{"id":22767,"date":"2021-04-27T07:31:00","date_gmt":"2021-04-27T07:31:00","guid":{"rendered":"https:\/\/www.experfy.com\/blog\/ai-build-or-buy\/"},"modified":"2023-08-23T13:21:57","modified_gmt":"2023-08-23T13:21:57","slug":"ai-build-or-buy","status":"publish","type":"post","link":"https:\/\/www.experfy.com\/blog\/ai-ml\/ai-build-or-buy\/","title":{"rendered":"AI (Artificial Intelligence): Build It Or Buy It?"},"content":{"rendered":"\t\t
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Founded in 2005, Rimini Street<\/a> is a provider of support services for enterprise applications from companies like SAP, Oracle and Salesforce.com.  The goal is to reach $1 billion in revenues by 2026.<\/p>\n

And to accomplish this, the company evaluated a myriad of AI solutions. But they all fell short.<\/p>\n

\u201cIn the end, we leveraged a combination of best of breed open source technology and tools to build our own AI platform that is very powerful, intelligent, extensible and scalable,\u201d said Brian Slepko, who is the Executive Vice President of Global Service Delivery at Rimini Street. \u201cOur home-grown AI platform and components give us all the flexibility we need along with the data intelligence\u2013and we now have three patents pending as a result.\u201d<\/p>\n

It was a risky strategy. After all, many AI projects fail to go beyond the proof-of-concept stage.<\/p>\n

But to remain competitive, companies often have little choice but to make big bets with AI. \u201cCreating your own AI solution will require a huge budget, research, time, and resource commitment,\u201d said Swapnil Bhagwat, who is the Vice President of Marketing at Atlas Systems<\/a>. \u201cBut AI capabilities for any business have the potential to become a great competitive advantage.\u201d<\/p>\n

So then what are the factors to take into account when looking at whether to build AI? <\/p>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Let\u2019s take a look:<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Is AI The Really Needed? <\/strong>Yes, the temptation is to assume that AI is some kind of elixir for any type of problem. But this is a big mistake. True, AI is very powerful but a simpler technology may be a better approach. <\/p>\n

\u201cIdentify your business challenges first\u2013don\u2019t jump on the AI\/ML bandwagon because it is the topic du jour,\u201d said Slepko. \u201cPut together a very structured plan which includes your vision, strategy, how you want to use the technology and the desired business outcomes you are trying to tackle.\u201d<\/p>\n

Experience<\/strong>:\u00a0If your organization has little real-world experience with AI, then you might want to first look at off-the-shelf products.\u00a0For example, a chatbot<\/a> could be a good place to start, such as with basic customer support services.\u00a0<\/p>\n

Another idea is to look at your company\u2019s IT applications and apply the AI functions. They can be quite powerful, especially since they are already integrated with your data sources.<\/p>\n

Don\u2019t Do Everything<\/strong>: If you decide to build a home-grown system, it is still smart to look at ways to get help from other companies. An example would be to outsource the data labelling (the process can be tricky and laborious). <\/p>\n

Capabilities<\/strong>: Is your organization AI ready? Usually the answer is \u201cno.\u201d <\/p>\n

According to Mingkuan Liu, who is the Senior Director of Data Science at Appen<\/a>, here are some questions to ask:<\/p>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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