demands.

    Therefore, we at Devtorium, with hands-on experience in healthcare MVP development, want to share practical advice for minimizing those risks. This blog will outline critical mistakes and explain how to avoid them with the right strategies and expert advice.

    Mistake 1: Mishandling Healthcare Data

    Problem: Healthcare MVPs often manage enormous volumes of data like patient health records, diagnostic information, treatment histories, etc.

    Thus, improperly designed data systems can lead to severe problems. Your MVP can be limited in delivering actionable patient insights and predictive analytics. Moreover, failure to organize data effectively causes slow performance, duplication of effort, or even loss of critical information. Healthcare MVP must conform with the FHIR (Fast Healthcare Interoperability Resource) standard developed by HL7 (the Health Level 7 standards organization). This standard lets the exchange of healthcare e-data between different systems securely and privately.

    Teams without domain expertise may also underestimate data interoperability challenges like integrating with existing electronic health records (EHRs).

    Solution: Our experts recommend implementing FHIR-compliant encryption, as prioritizing this standard will ensure robust data protection while supporting seamless interoperability in healthcare systems. Additionally, you can try to involve data scientists in MVP development, as they can provide your system with tools like advanced analytics, predictive modeling, and personalized recommendations.

    Mistake 2: Neglecting Compliance Requirements

    Problem: Some startups underestimate the importance of adhering to regulatory frameworks, as they think they can address compliance after the MVP is live. They focus on building features and functionalities but often overlook the need to comply with regulations for handling sensitive data, such as personal health information (PHI). Failing to integrate compliance like HIPAA (Health Insurance Portability and Accountability Act), GDPR (General Data Protection Regulation), or similar ones from the start can lead to costly delays, fines, or product rejection. Regulations aren’t optional— they are foundational in healthcare MVPs.

    Solution: Firstly, you should integrate compliance early in MVP development, as retrofitting it into an existing product can be costly and inefficient. Secondly, it is better to maintain detailed records of how your MVP collects, processes, and stores data. Regulatory audits often require transparent documentation. Last, the most critical point is implementing secure storage, encryption protocols, and a controlled access system. Collaborating with a tech partner experienced in healthcare compliance can significantly reduce risks and ensure your MVP is ready for market.

    Mistake 3: Imbalance between Simplicity and Scalability

    Problem: The most challenging task while creating MVP is to find the right balance between a functional and a scalable foundation for the project. Typically, inexperienced companies either overload the MVP with too many features or focus solely on short-term goals without planning for future product expansion. These risks occur when the team does not focus on the main goals and their development. Both these issues cause high chances of failure due to poor user experience, bugs, and wasted time and money.

    Solution: To prevent these extremes, you should design the MVP simple enough to launch quickly but robust enough to accommodate future growth. Also, it would help if you avoided “scope creep” by identifying the MVP’s minimum viable goals. At the same time, you better work with a technical team experienced in designing scalable architectures such as cloud-based infrastructures. We advise using cloud-based infrastructures intended for healthcare, like AWS HealthLake or Microsoft Azure, to manage large-scale data.

    Mistake 4: Ignoring User Feedback, Testing, and Iteration

    Problem: Many startups underestimate the importance of testing and iteration in MVP development, believing that users will not mention bugs and technical issues since it’s “just an MVP.” They often launch their product without proper validation channels and treat the MVP as a one-time release rather than an iterative process. This mindset leads to poor first impressions, decreased user engagement, and missed opportunities. When teams fail to establish proper feedback mechanisms, they risk losing users permanently.

    Solution: Our experts advise implementing a comprehensive testing strategy before launch. It suggests establishing clear feedback channels such as in-app surveys, customer interviews, and email questionnaires to collect user insights systematically. Regular iteration based on real user insights is the key to creating a successful MVP that meets user needs.

    Mistake 5: Choosing the Wrong Development Team

    Problem: Building an MVP is a time-sensitive and resource-intensive process, especially in the healthcare industry, where compliance, scalability, and precision are critical. That’s why hiring an inexperienced or lacking domain expertise team is not a good idea, even though they propose low prices for complex development services. 

    Hiring the wrong team can lead to costly delays, sub-optimal results, and technical debt. While some businesses try to assemble teams through freelancer platforms, managing scattered individuals can result in miscommunication and fragmented development efforts. This risk is amplified for healthcare MVPs, as the lack of expertise in regulatory requirements like HIPAA or GDPR can jeopardize the project entirely.

    Solution: To ensure effective MVP development, partner with a specialized company that understands the healthcare sector. Look for a team with a proven track record of building compliant, scalable solutions for similar industries. Evaluate their portfolio to be certain of compatibility with your project’s goals. Working with experienced professionals gives you access to a full-cycle service that covers discovery, prototyping, design, development, and testing.

    Conclusion: How to Make a Successful MVP Launch

    Developing an MVP requires careful planning and expertise in the highly regulated healthcare industries. You can create a product that paves the way for long-term success by avoiding common pitfalls.

    Our team has deep domain expertise in MVP development for healthcare to deliver high-quality solutions. From compliance and scalability to data security and user-focused design, we’re here to guide you through every stage of the MVP process.

    Ready to take the first step toward building a successful MVP? Contact our team for a free consultation and receive personalized advice from our experts.

    AI Law Regulations in EU & US

    Posted on by Volodymyr Marynenko

    Every time new technologies enter our lives, we must become pioneers and adapt to the new rules of the game. AI is not an exception. This innovation has already made its way into every sphere, from entertainment to science. Moreover, there are countless ways to use AI in real-life business. However, AI cannot remain unregulated without specific frameworks and rules. If such a powerful tool appears in the wrong hands, it can be used for selfish or harmful purposes.

    The prospect of AI being used in deep fakes, fraud, and theft of personal data or intellectual property is not just concerning but an urgent issue. The Center for AI Crime reports a staggering 1,265% increase in phishing emails and a nearly 1,000% rise in credential phishing in the year following the launch of ChatGPT. This highlights the urgent need for AI regulation.

    In response, significant regions such as Europe and the US have started developing principles regulating AI to protect their citizens, companies, and institutions while maintaining technological development and investment. The regulations contain critical nuances that must be considered when developing or implementing AI technologies. In this blog, we will explore and compare European and American AI regulations.

    The EU AI Regulation: AI Act

    Regulation on a European approach for AI

    The AI Act by the European Union is the first global and comprehensive legal framework for AI regulation. Basically, it is a set of measures aimed at ensuring the safety of AI systems in Europe. The European Parliament approved the AI Act in March 2024, followed by the EU Council – in May 2024. Although the act will fully take effect 24 months after publication, several sections will become applicable in December 2024, primarily focusing on privacy protection.

    In general, this act is similar to the GDPR — the EU’s regulation on data privacy — in many respects. For example, both cover the same group of people — all residents within the EU. Moreover, even if a company or developer of an AI system is abroad, if their AI software is designed for the European market, they must comply with the AI Act. The regulation will also affect distributors of AI technologies in all 27 EU member states, regardless of where they are based.

    The risk-based approach of the AI Act is comparable to the GDPR’s. It divides AI systems into four risk categories:

    • The minimal (or no) risk category is not regulated by the act (e.g., AI spam filters).
    • Limited-risk AI systems must follow transparency obligations (e.g., users must be informed when interacting with AI chatbots).
    • High-risk AI systems are strictly regulated by the act (e.g., using AI systems to enhance critical infrastructure).
    • Unacceptable risk is prohibited (e.g., biometric categorization).

    Non-compliance with certain AI practices can result in fines of up to 35 million EUR or 7% of a company’s annual turnover.

    The US AI Regulation: Executive Order on AI

    Although the United States leads the world in AI investments (61% of total global funding for AI start-ups goes to US companies), its process for creating AI legislation is slower and more disorganized than the EU’s. There is no approved Congress policy on AI systems regulation in the US for now. However, the White House issued an Executive Order (EO) on Safe, Secure, and Trustworthy Artificial Intelligence in October 2023. It sets federal guidelines and strategies for fairness, transparency, and accountability for AI systems. As with the AI Act, the EO aims to balance AI innovation with responsible development. 

    The AI Executive Order also focuses on guiding federal agencies in implementing AI systems and outlines a series of time-bound tasks for execution. It directs federal agencies to develop responsible AI governance frameworks. The National Institute of Standards and Technology (NIST) leads this effort by setting technical standards through its AI Risk Management Framework (AI RMF). This framework will shape future guidelines while aligning with industry-specific regulations. Federal funding priorities further emphasize AI research and development (R&D) to advance these initiatives.

    The most important thing to mention about EO is that it does not have the same enforcement power as a law. Instead, EO should be viewed as a preparatory stage of AI regulation, and its recommendations should be gradually implemented if you plan to work in the US market. For example, any AI software development company should start conducting audits, assessments, and other practices to ensure their safe approach.

    Comparison Table

    Legal Force:

    The AI Act will become a binding law across all EU member states once 24 months pass. After that, mandatory compliance will be required from everyone providing AI systems in this region. In contrast, the US Executive Order has less legal force. It sets essential guidelines for federal agencies, but it lacks the binding legal authority of a law passed by Congress. The EO’s enforcement is limited to federal government activities and impacts the private sector less. Thus, even a change of president can provoke future revocation.

    Regulatory Approach:

    The AI Act applies to all AI systems, categorizing them  from unacceptable to minimal risk to ensure that every AI system across industries falls under specific regulations. The US OE focuses on sector-specific regulations, targeting high-impact industries like healthcare, finance, and defense. While this approach fosters innovation, it may lead to inconsistent risk management across sectors.

    Data Privacy:

    The AI Act uses practices from GDPR to enforce strict rules around data processing, privacy, and algorithm transparency. The US privacy regulations remain fragmented, with state-level laws such as the CCPA and BIPA applying at the state level but no federal AI-specific privacy law.

    Ethical Guidelines:

    The EU AI Act emphasizes ethical AI development, focusing on fairness, non-discrimination, and transparency. These principles are embedded within the legislation. The US Executive Order promotes similar values but through non-binding recommendations rather than legal mandates.

    Support for Innovation:

    The EU AI Act aims to balance strict regulation with promoting innovation, offering AI research and development incentives within an ethical framework. These actions help foster AI innovation while ensuring public safety. The US supports innovation through federal funding and AI research initiatives, but companies have more flexibility to self-regulate and innovate without the stringent compliance measures seen in the EU.

    Conclusion: Challenges of Current AI Regulations

    The EU and the US face global challenges in balancing AI regulation and innovation. The EU AI Act imposes numerous restrictions that limit the possibility of developing revolutionary AI software, while the US EO, although offering more flexibility and encouraging innovation, lacks comprehensive regulations. The evolving nature of AI technology makes it difficult for regulations to keep pace, and businesses must navigate complex compliance requirements across different regions. However, for developers working on projects, adhering to these regulations is crucial to avoid legal risks and ensure the ethical use of AI.

    At Devtorium, we help businesses navigate these challenges by ensuring compliance with the necessary AI regulations. Our team can guarantee that your AI solutions meet both EU and US standards, allowing you to focus on innovation. For more details, contact us today and let Devtorium’s experts guide your AI development toward full regulatory compliance.

    If you want to learn more about our other services, check out more articles on our website:

    Generative AI Comparison: Best AI Models Available in 2024

    Posted on by Volodymyr Marynenko

    AI is a revolutionary technology, and its rapid growth is why you need some generative AI comparison sources right now. This tech has spread and evolved so fast that it’s hard to understand exactly what the solutions available on the market are capable of. Despite having some similar functionality, generative AI tools differ quite a bit. So, read on to learn the best time to use each top AI model.

    Who Needs This Generative AI Comparison Guide?

    If you use the Internet today, you will benefit from reading this simple guide on AI model comparison. This technology is quickly spreading to different areas of our daily and, most of all, professional lives. Therefore, knowing which AI tool to use and when is key to staying ahead.

    There are numerous areas of business where  you can implement AI, so you will definitely find ways to use this technology to boost your outcomes.

    Today, the market provides a variety of large language models (LLMs). Each of them has different tools and capabilities. Some are best used for coding only, while others perform exceptionally well in creative tasks. As a result, it’s pretty confusing and complicated to pick the right AI tools for your purposes. That’s why Devtorium R&D experts prepared this short guide on four of the most effective LLMs and their best use cases.

    Comparison of Generative AI Tools: Benefits and Uses

    Generative AI comparison guide.

    ChatGPT

    ChatGPT stands for “Chat Generative Pretrained Transformer.” OpenAI developed this LLM and currently offers three models: GPT-3.5, GPT-4, and GPT-4o.

    • Chat GPT-3.5 is a free version that anyone can access. However, it has many limitations, like no image input or complex task processing.
    • Chat GPT-4 is a $20/month subscription version designed for professional use. The model has excellent contextual understanding and creative reasoning. Among its drawbacks is slower task processing speed due to model complexity.
    • Chat GPT-4o (or ChatGPT-4 Turbo) is a brand-new version of ChatGPT-4 that offers similar capabilities but is cost-efficient and speed-optimized. This tool has free and paid plans with varying limits. Also, among its inputs can be text, images, audio, and video. Even though GPT-4o has a bit worse context retention than Chat GPT-4, this model still balances exceptional outputs with processing speed.

    Best ChatGPT applications:

    • Cost-effective solution
      For budget-conscious projects, models like ChatGPT-4o offer a balance between performance and affordability.
    • Hard prompts
      Advanced versions like ChatGPT-4o would be effective if complex or nuanced responses are necessary. Moreover, according to the LMSYS Chatbot Arena Leaderboard, the best hard prompt performance out of 126 AI models shows ChatGPT-4o.
    • Longer queries
      ChatGPT excels at understanding context and coherence across extended conversations, making it ideal for in-depth discussions or multi-step tasks.
    • Versatile applications
      From creative writing to code generation, ChatGPT developed its available functions evenly.

    Claude

    Not a common name in most AI comparison guides, Claude is a family of AI language models developed by Anthropic. These LLMs focus on providing safe AI interactions. Claude 3 Haiku, Claude 3 Opus, and Claude 3.5 Sonnet are among the models currently available to general users.

    • Claude 3 Haiku has the highest response time of all Anthropic models. It’s ideal for concise prompts and fast tasks. It’s also more affordable compared to others. However, it has limited creative capabilities and contextual understanding. It’s best suited for mobile application chatbots and instant messaging.
    • Claude 3 Opus is a mid-range AI tool with moderately fast latency. It balances creativity and accuracy, offering strong contextual retention and versatility.
    • Claude 3.5 Sonnet is the first release in the forthcoming Claude 3.5 model family. It’s one of the most advanced Claude models at the moment. This model is outperforming competitors in different spheres. However, it meets the same problem as Chat GPT-4: slower workflow speed due to more complex processing for richer output. Claude 3.5 Sonnet is now free on Claude.ai, while Claude Pro and Team plan subscribers can access it with significantly higher rate limits.

    Best cases to use Claude:

    • Code generation
      Claude 3.5 Sonnet generates optimal, almost bug-free code across 20+ languages, optimizing for project-specific needs and best practices. Also, according to the LMSYS Leaderboard, Claude 3.5 Sonnet is the best coding and math task-solving AI today.
    • Visuals analysis
      Claude 3.5 Sonnet can analyze images, documents, and PDFs, extracting essential information for diverse tasks. It’s free with basic features, but paid plans offer enhanced capabilities and higher usage limits.
    • Ethical AI applications
      Every Anthropic’s model is built on nuanced AI principles, prioritizing safety. It also means that all responses Claude provides must adhere to them. Claude is forthright about its limitations and potential biases, promoting responsible AI use.
    • Complex decision-making
      Claude can handle intricate scenarios with multiple variables. Moreover, it is ideal for tasks that require deep contextual awareness.

    Meta LLaMA 

    LLaMA (Large Language Model Meta AI) is an open-source LLM developed by Meta. Its main feature is its small resource intensity, which enables researchers and developers to meet complex requests on smaller hardware. At the moment, Meta offers three models of LLaMA: LLaMA 2, LLaMA 3, and LLaMA 3.1.

    • LLaMA 2 is a free-to-use OSS model of AI. It is the first openly available LLM instruction-tuned for text. It’s also great for commercial use if you struggle with huge budgets. However, this model is a bit outdated, so you can find inexpensive alternatives that provide higher performance.
    • LLaMA 3 is the next generation with some significantly upgraded features. This model is multilingual and has high prompt understanding. Unfortunately, it delivers bad performance in reasoning and math.
    • LLaMA 3.1 is a recent model built on LLaMA 3. It has improved reasoning and coding capabilities. Also, LLaMA 3.1 is the largest openly available model right now. So, if you want the best free-to-use AI model, this one will be a top hit according to our AI comparison.

    When to use LLaMA:

    • Commercial applications
      This AI model is ideal for many business applications without additional costs.
    • Meta integration
      LLaMA can be easily integrated into Meta AI, Facebook, Instagram, and WhatsApp, providing advanced AI capabilities for content generation, customer interaction, and personalized user experiences.
    • Multimodal tasks
      The model offers robust support for diverse languages and media formats, making it a versatile tool for global and cross-platform applications.
    Comparison of generative AI models on the market

    Gemini

    Gemini is an AI model developed by Google DeepMind. It is positioning itself as a competitor to advanced LLMs like GPT-4. Four Gemini models made it to our I comparison guide: Gemini Ultra, Gemini Pro, Gemini Flash, and Gemini Nano.

    • Gemini 1.0 Ultra is Google’s largest model, designed for complex AI tasks. It offers maximum computational power for enterprise-level solutions and advanced AI research. This AI tool is great for advanced app integration.
    • According to ratings, Gemini 1.5 Pro is the best Google AI model. It excels in general performance across a wide range of tasks. Gemini Pro can process hard prompts and follow instructions almost perfectly, making it suitable for professional-grade tools and large-scale applications.
    • Gemini 1.5 Flash is a lightweight model of Gemini Pro designed for fast data analysis.
    • Gemini 1.0 Nano is the most powerful on-device model available. It is ideal for mobile apps, IoT devices, and edge computing with minimal resource usage.

    Top Gemini use cases:

    • Overall best app
      Currently, Gemini 1.5 Pro has the best results, outperforming all listed competitors.
    • Factual accuracy
      Google’s AI relies on enormous databases and searches, ensuring its output is reliable and trustworthy.
    • Gmail integration
      Using Gemini, you can enhance email management by providing smart reply suggestions, drafting assistance, and content generation directly within the platform.

    Bottom Line: Which Model Is Best in AI Tools Comparison?

    To sum it up, the current tech landscape offers a diverse range of AI solutions tailored to various business needs. From the advanced capabilities of ChatGPT and Gemini to the specialized performance of Claude and LLaMA models, each of these tools can help you.

    Therefore, the best model for your specific case is the one that has the most advanced capabilities in the niche your business requires. If you want to benefit from AI integration, contact our experts for a free consultation today. We’ll help you choose a suitable AI model and develop the best implementation to enhance your business. If you want to learn more about our strengths, be sure to check our Devtorium’s case studies and verified Clutch reviews from our customers.

    How to Use AI in Small Business: Ideas and Practical Applications

    Posted on by Volodymyr Marynenko

    At this point, using AI in small business has become a mandatory requirement. There is just no other way to gain a competitive advantage. The level of competition in every industry is skyrocketing, so you must cut your costs and optimize every possible process. This is precisely what AI can do for small businesses, and we’ll tell you how today.

    How many companies consider using AI in small business

    Using AI in Small Business: Practical Tips from Professionals

    Leveraging AI tools can be troublesome for many SMBs because they need help figuring out where to start. Devtorium offers a range of AI software development services, and our developers have expertise in implementing AI into various systems. In this post, they will demystify AI for small businesses, providing insights and examples of successful AI usage.

    Bear in mind, that the majority of businesses are either already using or consider implementing AI solutions already. Take a look at stats in the graphs to see what position your company matches currently.

    Let’s start with a few general tips to consider when using AI in small business:

    • Start small
      First, you should begin with only targeted AI applications that align with your business goals and resources. For example, if you have an e-commerce site, add a chatbot to enhance customer experience.
    • Data quality matters
      For AI to work accurately, you must be sure that training data is clean and relevant. It’s crucial for minimizing the risk of bias in AI outcomes.
    • Monitor your ROI
      Your BA must analyze all AI projects’ return on investment (ROI) to ensure they deliver value to your business.
    • Collaborate with experts
      Partner with AI specialists or consultants to navigate complex implementation challenges.
    Interest in using AI for small business

    Real-World Implementations of AI in Small Business

    Improving Customer Experience

    Adding an AI chatbot to your website or service is the best AI innovation to start with. This virtual assistant can solve many tasks, from answering users’ frequently asked questions to assisting with product recommendations based on their behavior. Moreover, chatbots can learn and adapt over time. Therefore, their accuracy and efficiency in handling customer queries will improve.

    Virtual assistants can cut the workload of your human support staff. In turn, they will have time to focus on more complex tasks. Besides, these AI solutions can gather valuable data on customer interactions. Use them as an analytics tool to learn about your audience and make better-targeted business decisions. For example, you can identify trends, understand customer needs, and improve your services overall.

    To start using such a chatbot, small businesses can try services like Dialogflow by that uses Google  Al. You can also try to make your own chatbot with LangChain. If you want to go to the next level, check out our case of what a voice bot can do.

    Supply Chain Management

    Some fantastic ways of using AI in small business that deals with logistics include:

    • Optimizing delivery routes optimization
    • Reducing transportation costs
    • Cutting down on delivery times
    • Increasing logistics efficiency

    Also, you can use AI to evaluate supplier performance and manage relationships, ensuring the best terms and reliability. AI-driven supply chain management systems leverage advanced algorithms to analyze vast amounts of data and make real-time decisions that enhance operational efficiency.

    AI can also enhance predictive maintenance in logistics. This is done by using data from IoT sensors to anticipate equipment failures and schedule proactive repairs. With this tech, you can minimize downtime and improve your business’s overall reliability.

    Moreover, AI-powered demand forecasting models help anticipate customer needs more accurately. Therefore, businesses can adjust production schedules and inventory levels accordingly. By optimizing these processes, AI contributes to cost reduction and enhances the agility of supply chain operations.

    Using AI for small businesss: Predictive analytics and security.

    Predictive Analytics

    One of the best ways to use AI in small business is implementing predictive analytics to analyze your past data and identify patterns. These tools enable you to forecast sales trends, which can make a crucial difference in achieving success.

    Efficient use of predictive analytics can help you come up with effective strategies and prevent rash decisions. Furthermore, predictive analytics can optimize inventory management by forecasting demand and caution about overstock or stockouts.

    In addition, these AI systems can analyze sales data to identify seasonal trends and customer behavior patterns. You can utilize tools like Salesforce Einstein Analytics to anticipate market shifts.

    Visual content

    You should consider using AI in small business marketing, especially if you don’t have a dedicated marketing team. Creating and optimizing visual content can be easy using tools like Midjourney or Photoshop’s integrated AI, creating and optimizing visual content can be easy.

    For example, some tools today can personalize marketing materials based on user data, creating tailored experiences that appeal more deeply to the target audience. In addition, using generative AI can save time, money, and effort.

    Integrating AI into visual content strategies helps businesses stay ahead of the competition by consistently delivering visually compelling content. These tools can streamline the design process by providing instant enhancements and creative ideas, allowing teams to focus on more strategic tasks.

    Cybersecurity

    One area where small businesses aren’t using enough AI is cybersecurity. You should definitely make this your priority, as data breaches are a major threat today. Implement AI-powered cybersecurity solutions to detect and mitigate potential threats in real-time. For instance, predictive threat intelligence enables AI to analyze patterns and trends in cyber attack data, forecasting where and how future attacks might occur. Using AI for small business in this particular sphere enables them to strengthen their defenses preemptively.

    On other levels, AI enhances email security by detecting phishing attempts and malware-laden messages. This will significantly reduce the risk of successful social engineering attacks. Additionally, AI assists in post-incident analysis, providing valuable insights to understand the nature and scope of breaches, and informing future prevention strategies. This cycle of learning and making changes based on new data ensures that AI-powered cybersecurity solutions remain effective against an ever-changing threat landscape. 

    Conclusion: how to best start using AI in small business.

    Bottom Line: How to Use AI in Small Business to Get Top Value for Money

    To sum it up, small businesses can and should use AI systems to automate processes, make data-driven decisions, and achieve desirable growth. As AI continues to evolve and become more accessible, embracing this technology will be essential for staying ahead of the curve. However, it is challenging to adopt AI for your needs without technical expertise and business analysis. If you want to get maximum benefit from any AI tools or even customize some of them to fit your business needs, set up a free consultation with our experts today.

    What AI Cannot Do: AI Limitations and Risks

    Posted on by Volodymyr Marynenko

    Looking at some articles right now, one could think that AI is omnipotent. However, it’s essential to remember that AI limitations exist, and there are many. Therefore, you should not expect it to be a universal cure for all problems. Unfortunately, it’s still brand-new technology, and its functionality has to be improved.

    There are some incredible things you can achieve using AI. It’s also true that it can help your business save money by automating multiple processes and offering valuable analytics. However, some businesses take risks and apply AI in every situation. Such reckless use of tech can badly damage your business security and income.

    According to the AI Incident Database, the number of  AI misuse incidents in 2023 increased by 32.3% compared to the previous year. Nowadays, businesses must be realistic when considering the pros and cons of implementing AI. Devtorium Business Analysis and Information Security departments have the expertise to forecast probable risks caused by AI or other digital systems. In this blog post, our specialists will outline AI limitations and risks of implementing it without a system of fail-safes. 

    AI Limitations and Risks by Category

    What AI cannot do: AI limitations track back to the quality of data

    Data Dependency

    Data is the main resource on which any AI system runs. Algorithms train on the provided data. Therefore, AI heavily relies on data quality, bias, and availability, which can impact performance and decision-making.

    AI limitations caused by data:

    • Creativity
      While AI is good at generating content based on existing data, it struggles with original or innovative thinking.
    • Flexibility
      AI has limitations in adapting to new or unexpected situations outside its training data.
    • Bias
      Data bias can occur at various stages of the AI lifecycle. However, bias often originates from the data used to train and test the models.

    Contextual Misunderstanding

    What AI cannot do is understand the context. At least, this isn’t possible with the current level of technology development. AI’s lack of contextual understanding refers to its limits in interpreting information. In other words, AI can fail to realize societal context or grasp the subtleties of nuance. 

    AI limitations caused by context:

    • Natural Language Processing (NLP)
      While working on NLP tasks, like text analysis or translation, AI may have difficulty understanding language nuances such as idioms, slang, and dialects.
    • Visual recognition
      AI algorithms can fail to recognize objects within their broader context in computer vision tasks.
    • Social interactions
      AI-driven chatbots may struggle to catch the nuances of human conversation, including tone, sarcasm, or implied meanings. If you want to learn more about the capabilities of an AI-powered voice bot, click here.

    Ethical Concerns

    AI limitations is ethics are impossible to fathom because this technology doesn’t operate in a context that can be governed by ethics. Therefore, programming AI algorithms that could make ethical decisions is nearly impossible. The machine struggles to replicate feelings and emotions. It cannot make moral judgments in the same way humans can. 

    AI limitations caused by ethics:

    • Lack of empathy
      AI lacks emotional intelligence and cannot empathize with human emotions. Therefore, as an example, it cannot prioritize emotional well-being as a factor.
    • Cultural contexts
      AI systems may struggle to understand human cultural diversity. This can lead to biased or culturally insensitive outcomes, like stereotypes. As a result, implementing AI in some areas might work to reinforce existing inequalities.
    What is the black box problem and the AI limitations it imposes

    The Black Box Problem

    The Black Box Problem refers to the opacity of AI decision-making processes. AI algorithms are so sophisticated that it is hard to realize how they arrive at their conclusions. Therefore, a human might not be able to trust them completely. As a result, implementing AI in any position where the machine can make decisions that impact human life becomes a huge risk.

    AI limitations caused by transparency:

    • Error correction
      When AI systems make errors or produce unexpected outcomes, understanding why those errors occur is crucial. However, without a clear view of the internal workings of black-box AI models, diagnosing errors becomes much more difficult.
    • Trust
      Users may find it challenging to rely on AI when they cannot understand how systems make decisions. The black box problem can be particularly concerning for critical applications such as healthcare or criminal justice.

    Privacy and Security

    As AI cannot function without data, concerns arise regarding collecting, storing, and using personal data. AI technologies also introduce new cybersecurity risks. Malicious actors may exploit vulnerabilities in AI systems to launch attacks, which presents new threats to financial systems, critical infrastructure, and national security.

    AI limitations in the security field:

    • Tracking
      AI-powered surveillance technologies, such as facial recognition and biometric systems, threaten privacy by enabling constant monitoring and tracking of individuals without their consent.
    • Malicious use
      AI technologies can be leveraged for malicious purposes, including generating convincing deepfake videos, launching sophisticated phishing attacks, and automating cyberattacks.
    • Personal data
      AI systems may analyze and process personal data without adequate safeguards. This could lead to unauthorized access, identity theft, financial fraud, and other cases of data misuse.

    Bottom Line: How to Avoid Reckless Risks and AI Limitations?

    It’s impossible to avoid risks and AI limitations entirely with the current level of technology. Therefore, it’s imperative to address them responsibly to maximize the benefits of AI implementation. Devtorium professionals are always ready to help you understand risks and develop efficient, safe, and secure AI applications for your business. Contact our team for a free consultation on how to use AI to your best advantage.

    To learn more about the Devtorium Team and the multiple capabilities of AI, check out our other articles:

    Devtorium UI/UX Design Services: What We Can Do for You

    Posted on by Volodymyr Marynenko

    Surprisingly, the majority of people have very little idea of what exactly is included in the UI/UX design services they purchase from specialized providers like Devtorium. Of course, in the end, you get the design of the app or other materials you’ve requested. However, this type of service is much more expansive and covers many processes, from market research to branding.

    Today, we’d like to explain what’s included in a comprehensive design package using Devtorium UI/UX design services as an example. From the post below, you’ll learn what UI/UX and graphic designers can do for you and how you can use their services to help your business at any stage of development.

    Devtorium UI/UX Design Services: How We Create Web Designs

    Our designers start with research to create a stunning, visually appealing, user-friendly design. In fact, the stage during which the UI/UX designer creates the visuals usually takes less time than preparation. The quality of work you put in during the research and planning stages determines whether your product can deliver a superb customer experience.

    No one can argue that design affects user retention. Therefore, it’s one of the crucial success factors in our world of information overload. In order to deliver outstanding UI/UX design services, the Devtorium team takes the following steps.

    How Devtorium UI/UX design services work.

    Digital and website discovery (General User needs research)

    Our team starts the design process by conducting discovery sessions. At this time, we gather requirements and brainstorm ideas to understand the underlying purpose behind your digital goals. These sessions allow us to clearly outline the client’s needs and help align our strategies with your objectives.

    During this stage, we perform:

    • Competitor research
    • Field research
    • User personas and user stories study

    Digital and website strategy (Information Architecture)

    We start designing solutions once we thoroughly understand the client’s goals and challenges. At this stage of Devtorium’s UI/UX design services, our team will create wireframes and customer journey maps. This way, we can define the high-level structure of screen layouts, flow, behavior, and organization. These outputs visually represent our proposed solutions and help us envision how the identified problems can be addressed effectively.

    Our primary goal is to lay out content and functionality on each page strategically. We aim to maximize usability and user experience. To achieve this, we first build informational architecture:

    • Organise, structure, and label content, functions, and features
    • Choose between different design patterns for content layout
    • Use design patterns for content
    • Map out website and content 
    • Plan site navigation

    After the architecture is complete, we create wireframes that the client can effectively use when attracting investors.

    How Devtorium UI/UX designers work.

    Digital and website design development (User interface prototyping)

    With the website architecture complete, we can provide the rest of the innovative UI/UX design services and branding package. Depending on the client’s requirements, we can build a visual brand style from scratch or use their existing one. During this stage, we use tools like style tiles, mood boards, and prototyping to facilitate the process.

    Devtorium’s design services also include graphic design, which covers the creation of:

    • Brand and identity
    • Logo
    • Marketing collateral

    When working within the premise of our UI/UX design services, we can also leverage video and photos to enhance the website’s reach and engagement.

    Why invest in UI/UX design services from Devtorium.

    Why It Pays to Invest in Creative UI/UX Design Services

    We live in an era where everything is lightning fast, and you only have one chance to make an impression. Your product can be extraordinary and offer hundreds of solid benefits. However, if you can’t capture the client’s attention enough to slow down and learn about it, you’ll lose them.

    According to research published in the Behaviour and Information Technology Journal, you have only 0.05 seconds to make a favorable first impression. 50 milliseconds is all it takes to form an impression in the brain of a modern information-overloaded person. If that impression isn’t enough to capture their interest to pursue further study of your product, your chances of conversion are slim.

    That’s how important great design is, and if you want people to keep using your products, you must provide a stellar user experience. It really is that simple today. Therefore, above all else, you must never skimp on making your product as user-friendly, intuitive, and attractive as possible. If you want to make your product that way, contact us for a free consultation!

    If you are interested in more design topics, check out some of our other posts:

    How to Hire an Offshore Outsourcing Software Development Company

    Posted on by Volodymyr Marynenko

    Outsourcing software development offers a range of benefits to businesses of any size. The main advantage of this method is flexibility as outsourcing gives you access to a huge pool of talent. However, as much as it could help you, entrusting your product development to offshore specialists could also cause problems. The secret to success here is to hire a reliable outsourcing development company you can trust. This guide will help you with this by pointing out the most important factors to consider when choosing this service.

    Benefits of outsourcing software development.

    Advantages of Outsourcing Software Development

    Before we get into the ‘how’, you need to understand whether outsourcing is the right choice for your business in general. An in-house team means you have more control of the workflow at every level. However, building your own team is guaranteed to be more expensive.

    Meanwhile, outsourcing offers the following benefits:

    • Access to versatile tech talent
      When outsourcing software development you have access to all talent worldwide. Therefore, you can definitely find the exact combination of skills and tech expertise required to build your ideal product. For example, you can build an AI development team containing experts who specialize in AI training combined with expert developers who can build the system to their specifications.
    • Shorter time-to-market
      As you aren’t limited in tech expertise and don’t need to spend time recruiting and talent on your own, the product development journey will be shorter. Even if you need to recruit additional experts during the development process, the Devtorium IT recruiting service will do this for you. Therefore, you get to release your product faster and with minimal disruptions.
    • Easy scalability
      Having complete control of an in-house team also reduces its flexibility for scaling. However, when you are outsourcing software development, scaling won’t be an issue. Note that this is true both for up and downscaling. The size of your team will always correspond to your current needs and budget.
    • Quick team expansion
      Note that you don’t have to outsource the entire development project. In fact, you can often achieve better results by choosing IT outstaffing services. In this case, you will enhance your in-house team with additional tech expertise by recruiting offshore specialists. This is a great option for scalability and increasing your product functionality by hiring experts in highly specific areas.
    Tips on how to find an offshore software development company.

    How to Hire an Outsourcing Software Development Company: Step-by-Step

    1. Outline your requirements
      First of all, you need to have a clear idea of what you want to achieve with your product. In order to choose an outsourcing software development company you need to understand what sort of technical expertise you require. Note that you don’t have to create a complete plan of technical features for the product. However, it will be best to research your prospective competitors and make a list of features you want to have. This way, you will be able to narrow down the pool of outsourcing candidates. For example, you can look for someone with expertise in fintech development, or creating insurance platforms, etc.
    2. Research offshore outsourcing companies
      You can use reputable platforms, such as Clutch, to collect information about various offshore outsourcing companies. A reliable provider will have all the essential information on their website. There you can learn about the services they offer and take a look at the case studies portfolio to get some idea of the company’s expertise.
    3. Conduct an interview and get a proposal
      The next step is to contact the company and set up a meeting where you can discuss your project. You can arrange a free meeting with the Devtorium team anytime. During this meeting, we will collect your requirements and talk about details in order to understand how we can bring your ideas to life. Then, we will provide you with some estimates and a proposal. When ‘shopping’ for a 
    4. Start collaboration with the outsourcing software development company
      Once we settle on the proposal, we can start collaborating to meet your goals and deadlines. Devtorium Project Managers will establish the lines of communication and set up the workflow to ensure that the project stays within the budget and delivery times outlined in the contract.
    Best countries for outsourcing software development.

    Best Destinations for IT Outsourcing Today

    The first task that lies before you when looking for an outsourcing software development company is to choose a country. This shouldn’t be too difficult as there are reports that allow you to understand where exactly the IT outsourcing industry is the strongest. Moreover, you can find out average rates and see which destinations offer the best cost-to-value ratio for the client.

    • Ukraine
      Despite the war currently going on in the country, Ukraine remains the top IT outsourcing destination in Eastern Europe. The revenue generated by this industry has been steadily growing over the last decade and russia’s invasion didn’t impede this growth. According to Statista, the IT outsourcing industry is set to generate $1.7 billion in revenue in 2023 and double that within the next five years.
    • Poland
      Poland has the largest workforce of development professionals in Europe (about 500 000). About 40% of these professionals work in the IT outsourcing industry. Polish software development vendors provide highly skilled labor at a reasonable rate.
    • India
      India is one of the most popular software development outsourcing destinations due to the affordability and abundance of developers. The country has a huge pool of STEM graduates with about 2.5 million added every year.
    • Brazil
      Brazil is the top IT outsourcing destination in Latin America. It’s particularly appealing to US businesses because there are very few issues with time zones. The country heavily supports the IT outsourcing industry through favorable legislation and promotion of technical professions within its education system.

    Hiring an outsourcing software development company can be a game-changer for your business. So, don’t hesitate, and take the first step right now!

    What Is the Best Website Building Platform for Small Business?

    Posted on by Volodymyr Marynenko

    The biggest challenge in choosing the best website building platform for small business today is that there are just too many of them. No doubt, when you visit the websites of different builders, you’ll see claims that they are the best and an impressive list of features used to prove it. Indeed, the truth of the matter is that many of these platforms are excellent. So, a business owner who is not an experienced tech professional working with websites might get confused fast.

    Today, we’d like to bring some clarity to this issue. Devtorium has built dozens of websites for various industries, ranging from travel to eCommerce to derivatives trading. This experience gives our developers a perspective that enables them to help every client choose a website building platform best suited to their unique needs.

    Below is a list compiled by our web development experts who share their top 5 website builders. These platforms are flexible and affordable, which makes them a great fit for small businesses.

    Best website building platform for small business: WordPress, WIX, Shopify, Bubble, Webflow.

    Best Website Building Platform for Small Business: Top 5

    WordPress (+ WooCommerce)

    WordPress is the number one website-building platform today. Over 43% of all websites on the internet run on WP. Despite the complex customization system, WordPress is the most flexible website builder you can find. If you wish to be in charge of the site and want to add unique functionalities and features, this is the choice for you. In fact, the Devtorium website is built on WordPress, so you can see exactly what our developers can do with this platform.

    Moreover, small businesses specializing in online sales can easily create a WordPress store using a specialized plugin, WooCommerce. It’s one of the best eCommerce platforms today, and it allows you to run a store easily.

    WordPress benefits:

    • WP is a powerful content management system (CMS) that is free to use. You must pay only for a hosting company and domain names.
    • WordPress is an open-source platform. Therefore, you can create a site with unique functionalities even with a small budget.
    • This platform has a vast library of add-ons and plugins (over 60,000). Having unlimited access to various extensions (free and premium) makes this builder the most flexible for adding features and designs.
    • There are thousands of themes and templates (free and premium). Therefore, you can create a beautiful site even without hiring a UI/UX designer.

    AI capabilities:

    WordPress offers multiple AI plugins that can diversify and boost website performance. They can perform various functions, including content creation, virtual assistance, security, and more.

    Bubble

    Bubble is our favorite no-code platform. Users created 2.3M+ apps on it, and the platform raised $10.3 billion in funding. Bubble has a robust and, most importantly, scalable infrastructure. Therefore, it’s perfect for entrepreneurs building MVPs and also serves as a great website building platform for small business.

    Bubble benefits:

    • Bubble.io is one of the most scalable no-code platforms. It’s easy to update and maintain your Bubble website. 
    • The drag-and-drop design saves you time and money. You can design custom web apps from scratch without the limitations of preset templates. 
    • The platform handles hosting, so there are no hard limits on the number of users or data storage.
    • Bubble web development is compatible with all browsers and operating systems.

    AI capabilities:

    You can integrate AI in Bubble.io and optimize the website how way you want. It’s compatible with top trending technologies, including OpenAI and ChatGPT.

    Webflow

    Webflow is a no-code development platform that’s already used by 200,000+ organizations and businesses. Moreover, Webflow highly customizable. This website building platform for small business is a good option for design-oriented customers who wish to style the site precisely the way they want.

    Webflow benefits:

    • Due to advanced design features, you can create complex rich animations, parallax scrolling, and a variety of micro-interactions. 
    • Webflow comes with a built-in Content Management System (CMS). Therefore, you can effectively manage and modify all your content with this tool.
    • The platform offers an extensive list of SEO tools and optimization options.
    • Webflow has a huge library of integrations, including app integration and automation, content marketing solutions, analytics, and targeting tools.

    AI capability:

    Webflow was planning to develop an integrated AI feature that would assist platform users. However, as of now, they only allow for the integration of third-party AI tools. You can learn more about Webflow’s plans for AI development from their blog.

    Tips for choosing the best website building platform.

    Shopify

    Shopify is a website building platform for small business that specializes in online sales. As eCommerce goes, it’s hard to find a more comprehensive solution. Devtorium developers worked with Shopify extensively and they are very happy with the platform’s functionality, stability, and security. This all-in-one platform powers 10% of total US eCommerce sites. As Shopify offers unlimited storage and no product limit, you can scale from small to big online stores. This website builder works best for businesses that want to launch an online store really fast.

    Shopify benefits:

    • The platform’s advanced functionality enables you to manage your online store easily. Shopify offers everything from marketing and payment tools to secure transactions and shipping options support.
    • You can use Shopify to sell online or in-person. The platform supports multiple outlets, including web, mobile, social media, online marketplaces, pop-ups, in-person events, retail locations, and brick-and-mortar stores.
    • Shopify is completely cloud-based and hosted. Therefore, you don’t have to worry about issues like web hosting, security, caching, etc.
    • Shopify has a 24/7 support team. It’s one of the few eCommerce platforms offering 24-hour customer service via email, live chat, and phone.

    AI capabilities:

    Shopify recently introduced a new AI tool called Shopify Magic. This proprietary solution helps users generate product descriptions for their shops. However, bear in mind that Shopify Magic’s suggestions may not be 100% on target. It’s a common weakness of all AI content generators.

    Wix

    Wix is a website building platform powering over 10.8 million sites. It has quite a few limitations in site management and design. However, this platform is well-suited for small businesses, consultants, bloggers, and entrepreneurs.

    Wix benefits:

    • Wix provides access to its own web hosting and domain names (free and paid).
    • There is a built-in SEO tool. Therefore, you can improve the site’s ranking effectively.
    • Wix considers website safety and security. For example, all their websites have an SSL certificate and are automatically backed up.
    • Wix offers 24/7 customer support services for all paid plans.

    AI capabilities:

    Wix has artificial design intelligence (Wix ADI) that can assist you in designing a beautiful website. However, this feature is only available for some types of projects (portfolios, yoga sites, etc.). If your project fits the AI’s requirements, it will create images and content. In addition, it will connect your social media, create a contact form, or pick a suitable design for your audience.

    Bottom Line: How to Pick the Best Website Building Platform?

    The process of choosing the best platform and building a website using it can be rather straightforward and easy. As a business owner, you just need to take the following steps:

    1. Make a list of the things you want your website to have and do. It will be easier if you do some extra research. For example, you can look at what your competitors’ sites are like. Also, you can add some ideas of the things you enjoyed on various pages while browsing the Internet.
    2. Contact the Devtorium team and arrange a free consultation at a time convenient for you.
    3. Share your list of requirements with us. Devtorium developers, analysts, and designers will quickly come up with suggestions and estimates. Next, we’ll provide an offer with different options that will highlight different perks of specific platforms that you can benefit from while staying within budget.
    4. Pick the offer that you like most, and our dev team will do the rest. You’ll have your website up and running in no time!

    How to Use Generative AI in Real-Life Business

    Posted on by Volodymyr Marynenko

    Generative AI is the buzzword of today. Everyone must have tried using at least one of the available solutions by now. ChatGPT alone has over 100 million users, and Midjourney isn’t too far behind. However, if you are a business owner looking to boost your services or workflow with tech innovation, your main question should be, ‘how to use generative AI in my business?’

    We are here to answer this question today. Devtorium offers a wide range of AI software development services, and our solution engineers have expertise with different types of AI frameworks. According to our experts, the only limitation when implementing AI into business is your creativity. Generative AI uses are indeed quite specific. However, using your imagination, you can make these instruments help with many everyday tasks.

    How to use generative AI for business.

    Step 1: Choose the Type of Generative AI Applications You Need

    Generative AI is a technology that trains using specific datasets, and, based on that training, it learns to generate various types of other datasets. Simply put, developers input massive databases that the AI processes and learns. Then, it creates different types of content based on the information it consumed.

    It’s also important to note that generative AI applications are today’s top tech trend. They’ve been on a steep rise since 2020 and, according to Gartner, reached the ‘Peak of Inflated Expectations’ in 2022. ChatGPT made this technology truly mainstream as it introduced AI to the mass market. Every person with a computer and internet access could use ChatGPT and get some answers from it. This showed people without connections to software development that AI technology is real and that generative AI uses are endless.

    The quick popularization of other AI tools pushed this technology forward faster because, as mentioned before, it learns when it works with data. Therefore, AI improves with every task it completes.

    When you consider how to use generative AI in your business, you need to start by researching the types of these tools. The most basic way to separate generative AI into types is by the kind of output content they produce. However, remember that some AI solutions are highly complex and can generate various content.

    • Text generation
    • Code generation
    • Video generation
    • Image generation
    • Sound generation
    • Research and explanation

    The last type refers to generative AI uses in research where such tools can process, simplify, and summarize complex texts. For example, you can use Elicit or Enago Read for these purposes. Other popular generative AI apps are ChatGPT, DALL-E, Bard, DALL-E, and Midjourney, which create different content based on user-given prompts or dialogue.

    Generative AI tools and their types.

    Step 2: Generative AI Application in Real-Life Situations

    Types of these tools seemingly make it obvious how to use generative AI. However, are you sure you’ve thought of all the ways this can be implemented in business?

    Here’s a list of some ideas for you to consider:

    • Text content creation can be used to make marketing materials, blog posts, advertisements, and even work emails for some situations. For example, if you don’t have a talent for creative writing, generative AI tools like ChatGPT can help you write proposals, congratulatory emails, and even feedback.
    • You can use generative AI to edit texts as well. The tool can help you improve grammar and style or make some translations. However, it’s admittedly not perfect in translations, so be careful with how you use that output.
    • When you need to make guides or other helpful documentation for your customers, you can use AI generators to simplify technical texts. So, you’ll create posts and papers that are easy even for non-professionals to understand.
    • Image and video generators can also be used in marketing. You can create everything from a brand logo to a complete set of marketing materials used in ads, banners, blog posts, and even website designs.
    • In other generative AI uses, 3D models can be implemented in manufacturing and used to aid business planning.
    • Architects can use generative AI applications to create and analyze existing designs.
    • If needed, you can use Midjourney and similar tools to create illustrations for your content.
    • Sound generation can be applied to create tunes for social media or for your personal artwork, as well as advertisements and presentations.
    • Text generators, like GPT-4, are part of responsive chatbots and other automated reply solutions. For example, you can program these tools to send automatic email replies.
    • Sound generation solutions can work with speech in different ways. One of them is speech-to-text, which will allow you to create records of lectures or important meetings.
    AI applications in customer service.

    AI Uses for Onboarding and Customer Service

    Currently, the main areas of generative AI applications are employee onboarding and customer service. That’s because a chatbot is the most popular AI instrument used in business today. However, generative AI uses allow you to expand on those implementations, further boosting their efficiency.

    Some ideas on how to use generative AI in onboarding and customer service include:

    • Creating educational courses using video and speech generation technologies.
    • Personalizing customer journey experiences.
    • Creating a support service for navigating the company or website.
    • Creating a service to collect and process complaints, using AI capabilities to allow the tool to resolve some common issues.
    • Developing a content recommendation system for customers to help boost sales.
    How to use generative AI to boost your business.

    Bottom Line: Who Needs Generative AI Apps Today?

    This is only a short list of the most basic AI uses one can come up with today. If you are serious about improving your business’ productivity with this technology, you should book a free consultation and discuss your case with our AI solution developers.

    AI applications are so versatile that they can benefit any business today. All you need is a bit of creativity and a lot of technical expertise. We have both and can help you achieve the best results with custom AI solution development services. These can be tailored to your budget and needs. Most importantly, they can grow with your business, offering continuous improvement and optimization.

    We are a team of 200+ qualified software engineers, business analysts, data scientists, project managers, and UI/UX designers. All our professionals hold specialized certifications in their niches and have expertise in complex projects for a variety of industries.

      Contact Us

      sales@devtorium.com

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