In fact, many companies are looking for ways to achieve effects after applying AI.

What companies expect from AI is business optimization, growth in sales and business models, and increased cost efficiency and others, but they say that the actual goals and methods of introducing AI should be different depending on understanding and maturity of AI. Let's check MEGAZONE.DIGITAL’s strategy for successful AI introduction through application cases of existing companies.

According to a survey by the Boston Consulting Group, companies can be divided based on AI maturity.

1. Pioneering Companies: Organizations that understand and have adopted AI (integrating AI into internal processes as well as products and services)
2. Researching Companies: Organizations that understand AI but are not using it beyond the pilot stage (Reviewing effectiveness)
3. Experimental Companies: Organizations that are experimenting on or introducing AI, but do not have a deep understanding of AI (learning through experiment)
4. Passive Companies: Organizations that have not adopted AI or do not have a good understanding of it

In fact, many companies are applying AI and seeing its effect. It can be seen that the introduction was carried out according to needs of each company, such as Allianz, KB Insurance, Chevron, and GE, and there were remarkable results.

Allianz

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KB Insurance

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Chevron

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GE (General Electric)

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However, since each company has a different approach and goal for AI, it is not appropriate to apply it as it is even if the business field is similar. MEGAZONE.DIGITAL decides position of a company through two groups of indicators and provides consulting on an AI introduction strategy.

The table above helps you objectively understand the current situation of the company and apply it through a framework for AI introduction, starting with minimizing differences through intensive communication with customers

In addition, through a configuration framework of an AI platform, we are proceeding to the following stages.

1. Diagnosis of customer’s problem and consulting on goal setting
2. Establishment of pipeline integrated with data, AI model and SW application
3. Composition of the DevOps environment enabling simultaneous CI, CD of AI model and SW application
4. Maximization of AI introduction effect through efficiency of operating platform