Should a small business invest in Artificial Intelligence and machine learning?

We as a human has accepted long ago, that technology is the only key that could make things easier, better, faster and more efficient. In the league of efficient and effective innovations, AI and ML are all ready to transform our business landscapes.

Both AI and ML are touted to add edge companies required, increase efficiencies, improve sales and marketing and even help in critical HR functions and Financing strategies. However, there have been thoughts like new technologies are meant for large businesses only. We have witnessed the very slow adoption of technologies in smaller companies in the past.

Does artificial intelligence services and ML also destine to be the same as their peers in the arena of small businesses?

That may not happen with AI and ML since these already have become ubiquitous. In fact, people may not get a sense of interacting with such technologies, but these techs are already in our everyday life. That personalized price offers everywhere in your browser for a particular product or service you searched a weak ago or two is the result of AI.

Earlier, there works the mantra in businesses i.e. "if you don't use this/that technology, chances are high that your competitors do and this should be a concern."

In today's time, companies, whether small or large needs to run up from this way to adopt a technology. The technologies with which we live are crucial and possess massive scope in one and many ways to change human's day to day life, as well as help businesses, hit their needs profoundly. Scope of technology in a business can be more than its competitors can think. Every innovation/technology came to addresses some specific issue which was unsolved; thus varies from one another. Therefore, every business should embrace technology as per it's business use-case.

Let's First Understand AI and ML

Artificial Intelligence: Artificial Intelligence is two words in itself "Artificial" and "Intelligence". Artificial as it means – something which is not natural or many by human, Intelligence, on the other hand, refers to the ability to understand or think. AI is not a system, rather it is implemented in the system. Let's understand AI with a definition. "It is the study of how to train the computers so that computers can do things, which at present human can do, better." So, using AI, we add all the capabilities of humans to machine.

Machine Learning: Machine Learning is the process in which a machine is made to learn by its own with being explicitly programmed. It is an application of AI that instills an ability within the system to learn and improve from experience by itself. ML applications can be generated by integrating the input and output of that program.

How AI and ML work?

As we discussed earlier, AI is implemented in a system. It works best by combining large amounts of data sets with fast, iterative processing and intelligent algorithms where ML plays its role. AI-based systems are touted to learn automatically from patterns and features in that vast data sets. Rather than investing time and money in self-driving cars, the industry recognized the artificial intelligence's practical use-cases in processing a vast amount of data generated daily. If companies strategically apply AI to certain processes, insight gathering and task automation occur at an otherwise unimaginable rate and scale.

Through breaking down mountains of data generated from text and voice search on the web and smart devices, AI systems help to perform intelligent searches, penetrate both text and images to find out patterns in complex data, and then with help of other components act on those learnings. Since affordable cloud computing and big data explosion are bound to cover up the market in 2019, we can expect continues disruption of AI technologies throughout the year.

Basic Components Of Artificial Intelligence

Though AI doesn't go along with a system alone. There are several components which keep complete tuning with each other and serve the system to deliver the required results. Here is the list of AI components:

We are not going deep in AI's components and its special features. We will cover them in our next blog.

How Walmart Uses AI

Recently retail giant Walmart uses the power of AI to make automatic business decisions. There are 245 million customers visiting 10,900 stores and 10 websites all over the world. Every hour, Walmart collects 2.5 petabytes of unstructured data. The retail giant uses that big data with AI to analyze to understand the pattern of user's shopping, recognized products trending on social media channels and how weather and particular seasons affects sales, and so on.

Likewise, small businesses also on daily basis produce a large volume of data – both structured and unstructured. Chris Howard, distinguished research vice president at Gartner, quoted that the number of enterprises implementing AI grew 270 percent in the past four years. Thus, in 2019 for every CIO of any organization, getting AI and ML integrated has become absolutely ubiquitous.

To get a better sense of the kind of things AI and ML can do with such data of small businesses, let's consider the following use cases:

Reaching Out – Businesses are opting bot application development service to integrate Chatbots in their digital systems to make connection and communication faster and convenient with customers, employees and stakeholders. While you as a user get help for your queries, these chatbots do stock up data. These agents function 24 hours a day without human intervention and answer the most basic queries to more complex ones. AI with ML here can easily look up to the data to understand the peak hours when users search/interact with a business, etc., and also take a note from user's feedback positive or negative or satisfactory for improvement.

CRM/ERP – If you are managing your business operations using CRM and ERP apps, you must understand its utility as well as its limitations. These business tools need upgrades to make a tune with today's fast-paced digital world. AI integration within these ERP and CRM tools could prove to be a significant statistical move for small businesses. Given the enormous and differentiated types of information produced by the business, it is difficult for a human being to find out correlation from such structured and unstructured data sets and suggest somethings meaningful quickly.

However, for AI, it is a matter of minutes to produce valuable business insights for strategic decision making. For instance, AI can collect customer data from different touch points and combine them with CRM to come up with meaningful information.

HR – In every industry and every company, employees productive hours often waste on some routine and mundane work every day. Mundane work such as payroll administration and accounting can be effortless with AI and ML. AI and ML add up automation to some vital aspects of work that required the attention of skilled manpower. The technology likewise can make the business more effective since much more can be done with fewer employees.

Finance – Finance is one zone where AI and ML are getting wide adoption super fast. Now, it is becoming common to come across entire businesses based on AI and ML to complete certain things. For instance, the credit risk of a borrower. For small and medium-sized companies, it is judicious, to begin with automating some of the exercises. As per McKinsey and Company about a third of opportunity in finance can be captured using basic task-automation technologies, for example, robotic process automation (RPA).

"Working on existing IT frameworks, RPA is a class of general-purpose tool software alluded to as "software robotics" instead of "physical robots". RPA and complementary technologies, similar to business-process management and optical character-acknowledgment tools, have been integrated effectively over various activities in finance," says McKinsey.

Conclusion

Organizations are already colossally profiting by executing AI and Machine Learning software support services in their businesses. Numerous procedures have improved through the expertise of these technologies.

But of course for small businesses, evaluating cost and benefits is crucial to adopt new technology. As we have already discussed that the technology will only help make things easier, better, faster and more efficient, small businesses can also integrate the innovative technologies strategically. They must look up to the opportunities open up by AI and ML – how it will be useful for consumers as what will it do to competitors. Thus; small business can go ahead while taking into account the solutions that would be implemented to improve the business processes.

Find more top mobile app developers worldwide on AppFutura.