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Which AI Tools Should You use for Gamification in Your Company?

Avani Tiwari,

Research Intern,

Indian Society of Artificial Intelligence and Law.


Adoption of AI tools is increasing rapidly. AI is being used in various fields to automate mundane tasks, clubbed with human experts it is being used to perform tasks more efficiently.

Gamification is a term which has gained popularity in recent times. It deals with using game mechanics and game elements in non-gaming scenarios. Use of a combination of AI and Gamification is still evolving. Its applications can be traced in various areas like recruitment, training new hires, engaging existing employees, as a marketing strategy to engage customers etc. Using AI tools for gamification enhances the process for users and makes it more realistic and interactive. Fitbit, a popular device amongst people nowadays is one of the examples.

Given below are some of the popular AI tools their features, drawbacks and costs associated with it. The objective is to provide insight to companies from various parts of the world who are looking forward to inculcating AI tools in their gamification strategy.

1. Azure Machine Learning: It is a cloud computing platform by Microsoft. It provides cloud services, allows to build, manage and deploy applications on a network with tools and frameworks. It is available in 140 countries, has 54 regions worldwide, 6 geographic locations with more than 100 data centres. It has a pay as you go policy. For the smallest instance, Azure charges US $70/month for 2vCPU’s and 8GB of RAM. Coming to the largest instance, it costs US $6.79/hour the 3.89TB of RAM and 128 vCPU. When it comes to integration with open source tools, since most organizations use Microsoft OS hence MS tools the winner would be Azure from this perspective. Azure was established in 2010 and offers over 100+ services. It provides better development operation with a strong security profile. It provides a cost-effective solution. It is Op-Ex friendly. Coming to disadvantages, it uses different code base for cloud and premise which makes it a little difficult to use by coders. Its PaaS ecosystem is not as efficient as IaaS. It provides poor management of GUI and tools which is most important for gaming. Adding to all this it does not provide integrated backup.

Companies such as Johnson Controls, Polycom, Fuji Film, HP, Honeywell, Apple use Azure.

2. Amazon Web Services: As the name suggests, it is a cloud computing platform by Amazon. It allows you to create and deploy applications over the internet. It has 69 availability zones within 22 geographic locations and is planning to have 12 more in the near future. AWS can be considered as a winner in terms of availability zones It also has a pay as you go policy. For the smallest instance, AWS charges US $69/month for 2vCPU’s and 8GB of RAM. Coming to the largest instance, it costs US $3.97/hour for 3.84TB of RAM and 128 vCPU. If a company is heavily facing cost constraint then for the long term using AWS is advisable. AWS provides a greater number of services as compared to the other two platforms considering it is the earliest in the market (established in 2006). It provides 200 services. It provides enterprise-friendly services with instant access to resources which increases speed and agility. It has disadvantages as well as the technical support fee it charges. It suffers due to limitations of EC2 service.

Companies such as Netflix, Airbnb, Unilever, BMW, Samsung, Mi, Zynga use AWS.

3. Google Cloud Platform: As the name suggests it is a platform by Google. It allows application development and integration over cloud services. It is available over 200 countries, in 61 zones and 20 regions. It also has a pay as you go policy. For the smallest instance, AWS charges US $52/month for 2vCPU’s and 8GB of RAM, which makes it comparatively cheaper than the other two. Coming to the largest instance, it costs US $5.32/hour for 3.75TB of RAM and 160 vCPU. Google offers a 50% discount in certain cases and offers a flexible contract. Even though the pricing of AWS seems cheaper but overall due to its customer-friendly pricing models GCP is the winner. Google as compared to the other two offers only 60+ services. It can be concluded that it provides better pricing than competitors. Another advantage is that it provides live migration of virtual machines. It charges hefty support fee and has complex pricing schema which can prove to be a drawback. Apart from this downloading data from GCS is expensive.

Companies such as HSBC, Pay Pal, 20th Century Fox, Bloomberg, Dominos use GCP.

Which tool is better?

This is a question that cannot have one definite answer. All the 3 are leaders in some and losers in some services while most of the times they have a tie. Choosing the best for a company solely depends on the financial constraints, technical requirements, availability zones etc. of the respective company. The decision making is quite closely comparable to buying smartphones or laptops, choosing data plans of various ISPs by individuals or companies as the case may be. No doubt that there is no such thing as the best when it comes to technological tools and devices. The decision making differs from person to person, company to company and purpose to purpose.

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The Indian Society of Artificial Intelligence and Law is a technology law think tank founded by Abhivardhan in 2018. Our mission as a non-profit industry body for the analytics & AI industry in India is to promote responsible development of artificial intelligence and its standardisation in India.


Since 2022, the research operations of the Society have been subsumed under VLiGTA® by Indic Pacific Legal Research.

ISAIL has supported two independent journals, namely - the Indic Journal of International Law and the Indian Journal of Artificial Intelligence and Law. It also supports an independent media and podcast initiative - The Bharat Pacific.

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