How Artificial Intelligence spells success to businesses and what to do to eliminate AI-associated risks

Which technology is leading the world forward nowadays? Certainly, Artificial Intelligence is among those solutions that have recently become efficient, competitive tools. In 2021, 86% of CEOs claimed that AI was a company's mainstay, which is hardly surprising. However, before speaking about how Artificial Intelligence would benefit your enterprise (we will explore four current uses of AI), we need to clarify the term itself. People tend to utilize it for defining any software engaging human-like processes. 

Although naming applications based on planning, learning and problem-solving artificial intelligence is technically correct, it does not unfold any specifics. So let us dig deeper in the next paragraph to understand how the technologies operate and are predominant in business nowadays.

Machine learning vs deep learning: what's the difference?

Machine learning

Primarily, it handles vast amounts of data promptly, identifying anomalies and the main patterns. It makes machine Learning indispensable for the Internet of things and turns connected wireless devices into digestible data sources. ML is also critical for optimizing the work of machines: in case some of the functions are at a decreased capacity, the tool defines it and notifies employees about the need to contact preventive maintenance teams for corrections. 

Yet, we need to mention here that the technology is an umbrella tool as well, and the development of AI neural networks encouraged the evolution of what we call deep learning.

Deep learning

Simply put, deep learning is the more specific branch of ML, equipped with more advanced functions (for instance, fraud detection). The technology is distinctive by analyzing multiple factors simultaneously. Assuming you have to prepare self-driving cars for a smooth operation. In that case, exceptionally helpful would be to provide them with the data on other objects' distance, their speed and the justified prediction of what will happen in the next 5-10 seconds. That is DL's task to assist self-driving vehicles in making decisions.

It is noteworthy that deep learning is used even more often than ML, as older ML mechanisms reach a particular amount of data and then plateau the processing of content. Meanwhile, DL keeps up working effectively as more info is received. As a result, deep learning implies more independency and space for scaling.

Using AI in Business: 4 inspiring examples

Businesses have a wide-open field of AI-based tools: from chatbots and targeting to creating predictive recommendations. Moreover, AI and applications that have it in their core will allow you to stay updated with modern tech trends and earn a living. And here's how: 

Using Artificial Intelligence tools in Operations 

AI is key to automating work processes and freeing up space for accomplishing more complex projects or tasks with a higher priority:

• Enhanced IT processes. First and foremost, machine learning can automate software maintenance and cybersecurity tasks, as it traces potential hazards faster than humans. 
• Digital transformation. Blockchain and robotics assist in managing data and decreasing IT operational friction. It can be beneficial for banking, tourism, e-commerce or healthcare branch. 

Using Artificial Intelligence tools in Accounting

Since Artificial Intelligence never tires and sleeps, it can upload files, read them and sort them by the accounting codes during the workday. 

• Completing repetitive tasks. To name a few, AI records information, reconciles accounts, categorizes transactions, correlates significant data from scanned receipts to payments, categorizes expense reports, and promptly traces price changes. 
• Semi-automizing payroll and other complex processes. In addition to the advantages mentioned above, AI is skilled at learning from failures and strategic problem-solving. Thus, market leaders increasingly invest in the newest AI-supported payroll systems. 

Using Artificial Intelligence tools in Marketing

AI is primarily associated with obtaining detailed insights on target customers: businesses may use data to increase conversions and shorten the workload of marketing teams. With the help of AI, you can know how users interact with a website, what devices they prefer to use and get information on customers' demographics and location. 

• Customized UI and enhanced CRO. Although creating websites from scratch is still beyond AI's capabilities, intelligent personalization features help companies attract new clients and increase the loyalty of existing ones. For instance, the technology displays the most relevant items for a specific audience and sets push notifications that notify customers about new offers at the most appropriate time. 
• Image recognition. Marketers can analyze many photos posted to social media daily to realize where and how customers utilize products or take advantage of services. That's an excellent way to estimate market penetration and measure brand awareness, as well as gain an understanding of how to increase these parameters.
• SEO optimization. Machine learning helps to grasp the specifics of competitors' SEO tactics, shape SEO-friendly websites and find out about keywords that will take on new relevance. 

Using Artificial Intelligence tools in Sales

Harvard Business Review informed that AI improves leads by around 50%, decreases call time by 60-70% and has cost reductions of 40-60%. Here are the most fruitful ways to utilize the technology in sales:

• Demand forecasting. You may develop accurate automated sales projections, taking into account historical sales results and specifics of customer interaction. 
• Prioritizing leads. Based on communication with the salesperson, customer data and social media postings, the technology prioritizes leads, putting those with the most significant chance of closing successfully on the top of the list. 
• Using chat/email bots. Finally, applying AI to send personalized messages to multiple customers or start the conversation by sending a tailored notification is beneficial for e-commerce and retail. 

How can you handle risks associated with AI?

Security experts advise approaching AI risk management similarly to how you would prefer to organize that while onboarding new employees who need to follow the organization's values. The European Commission's High-Level Expert Group on Artificial Intelligence's Ethics Guidelines for Trustworthy AI highlighted five essential steps for confronting AI hazards:

1. Focus on the development of integrity in AI from the very beginning. Be precise about deployment, evaluation and security AI according to a culture of integrity and short-term and long-term targets. 
2. Take a deep dive into AI's past performance. Explore and analyze potential biases which may occur to root out possible security threats. 
3. Integrate AI into your company's culture before the deployment phase. It's crucial to first of all estimate privacy, limitations and functionality for each new AI solution. 
4. Evaluate the performance of AI. Track the functioning of AI, and think over corrective actions and possible enhancements. 
5. Keep your system safe and terminate those solutions which do not correspond to your company's values. Apply robust security tools designed for AI-based solutions and establish concise mechanisms of deactivating tools that are no longer efficient. 

Proceed with an innovative digital transformation with PNN Soft

At PNN Soft, we have experience, passion for innovative technologies and readiness to accomplish challenging tasks. We provide clients with best-in-class programming products with an AI in their core. We have been delivering programming products for 20 years and honing our skills to put our ideas into the newest solutions and services. In this process, we emphasize strengthening security both during and after development. 

We immerse ourselves in analyzing individual companies' features and needs. That is why our clients prefer a long-term cooperation.

PNN Soft actively uses Agile, Scrum, and RAD methodologies to interact with clients effectively, satisfy customers' needs and obtain more flexibility. Our Agile teams of experts include software developers, GUI designers, testers, technical writers, and managers. 

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