Artificial Intelligence has become a bit of a buzzword in the business world, with tech giants like Google, Amazon, Netflix, Twitter, and TikTok making huge advances in Artificial Intelligence. 

Google uses Artificial Intelligence to refine search results, and target advertisements; Amazon and Netflix use it to recommend products and television shows to watch; Twitter and TikTok to suggest new users to follow. The ability to provide all these services with minimal human intervention is one reason why tech firms’ dizzying valuations have been achieved with comparatively small workforces.

“Just as electricity transformed almost everything 100 years ago, today its actually hard to think of an industry that will not be transformed by Artificial Intelligence in the next several years.” Now in every household and business, we use electricity without even thinking, will the same be true of Artificial Intelligence?

Despite the hype around Artificial Intelligence, many companies have continued to resist its adoption.  Instead they are waiting for the technology to mature and for expertise in Artificial Intelligence to become more widely available. They are planning to be “fast followers” — a strategy that has worked with most information technologies.

There are several reasons for the reality check.

• Every business has a budget and a return on investment (ROI) to worry about. After all, the implementation of artificial Intelligence will eat up a sizeable amount of your company’s resources and time: is it worth it?

• AI won’t change a business overnight. It becomes intelligent after learning and processing large volumes of data. Consequently, this means that businesses need to have the infrastructure in place to facilitate and coherently store large volumes of company-specific data.

• Often regarded as one of the biggest obstacles to AI adoption, a business without a modern networking infrastructure will have difficulty supporting AI technology. Legacy technology has trouble supporting AI because of the sheer amount of data that AI needs to process. 

• AI compatible infrastructure will need to be agile, flexible, and scalable and have enough processing power to accommodate huge volumes of data. One solution that larger businesses are turning towards is cloud-based services. This strategy negates the huge costs of bringing in new servers and powerful processors.

• Businesses, particularly big ones, often find change difficult. One parallel from history is with the electrification of factories. Electricity offers big advantages over steam power in terms of both efficiency and convenience. Most of the fundamental technologies had been invented by the end of the 19th century. But electric power nonetheless took more than 30 years to become widely adopted in the rich world.

• Firms may have been misled by the success of the internet giants, which were perfectly placed to adopt the new technology. They were already staffed by programmers, and were already sitting on huge piles of user-generated data. The uses to which they put Artificial Intelligence, at least at first—improving search results, displaying adverts, recommending new products and the like—were straightforward and easy to measure.

• Finding staff / Software Engineers can be tricky for many firms. Artificial Intelligence experts are scarce, and command luxuriant salaries. Only the tech giants and the hedge funds can afford to employ these people.

Conclusion 

Many of us carry idealized visions of Artificial Intelligence auto-completing tasks for us and becoming more readily available as time passes, but Artificial Intelligence remains like any learning tool. Artificial Intelligence requires time, resources, and skill to create the desired result. The best way to take advantage of long-term Artificial Intelligence goals is to begin now and orient staff towards Artificial Intelligence skills that will assist the transition from manual work to problem-solving automated processes. The more time and resources that can be allocated to Artificial Intelligence's beginning and maintenance, the better the results it can provide. There are simple tasks, such as data-gathering, that can be completed now to assist with AI integration in the future. Using the fast follow method could now mean losing a distinct advantage within the market.

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