How AI/ML Technology Integration Will Help Business in Achieving Goals in 2022

AI/ML systems have a wide range of applications in a variety of industries and sectors, and this article highlights the top ways AI/ML will impact your small business in 2022.

By Sudeep Srivastava, CEO of Appinventiv


We live in a time of disruption, where Artificial Intelligence and machine learning are transforming industries. AI and ML are transforming the tech industry by assisting organizations in achieving their objectives, making key decisions, and developing goods and services.

For enterprises, sales AI assists representatives in making better data-driven decisions for long-term business operations and increasing revenue through tailored deal cycles that meet the individual needs of end clients. ML-driven sales can also operate with hyper-personalization, which is a critical advancement in fine-tuning client business cycles.

AI's relevance and applications in businesses are fully understood by today's corporate leaders. AI/ML systems have a wide range of applications in a variety of industries and sectors, and this article highlights the top ways AI/ML will impact your small business in 2022.

Hyper Automation

Hyper Automation is the process of automating processes using modern technology. Hyper automation can be used for a variety of reasons like, to improve customer support, enhance employee productivity, and system integration.

  • Improved customer service: Enhancing customer service requires responding to customer emails, questions, and concerns. Companies can use conversational AI and RPA to reply to client inquiries automatically and increase their CSAT score.
  • Boost employee efficiency: You can decrease your employees' manual effort and boost their productivity by automating time-consuming tasks.
  • System integration: For system integration, hyper automation assists businesses in integrating digital technology into their processes.


Cybersecurity Applications

New approaches are being explored by companies to make cybersecurity more automated and risk-free with the help of AI and ML. AI integration in business is helping to enhance cloud migration strategies and boosting the effectiveness of big data technology.

As per the reports by Markets and Markets by 2026, the market for AI and machine learning in cybersecurity is expected to reach USD 38.2 billion.

In cybersecurity, AI can be utilized for data clustering, classification, processing, and filtering.

On the other hand, ML can analyze historical data and present the best possible solutions. The system will deliver guidance on various patterns to detect risks and viruses based on previous data. As a result, anyone trying to attempt to hack into the system will be disrupted by AI and ML.

Data Analytics

When it comes to Data Analytics we know that technology has a lot of potential. AI is adept at deciphering algorithms and applying them to extract useful information from massive amounts of data. With AI software development, the company can then collect data on a huge scale in order to analyze it and develop better client acquisition techniques. These data are extremely difficult to correctly examine because they contain a large amount of information.

These data can be processed fast and a complete report can be prepared soon with the help of AI. This is quite beneficial in the workplace and improves the overall productivity of the company industry.



Automation has had a huge impact on practically every business sector since it streamlines mundane and repetitive processes, saves time and resources. Combining these automation approaches with machine learning to develop automation systems that are constantly improving is the next stage of automation.

Routine cognitive activities are rapidly automated by artificial intelligence. The AI provides many of the microservices automatically. Application deployment is a microservices example. It used to be a highly tedious and monotonous task for developers, but now it can be done effortlessly with the help of AI. Many other complicated operations have been automated, lowering the cost of doing business and reducing staff effort.

Machine learning can be used to improve the production process at the industrial level. This can be accomplished by analyzing current manufacturing models and identifying any flaws and pain points. Businesses can quickly address any issues in this way, ensuring that the manufacturing pipeline remains in top shape.


Cognitive services

Image recognition (computer vision) and natural language processing are two cognitive services that can benefit from machine learning. Improved image recognition technologies, will allow businesses to build more secure and convenient authentication choices, as well as product identification to support autonomous retail services like cashier-less checkout. As a result, new retail experiences like Amazon Go have emerged.

ML and AI integration in business can easily cater to a wide range of audiences from various geographic, cultural, and ethnic origins using natural language processing and a deeper knowledge of the benefits afforded by machine learning. Furthermore, the capacity to deliver services or experiences in a customer's local language will result in a larger consumer base interacting with the company.


Marketing & Sales

When it comes to analyzing the market and clients, AI can be beneficial. To create a better and enhanced product, predictive analysis can be applied to data gathered from the system matrix, web matrix, and social media. Customer insights can help you take your customer experience to the next level.

With the help of recommendation engines, sales projections, automation and AI fuel the e-commerce business model by increasing retail experiences. For example, Amazon, Alibaba, and eBay are significant companies that have used AI to transform the online retail business.

Intelligent recommendation systems help to increase the link between marketing and sales. There are many e-sales recommendation programs that analyses internet search patterns and makes product recommendations based on a predictive understanding of customers' behavior. Machine learning algorithms and big data techniques are used to power the systems.


Final Thoughts

Industries are becoming more advanced day by day with the use of AI and ML. In certain circumstances, this has necessitated the use of technology in order to stay competitive. However, relying solely on technology can only bring us so far. To truly establish a place in the market and break into new worlds, we must innovate to attain goals in creative and distinctive ways.

Every goal necessitates a particular approach in order to be met. Speaking with experts about what's best for your business will help you realize how technologies like machine learning and AI can increase your company's productivity and help you reach your vision of helping your customers.

Bio: Sudeep Srivastava is the CEO of Appinventiv, is someone who has established himself as the perfect blend of optimism and calculated risks, a trait that has embossed itself in every work process of Appinventiv. Having built a brand that is known to tap the unexplored ideas in the mobile industry, he spends his time exploring ways to take Appinventiv to the point where technology blends with lives.