Wonder how Netflix is able to suggest TV series that match your interests, or how Amazon recommends personalised products, thus urging you to buy more? These are all made possible thanks to Artificial Intelligence and machine learning.
The adoption of these two emerging technologies is growing at an unprecedented rate. Today, the business applications of Artificial Intelligence (AI) in particular can range from a simple chatbot to something highly complex, all to serve the purpose of fully utilising the data businesses currently possess.
To what extent can businesses benefit from the power of AI and data? Why should businesses invest in AI solutions? Read on to learn more.
1. Data Compliance
Data compliance is the process where businesses have to follow regulations set out by data-protection laws to ensure that customer’s personal information is kept safe against misconduct or theft. The General Data Protection Regulation (GDPR) states that people have the right to know what data organisations have about them.
Organisations need to have the right software to identify whether the information on hand belongs to a customer or an employee. This is known as Data Subject Access Request (DSAR), where an individual can ask an organisation what personal information they possess.
An organisation has to be prepared to carry out that act by legislation and has to declare all the information they have if there is a DSAR. Otherwise, they may face hefty fines or legal action.
A recent study conducted by Macro 4 indicates that ‘around 40% of organisations in the sample were not completely compliant with GDPR rules for handling DSARs, with 14% took longer than the permitted one month to supply the personal data requested’ . This can damage the organisation’s reputation as it leads to lower customer satisfaction and ultimately results in non-compliance from a legal standpoint.
2. Data Transformation
Data can come in many shapes and sizes, both structured and unstructured. It would not be an overstatement to say that data is the new oil as it enables organisations to make more informed decisions. Thus, organisations need to be knowledgeable of all their data assets and how they can use their data to their own advantage.
Interestingly, the amount of worldwide unstructured data is projected to reach 80% by 2025 . What does this mean for organisations? It means they are only looking at 20% of the data that is in front of them, and the remaining 80% is greatly underutilised.
Organisations need to invest in AI-enabled data crawlers to index their data and store them in a secure repository, such as data lakes, to protect the most critical asset a business has.
Additionally, AI-enabled data crawlers can search the entire on-premise or cloud database and help organisations to classify all of their data, highlight errors or duplications. Once organisations are aware of what they have and their values, they can decide to keep the data or to discard it.
Data is susceptible to breaches. Customers put faith in organisations in keeping their personal information safe, therefore, organisations should uphold this faith by investing in security to keep sensitive information secure.
The Data Breach Report 2020 indicates that the ‘average total cost of a data breach was $3.86 million and that it took 280 days on average’  to identify and contain the breach.
Organisations need to be proactive and invest in AI technology to avoid running into problems. Adding Malops (Malicious Operations; the time hackers take to penetrate and achieve their goals) to data assets can help identify potential data breaches promptly as opposed to 280 days later.
It is also important for organisations to not only protect their data assets but also know the sensitivity. Those data assets with greater sensitivity should be prioritised first.
4. Productivity Improvements
AI can help organisations to save time searching or collating data for a report. Why should an employee spend hours scouring for information when an AI-enabled data crawler could find it within seconds?
The Insurance industry, in particular, stores an endless amount of data, and this data has to be accurate when determining the value of contracts or claims. Investing in AI technology can help insurers lower inaccuracies and give a more truthful reflection on the value of the contracts or disputed claims.
Furthermore, its predictive capabilities can help employees to manage workload and operate as smoothly as possible, thus, improving productivity. For example, if a Lorry Driver is transporting goods from Point A to Point B, he needs to be aware of the weather conditions, congestions, road accidents, or whether he needs to slow down, and so much more.
5. Data Valuation
Are you aware of how much data means in monetary terms? There are three approaches to determine how much your data is worth.
Approach #1 – The cost approach
How much would it cost to replace or replicate lost business data?
Approach #2 – The income approach
If you lose your business data, how much revenue will your business lose? If you can’t reach out to your customers, how are you able to conduct business?
Approach #3 – The market approach, where data can be bought on the open market.
When estimating the value of your data, always take it with a pinch of salt. This is because data can be error-prone, duplicated, inaccurate, and incomplete.
Therefore, it is paramount for organisations to use software to discover, classify, index, and weight the value of data to know what they have on their hands, what they don’t have, and what they might need.
For example, with M&As, there are going to be two customers records. As such, you would need to combine them to get a high-quality, high accuracy record with no duplications.
If your organisation is looking for an AI-powered solution that drives growth and helps you to take full advantage of data, invest in dataBelt could be what you have been searching for.
For more information about dataBelt and how it can help you, check out our most recent blog here or download dataBelt datasheet by simply clicking the button below.