How To Make It Easier To Implement AI In Your Business

How To Make It Easier To Implement AI In Your Business

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Founder, Buuuk – Digital Innovation.

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 businesses with its learning algorithms. The global technology intelligence organization ABI Research predicts the number of businesses that will adopt AI worldwide will scale up to 900,000 this year, with a compound annual growth rate of 162%. This revolutionary technology helps improve customer decision management, forecasting, QA manufacturing and writing software code, increasing revenue with the data it generates every day.

Why Implementing AI Can Be Challenging

With its unprecedented capability to learn and comprehend, AI is disrupting the world at a speed never seen before. The results of a 2019 McKinsey survey reveal that the use of AI has increased about 25% every year in standard business processes with executives inferring its potential to reduce costs and boost revenues. But implementing AI in business operations can be tough due to the following factors:

The 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. To implement AI algorithms at a reasonable cost, consider approaching AI solution providers who have the best expertise in this industry.

Small Datasets: AI business systems need to be programmed to manage enormous amounts of data. You can expect better outcomes with higher quality 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 onsite interactions.

Data Labeling: Today, many AI systems utilize deep learning or machine learning (ML) for data labeling. With the vast amount of data generated each day, it is difficult to label it all. With an AI-led data labeling approach, however, it can become simpler to label the data internally.

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

Where AI Is Being Used

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

Social Media: Most social media platforms depend on AI for personalizing feeds, identifying user interests and recommending content to keep the users engaged. Other ways AI is used are in emojis, facial recognition, filtering spam messages and responding to messages on Facebook, Instagram and Twitter.

Customer Service Chatbots: AI-trained chatbots portray customer service representatives by using natural language processing. The main reason for investing in chatbots is to raise customer satisfaction. Today, various sites—particularly e-commerce websites—use chatbots for serving their customers.

Healthcare: AI 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.

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 for the speed of the car, condition of the road and other traffic factors. AI is employed by companies such as CarVi, Tesla and Zoox in the automobile industry.

Making It Easy To Adopt AI

Incorporating AI software into the functioning of your organization must ensure that it meets your organization’s needs. The Enterprise Artificial Intelligence (AI) Market Outlook estimates that the AI industry worldwide will amount to over $53 billion by 2026. To implement AI, consider following these steps:

1. Define your end goals. When adopting AI in your business, you need to consider the end goals to be achieved and the software programs that will make it easier to reach your ideal customer. An end-first process is important to refine the specific features or capabilities that align with your organization’s goals and to identify the metrics that will be used to determine success.

2. Invest in smart software. The right AI software should allow easy deployment due to its flexible architecture. Using this software, you should be able to uncover the power of data in your business with advanced predictive modeling applications and to make use of data flow graphs for building the data models.

3. Evaluate the capabilities of tech adoption. Now that the preliminary stages of AI implementation are completed, the actual implementation of AI comes into play. For this, you need to determine the internal capabilities of your business.

4. Test the system. After the AI program becomes operational, now is the time to test the system to see how your efforts are helping reach your goals. When you know your metrics, such as order times, sales improvement and productivity, you can decide how to best implement AI in your business.

Wrap Up

AI continuously proves to be an asset for businesses and has been revolutionizing the way they operate. It goes a long way in helping to cut operational costs, automate and simplify business processes, improve customer communications and secure customer data.


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