Artificial Intelligence (AI) is a buzzword in the digital world. It is believed to have the potential to make a transformation in any industry and offer a promising future for the businesses with its learning algorithms. The global technology intelligence organisation, ABI research, predicts the number of businesses that will adopt AI all over the world will scale up to 900,000, with a compound annual growth rate of 162%. This revolutionary technology helps in improved customer decision management, forecasting, QA manufacturing and writing software codes, making profits eventually with the data it generates everyday.

Why Implementing AI in Business can be Challenging?

With its unprecedented capability to learn and comprehend, AI solutions are disrupting the world at a speed never seen before. A recent McKinsey survey revealed that the use of AI increased every year in standard business processes with executives inferring its potential to reduce costs and boost revenues.

Implementing AI in business operations can be tough due to the following factors:

1. Costs involved

AI implementation in businesses demands deployment of expensive and high-performance hardware and software. This has to be executed within a limited allocated budget. For implementing the AI algorithms at a reasonable cost, it is best to approach AI solution providers, who have the best expertise in this industry.

2. Small data sets

The AI business systems need to be programmed to manage enormous amounts of data. You can expect better outcomes with higher quality of data. Often, it is difficult to interpret whether the data you have is structured or unstructured and compare it with your data model based on the customer information and on-site interactions.

3. Data labelling

Today, many AI systems are utilising deep learning or machine learning for data labelling. With a vast amount of data generated each day, it is difficult to be labelled. With a certain AI-led data labelling approach however, it becomes simpler to label the data internally.

4. Implementability of AI

Implementing AI can be difficult at times as the AI algorithms determine the performance of the business intelligence operations. Organisations implementing AI must know the working of AI-based solutions or technologies to be prepared for the outcome. Continuous training of AI or ML models requires manpower, which can be difficult to manage for enterprises.

5. Proof of Concept

For AI technology, a PoC is the most cost-effective method for delivering business value and demonstrating the business impact. It helps in understanding the existing business processes and combining them with other processes. It benefits the decision-making process in the business by testing the technologies and methodologies, delivering immediate value and comparing different approaches and solutions.

Industry Examples where AI is being Used:

Although AI implementation is challenging for almost every business, implementing it can make the business operations much easier. Here are some real-life industry examples:

1. Social Media

Everyday-used social media platforms depend on artificial intelligence for personalising feeds, identifying user interests, and recommending content to keep the users engaged.

Other ways where artificial intelligence is used are in emojis, facial recognition, filtering spam messages, and responding to messages on Facebook, Instagram, and Twitter.

2. Customer Service: Chatbots

Artificial intelligence-trained chatbots portray customer service representatives by using natural language processing. The main target for investing in chatbots is to raise customer satisfaction to the maximum. Today, various sites including e-commerce websites use chatbots for serving their customers.

3. Healthcare

Artificial intelligence has proven its prowess in the healthcare industry where it is used to perform surgeries.

AI-powered virtual assistants reduce the number of hospital visits and bring healthcare services to nations that are still developing. Some healthcare businesses using AI include GNS Healthcare and Zakipoint Health.

4. Automobiles

AI has such enormous potential that by 2040, it is expected to create a whopping 33 million autonomous and self-driving vehicles.

The AI sensors in these cars make accurate predictions in the speed of the car, condition of the road, and other traffic factors. AI is mainly employed by the companies CarVi, Tesla, Zoox in the automobile industry.