Just like hundreds of years ago, business is the driver of innovations. Thus enterprises seek ways of implementing cutting-edge technologies to make their products and services more profitable, competitive, and cost-effective. Artificial intelligence (AI) is now an indisputable leader in terms of increasing profitability. According to Accenture, in 10 years AI will be able to generate 40% of business incomes. But if AI implementation is such a gold mine, why only 2/3 of companies deal with it? Probably because the other 1/3 haven’t read this article yet. Follow up to make your AI adoption journey smooth from the start.
Let’s Start From the Basics
Artificial intelligence is something that almost everyone has heard of today but only a limited fraction of those can really understand the essence of the thing. Initially, AI is the ability of a computer to think like a human and perform complex tasks such as research or analysis. ML for its part is an AI dimension that enables computers to self-teach on the basis of massive data input without actual human supervision. Integrating AI into your business can help with tackling a wide range of business problems, unburdening people not only from monotonous but also from quite thought-requiring tasks.
According to the type of business process AI solutions can cover 3 task dimensions. These are automation, which boost monotonous operations and helps avoid human factor errors; real time data analyses, which dives into your dataset and brings to light new valuable tendencies and insights; and natural language processing, more widely recognized in the form of chatbots.
AI Implementation Strategy
Just like before any other kind of technology integration, AI implementation requires a number of thoughtful steps before your business will be able to benefit from smart solutions AI has to offer. However, the success of the integration also depends on factors like business scope and its preparedness for such innovations.
1. Identify the Most Profitable Business Areas
After you’ve got a realistic understanding of what AI and Machine Learning are, don’t rush into their implementation. First, decide on the areas that are key to your business and if they can somehow be enhanced with the help of AI.
2. Know Exactly What You Want AI to Do
A clear understanding of what AI can bring to your enterprise is essential. Imagine certain examples of AI implementation in daily life, define the projects and tasks you will be able to perform with AI onboard not to become confused upon the integration.
3. Estimate Business Value
AI implementation sounds promising, but are you sure that it will bring real profit? There are businesses that are just not ready for such boosting. So to avoid income breaches and ineffective smart solutions, make use of a calculator beforehand.
4. Collect and Prepare Your Data
“Really successful AI applications are based on properly collected, up-to-date and organized data. It’s highly desirable to have the data describing automatable decisions or accelerated business processes in plentiful circumstances and from different angles. Since ML and AI algorithms depend on the sufficiency and quality of the information you provide, make sure you are prepared”.
Eugene Medved, AI developer at InData Labs.
If not, you can always get help from a skilled data science team willing to prepare your data.
5. Take Baby Steps
AI implementation doesn’t mean you have to turn your enterprise upside down, making all the processes automated and robotized. Instead, start small by launching a pilot project to see if AI falls in line with your business needs.
6. Involve AI Experts
Although it is an obvious step, some people decide to save on hiring someone from the outside to do their job properly. Unfortunately, AI and machine learning are not the technologies that can bring profit unless you invest in them.
7. Create an Internal Team
Apart from outsourcing experts, the team that will work on smart technology integration is of no less importance. Bring together people who are willing and ready to implement AI in your business because their own job will be simplified as a result.
8. Focus on a Single Goal
Being aimed at multipurposeness is great but not when you’re making a technological shift in a business. Setting priorities such as enhancing customer experience or saving time on completion of a certain task is the right way to go.
9. Gather Feedback
During the trial period get as much feedback from the team as possible. Do not neglect any piece of information as every drip will matter when a specific operation is solidly incorporated into your daily business routine.
10. the Green Light to AI
If your pilot project has proved beneficial, you can slowly start to incorporate artificial intelligence in other dimensions following the same scheme. But again, don’t embark on pocket emptying decisions right after the first success.
