More businesses are realising the value of Artificial Intelligence (A.I.) technology, as shown by a recent report from Tortoise Intelligence. According to this study, investment in A.I. worldwide reached $77.5 billion in 2021—an increase prompted by the COVID-19 pandemic that forced business leaders to digitise their processes.
With A.I.’s domain ever-expanding, it’s natural for business leaders to jump on the bandwagon and look to A.I. as the answer to their problems. But it’s not overly wise to invest in the technology, or any technology for that matter, without reviewing several factors first. To get the most out of A.I., you should ask yourself and your team a few questions before you start incorporating it into your business model.
As a business or leader, what problem am I actually trying to solve?
When deciding whether or not to use A.I., you should carefully consider what problems you are trying to solve, as this will help you determine whether A.I. is the right solution for your company. For example, companies like Spotify and Netflix use A.I. recommendation engines to improve their customer retention, while banks employ A.I. to spot customer patterns that indicate fraudulent activity.
Large enterprises are not the only ones benefiting from A.I. Small businesses that understand what they need also gain a lot from the technology. For instance, a small retailer with an A.I.-powered CRM software may grow its loyal customer base. It’s a matter of figuring out the pain points of your business and seeing whether A.I. can play a role in solving them.
Do I have the data to train a model and if I do?
A.I. technology is only as good as the data it's given. So, before you invest in A.I., you need to make sure you have large amounts of quality data to train the system. If not, it's likely that the A.I. system will not be able to accurately solve the problem you're trying to address.
You can determine the quality of your data through these dimensions:
- Accuracy - the data is 100% correct and reflects real-world situations.
- Completeness - the data is comprehensive and has all the required values.
- Consistency - the data is reliable and matches other sources.
- Validity - the data adheres to business rules and parameters.
- Uniqueness - the data has no duplicates or overlapping values.
- Timeliness - the data is up-to-date or can be updated in real-time.
In order to get the best results from an AI model, it's important that you prepare the data properly. According to a survey by Anaconda, data scientists spend 45% of their time on data preparation tasks. The quality dimensions in mind, these data scientists would go through several steps like data cleansing and data visualisation.
What's my risk appetite and do I have the ability and support to manage the risks?
When you implement A.I., you have to think about the privacy and security risks involved. When companies become victims of cybercrime, they usually end up spending a lot of money to fix the problem.
IBM’s research revealed that the average cost of data breaches reached $4.24 million in 2021. That’s why when thinking of investing in A.I. technology, you would also need to consider investing in strong security measures.
Although artificial intelligence (A.I.) adoption is becoming more and more common, there are still ethical concerns surrounding it. For example, machines learn from the data sets they’re fed. If those data sets reflect biases or discriminations of the developer, the machine could incorporate those ideas into its own processing.
These are valid things to ponder before adding A.I. into your business model, especially if your business is guided by certain ethical principles.
What is my budget?
Budget considerations play a large role in your decision-making; A.I. technology is expensive, so you need to make sure that you have the financial resources to invest in it. Understand also that A.I. is a long-term investment, so you need to have a solid plan for how you'll finance it over the long term.
The cost of A.I. depends on a number of factors, but Analytics Insights evaluated that a complete A.I. solution could range anywhere from $20,000 to $1,000,000 and beyond!
How will I deploy and manage my AI system?
Deploying and managing A.I. requires a lot of thought and consideration. You need to ask yourself where you want to store your data, how your users will access it, and who will be responsible for maintaining the system on a day-to-day basis.
If you don't have the in-house expertise, you'll need to hire someone who does – but this can be a costly investment in itself. As such, it's important to factor this into your decision.
Artificial Intelligence can be used in numerous ways to support your business, but to achieve the desired results, you'll need to do your research and implement A.I. correctly.
If you're unsure how A.I. can help your business, talk to Spark and we'll tell you about how we've helped our customers transform their data into actionable insights that solve complex business challenges—through Artificial Intelligence.