The Impact of Machine Learning on Improving the Productivity of Startups


Even though technologies like Artificial Intelligence (AI) and Machine Learning (ML) have been widely used for quite some time, many firms today are still hesitant to implement AI-based practices.

Adopting AI & ML swings the balances in your favor as a startup owner. By becoming aware of the amazing potential of AI-powered and ML-powered technologies, you may outperform the competition and open up fresh opportunities for creativity and efficiency for your startup.

Critical judgments are now mostly dependent on scientific facts, thanks to technology. This improves the precision and error-free nature of every action, particularly in the commercial environment. Industries can more effectively meet the wants of their customers by utilizing artificial intelligence and machine learning.

Nowadays, businesses utilize Machine Learning in particular to make sure they get the best productivity results for the money they spend on running their operations. Businesses today need to improve the operational tasks they carry out at work to guarantee their teams are constantly productive, in addition to the requirement to schedule unconventional indoor team-building activities to promote employee morale.

How has Machine Learning impacted businesses?

The versatility of machine learning sets it apart from conventional analytical algorithms. Algorithms for machine learning are constantly updating. The ML algorithm will produce increasingly accurate insights and predictions as it consumes more data.

Leveraging the power of Machine Learning has led businesses to:

  • More readily adjust to constantly shifting market circumstances
  • Streamline day-to-day operations
  • Acquire a deeper understanding of business and consumer demands in general

Here are some statistics that prove ML is here to stay:

  • The global machine learning market should expand at a 38.76% growth rate between the years 2020 and 2030
  • 33% of IT leaders said Machine learning is utilized for business analytics.
  • 80% of machine learning companies target retail industries and ecommerce
  • 40% of newly healthcare-related patent applications with an AI or machine learning component have been filed.

Here is how Machine Learning can be effectively used to improve workplace productivity:

  1. Hiring Right

Every day, the human resources department receives hundreds of job applications, and it can be challenging to weed through them all to find qualified candidates to fill the necessary positions in the workplace. An individual tasked with reviewing these applications typically has biases or unwittingly allows their emotions to cloud their judgement.

When a tool is tasked with screening resumes, it can do it objectively and completely disregard any appeals to emotion. Human resources can hire the best candidates for the organization with the aid of technology like a recruitment application that screens applicants based on their distinctive qualifications.

The recruiting applicant will be entrusted with keeping an eye out for important factors inherent in a poor hire and will make every effort to prevent this from getting into the pool that will advance to the next stage of the application process. In this manner, only candidates who share the company's values will ultimately be hired to carry out important activities for the business.

     2. Making Sales Forecast Right

Managers may effectively develop forecasts that are more accurate by using information obtained through numerous channels. By doing this, it will be possible to deploy personnel effectively. To produce sales estimates that will be helpful in the production element of the business, data from all platforms can be gathered, including social media marketplaces, ecommerce businesses, and brick and mortar stores.

Knowing how many sales are coming in can make it easier to estimate what will happen in the near future when other important factors, such as events, are taken into account. As a result, productivity will rise while production waste is decreased.

    3. Making Accurate Use of Enterprise Search

The advantages of corporate search powered by machine learning extend to your staff and customers. If your company is large, finding information may be difficult, especially if it is dispersed across several platforms and channels.

Customers and team members can access a wealth of information that will be helpful for their individual responsibilities with only a few clicks on your device. People in your business will be more effective and efficient at their work if they have access to information.

   4. Making the Most of Chatbots

Chatbots can be quite useful for your company. The predictive responses to client enquiries will include previous responses on platforms that are automatically saved on the system. Now, if a chatbot is unable to respond to a query, it will be transferred to a team member for prompt acknowledgment.

This improves output and response times, which are important factors in ensuring customer happiness.

   5. Forecast the Upcoming Changes in Labor Requirements

In the retail industry, it can be difficult to maintain low staffing expenses while maintaining consumer satisfaction. When a retail store experience extended stretches without clients, having multiple employees on duty can be both expensive and completely ineffective.

A labor scheduling tool that collects data based on outcomes and inputs it into the POS will boost a retail store's productivity. This program makes sure that important parameters, like employee hours, products per transaction, and hourly sales, are taken into account when deciding how many employees to deploy during particular times of the day.

A labor scheduling tool will assist a company in deciding whether to hire full-time or part-time personnel, guiding hiring decisions and drastically lowering labor costs. It is more economical to hire part-time workers. Additionally, it would be preferable to improve a company's bottom line if the tool indicates that full-time personnel are not necessary.


Machine learning is quickly becoming a foundational technology that is organically adopted across all business sectors in order to address complex business problems and increase an organization's efficacy and scalability.

The machine learning process is iterative and continually changing, which enables firms to stay abreast of market and customer demands. In addition, because all of the main cloud providers provide ML platforms, it is simpler than ever to design or integrate ML into already-existing business processes.


Written By:
Aviskaran Team
Content Writer, Aviskaran Technologies