June 21, 2024 • 484 Views • 16 min read
Tetiana Stoyko
CTO & Co-Founder
Integrating AI into business is a new trend in the IT industry. The emergence of various open-source AI solutions like ChatGPT and MidJourney started an AI revolution, by showing everyone the capabilities of such software and possible artificial intelligence role in business.
To cut a long story short, modern users already have advanced experience in working with various AI solutions. Besides unlimited access to open-source AI models like chatbots, many businesses can also use custom software development service to adjust and personalize artificial intelligence integration.
As a result, artificial intelligence has turned from advanced unknown technology from futuristic books to a new routine reality in less than 2 years. Still, many business owners hesitate and are not sure about integrating AI into business.
The best way to make the right decision is to analyze a few examples of artificial intelligence in business, and the challenges of artificial intelligence in business today.
Let’s start with the basics. Ask yourself: What do you know about Artificial Intelligence and Machine Learning?
To cut a long story short, Artificial intelligence is a complex software solution, designed to identify patterns and various correlations. Based on this feature, AI is capable of learning new information and taking its own actions to succeed and achieve certain goals. The process of AI training and learning is called Machine Learning.
In other words, implementing artificial intelligence allows the automation of various tasks, by letting AI make its decisions while performing them.
One of the most important advantages of any AI integration - is flexibility. Most AI business solutions are industry-agnostic: they can be trained to perform any task. In such cases, the only limitation, related to AI efficiency - is its training and access to requested data.
So, when implementing artificial intelligence in business, remember a simple rule: the more data AI has - the better results it shows. Frankly, providing AI models with enough data is one of the hardest tasks in terms of machine learning.
Before answering how to integrate AI into your business, we also have to discuss AI business opportunities, available today.
Artificial intelligence integration is a great way to improve and automate numerous business processes. Starting with business analysis and better customer experience, and ending with using AI to enhance business operations, which require time and are resource-intensive.
Frankly, one of the most challenging steps of integrating AI into business is to define the goals, you want to achieve, and find AI solutions, capable of doing so.
For instance, many examples of artificial intelligence in business are designed to achieve content personalization and create a seamless customer experience while using business services or software.
The main ways of using artificial intelligence technologies in business today:
Nevertheless, the abovementioned is not the final list of possible advantages and benefits of integrating AI into business. Still, the only evident reason for using AI to enhance business operations is that it works.
When you think about how to implement AI in your business, you have to complete a few previous steps.
As was mentioned before, there are numerous AI-driven tools, which can be integrated into your business to perform various tasks. However, before you implement AI in business, you must define which artificial intelligence integration will benefit you the most.
So, the first and most important step before integrating artificial intelligence in business operations is to define your needs and goals.
At this stage, you have to participate in the project's discovery phase, set precise tasks, and define what you want to achieve by AI implementation in business.
For instance, it can be a conversational AI for customer support services, designed to improve your customer-oriented services. Or, maybe, you are looking for AI business process automation, capable of streamlining various calculations and data processing like AI sales forecasting software.
To cut a long story short, before you implement AI in business, you have to define why and what you are doing it for. It can be just a general conception like “I am looking for AI, which can talk to my customers”. Still, to make it even better, try to theorize and explain in detail. For illustration, “I am looking for an AI, capable of generating human-like responses to my customer’s questions in under a second”.
In the first case, you can choose whatever chatbot or similar software solution, which eventually can not meet your expectations. In the second scenario, you and your team will have a clear understanding of what you are looking for, and have at least approximate KPIs, features, and performance metrics:
“Human-like responses” means, that you require AI with Natural Language Processing (NLP) capabilities, “In under a second” - it must have great performance results, which can be tested
The next step in integrating AI into business is to find a team of dedicated developers, familiar with such technologies. It is preferred to choose a team with proven experience, which can be found in case studies on its website.
Despite the variety of artificial intelligence integration, and multiple APIs, offered as a service, it is better to find a team, capable of implementing artificial intelligence and adjusting it to your needs.
Don’t forget: embedding AI into business processes is a flexible process, which can be additionally trained or adjusted to meet your expectations and perform tasks even better. However, to make it right - you developers must have enough experience in working with such technologies.
So, one of the best ways to integrate AI for business development is to find a dedicated development team.
Finally, before AI implementation in business, you must find the most suited tech stack.
Integrating AI into business is a simple task: most AI business solutions are distributed as SaaS and via API. So, all you need to do is to integrate API.
Nevertheless, to achieve better results in AI business process automation, it is necessary to adjust it to your needs. To correctly adjust and set up your AI business automation, you need:
For instance, if you are willing to use AI for Big Data analytics, you should consider Python-based solutions. Some other purposes might require React or other programming languages and frameworks. So, the best way to choose the correct tech stack - is to ask your developers for advice.
After all the previous steps, you can start AI implementation in business.
Frankly, it is the easiest step, which requires some experience and skills. Yet, after implementing artificial intelligence, don’t forget to adjust it.
Modifying and adjusting the AI implementation in business varies in time and resources, depending on the complexity of desired results and operations, it must perform.
For a better illustration, let’s consider examples of artificial intelligence in business, developed by Incora.
VoiceOrder.ai is one of our recent projects, related to working with artificial intelligence integrations.
This mobile application is designed to find discounts and other user-oriented deals in various restaurants. It involves AI-driven algorithms to personalize offers and deals to the customers, who are willing to order food delivery.
Apart from that, the mobile app uses AI voice technology as a way of user interaction. Built-in artificial intelligence integration is capable of recognizing human voice and transcript it into commands for further action.
As a result, our team used the full potential of AI business automation, which offers a few AI options simultaneously.
BlackBird.ai is a great example of FinTech AI implementation in business.
To cut a long story short, BlackBird.ai is driven by unique and sophisticated algorithms, which help with risk assessment and fraud detection. One of the main requirements of this project was enabling the possibility of estimating the credibility of data and various articles.
BlackBird users are offered credibility ratings and tags like “unreliable”, “suspect”, “undecided”, etc. So, they still can see articles and make their own decision on whether to trust the content or not. Therefore, app users are more aware of potential misinformation or fake content, as well as potential mistakes in the text.
Another case involving AI in business processes is developing conversational AI for customer support.
According to Forbes, 73% of businesses use AI chatbots. This means, that AI business process automation in certain fields like customer experience and support become rather a must-have feature than an extra option. At least, if you want to stay competitive in the market.
So, we were involved in embedding AI into business processes, related to customer support and satisfaction services. As a result, using artificial intelligence integration helped to upscale the service quality, and save costs by redirecting customer support specialists to more complex and prioritized tasks.
Instead of asking yourself “How to integrate AI into an app?”, pay more attention to the importance of artificial intelligence in business, and the potential benefits it can bring.
As we mentioned before, integrating AI into business is not a difficult task nowadays. If you contact us and start cooperating with Incora software, adjusting the AI module to your needs won’t also be an issue.
One of the major challenges of artificial intelligence in business is knowing what you expect it to do, and why you need an artificial intelligence integration.
Therefore, instead of worrying about the technical aspects, try to answer yourself: what is artificial intelligence in business, and how can I benefit from it? When you will have your answers - we can embody your ideas to live.
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In business, AI stands for Artificial Intelligence, which refers to the use of computer systems and algorithms to perform tasks that typically require human intelligence, such as decision-making, data analysis, and customer service automation.
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