Although businesses are actively looking for ways to put AI technology to work and improve business results, many of them are still hesitant when it comes to undertaking necessary measures associated with certain corporate changes. Here are the tips that might help overcome those doubts and evaluate your company’s readiness to adopt the AI technology.
Are You Willing to Test and Experiment?
Companies that are only starting their data science and AI journey will soon find out that testing and experimenting are an essential part of the AI technology. In order to prove each algorithm’s’ efficiency, it has to be tested against the real data. It is the only approach that makes it possible to measure the business impact of the technology.
For example, data scientists have created models and analyzed data in a way that has worked in the past, it doesn’t necessarily mean that it will work the same for another company with the peculiarities of its data.
In order to overcome this barrier and ensure the smooth adoption of AI, companies should foster an experimental culture and provide the infrastructure to support it. This can be accomplished using isolated sandboxes. Isolated sandboxes are security mechanisms for separating running programs. They are commonly used for experimenting as such infrastructure allows to execute new, previously untested code without risking to harm the whole operating system. Sandboxes are providing a highly controlled environment.
Such an approach allows for the creation of a real testing environment, whereby different tools and methods can be tested and compared against each other to ensure the best one goes into production.
One of the most important things is to define the key metrics for each model in order to measure the results after each experiment.
Are Your Business Processes Ready for Innovation?
It goes without saying that companies have to be flexible and fast in this data-driven world. Organizations that have significant data, yet lack the initiative to take steps to derive value from that data, are losing their businesses opportunities.
By not using predictive analytics to get real-time insights and deliver personalized customer experiences, companies are not able to effectively market to customers, which results in churn and lost revenues. In order to perform the transformation, this organizations often have to change their mindset – from the very top down.
According to experts from Silicon Valley Data Science “successful data teams are agile and cross-functional”. AI technology cannot appear and exist in the company without breaking the habitual rules and processes and agility is there to help overcome the challenge. AI technology is new, it does not guarantee success from the beginning and involves experimentation. By ensuring agile and flexible business processes, companies will be able to spend less time, effort and money on hypothesis testing.
AI adoption represents a major change to any company, but it brings the benefits that are worth the effort in making that change. Organizations that are ready to these changes will be in an advantageous position, and in case something doesn’t go as planned there are always data science and AI consulting companies to turn to for professional help.