How Automated Decision-Making Will Revolutionize These 5 Industries
In the last few years, artificial intelligence (AI) technology has advanced significantly. And this is not only technologically speaking but also in the sheer amount of investments that businesses are spending to upgrade their technology stack. According to data from the IDC, spending on AI-based technology could reach $110 billion by 2024, growing from its 2020 figure of $50.1 billion. But why are companies investing so much in AI and automated decision-making technologies, and should we fear the ever-present question, “will robots take our jobs?”
Is AI-based Automated Decision-Making for All?
Automated decision-making systems help businesses work more efficiently—it’s a fact. The automated processing of data and other information aids companies in working faster, making fewer mistakes, and scaling their business effectively. Automated decision-making systems take this one step further. This type of technology allows automatically-collected data to be processed and decisions to be taken or advised based on the results.
For example, GiniMachine uses AI to fight bad loans by building innovative credit scoring models that are designed to reduce non-performing loans by up to 50% while boosting loan portfolio return by 30%+ using automated decision-making support systems powered by AI technology.
This and similar technology empower businesses to boost their potential using intelligent decision-making tools and save time for more human-facing tasks. It also reduces the risk of error in decision-making, helps avoid human bias, and optimizes work processes.
2021 – Hyperdrive for Automated Decision-Making Applications
When the coronavirus crisis hit in 2020, many companies found themselves having to rethink the very way they do business. Combined with the increased drive for technology, we have something called a ‘double-disruption,’ meaning significant changes are happening across almost all spheres.
To put this in numbers, according to the World Economic Forum 2020:
- 43% of businesses may reduce their overall workforce due to technology upgrades
- 41% are focusing on a specialist-contractor business model for task-specific work
- 34% actually plan to expand their workforce to help technology integration
So, what does this mean for the future? In short, the way we work is changing in a big way. While we are nowhere close to a “robots-taking-our-jobs” scenario, the truth is that more and more roles are becoming automated. This is especially true for positions that involve simple, repetitive processes.
But what about decision-making, and can machines make fully automated intelligent decisions? Not completely. Today, even the best-automated technology is designed to aid businesses, not completely replace human workers. Automated decision making software can analyze information using tools, such as Big Data, learn from it using Machine Learning (ML), and give the most logical conclusion based on the data, which is then delivered to a human to make the final call.
Empowered by a large amount of data, a machine can consider a much more comprehensive range of information than a human mind, and this is what makes it such an effective tool.
Which Industries are Primed for Automated Decision-Making?
Now that we know the current status of the industry, let’s take a look at the top 5 spheres where AI-based decision-making is set to make waves.
Healthcare
Which would you rather your physician concentrate on you or the data on their screen? If you selected “you,” then you are looking at the new focus of automated decision-making in health tech. AI technology is increasingly being adopted in the healthcare sphere, including:
- Registering patient data
- Analyzing results of biological material tests
- Elements of clinical assessment
- Drawing together data from various sources (smartwatches, etc.)
By shifting the direction of healthcare from a doctor sitting in a room analyzing endless reams of information to one which is more automated, the physician is able to concentrate more on the patient and the less quantifiable elements of their health. This revolutionary change in healthcare could even save money, with an estimated $100 billion saving potential in medical research.
Finance
In the diverse world of finance, the general rule of thumb is the more data, the better. No matter which area your business practices in, there is little doubt that you’ll be bombarded by reams of data. AI-based decision-making software tools empower financial companies to make more of their data and utilize it effectively in their business decision-making. For example:
- Trading—Robo-advisors are one of the latest financial trends to watch out for. AI-based decision-making tools can analyze a wide variety of trading data and deliver feedback and the next investment decisions to take.
- Credit—for businesses, it can be a challenge to know which client is likely to pay back their loan and which is most profitable for business. Automated decision-making technology analyses business data and gives more accurate feedback on a client’s creditworthiness.
- Banking—from finding the right account for a client to revealing the most profitable investment decisions for their budget, automated decision-making is the future in the making. It could potentially help clients in making smarter decisions with lower risk to their capital.
Insurance
How risky is your insurance policy? This is the question every provider is asking themselves when creating a policy with a client. So how can you know a client’s actual risk versus their supposed one?
Automated decision-making tools, especially AI, allow providers to analyze a broader range of data than ever before, be it historical claims, a person’s finance, or external factors. By generating and analyzing a combination of this information, the technology is able to determine whether or not a person is a risk for an insurance policy or not. This allows the decision-makers greater peace of mind when it comes to issuing policies.
Marketing
Data is king, and no more so than when it comes to marketing. Each day, every marketing manager analyses a vast amount of data that they hope will help their campaigns to outshine the competitors. But it doesn’t have to be that way.
Utilizing the automated decision-making capabilities of AI-tech, marketing managers can boost the strength of their campaigns by knowing precisely who to target and when. In using this data, their activities become smarter and more tailored to the actual audience, not the supposed one, so the campaigns are more likely to hit home and convert.
For example, a marketing manager may seek to understand:
- Platforms that are most appropriate to the user base
- Number of ads per day
- Information about content and which information is posted about the company
In combining all this information and more, marketing managers can equip their campaigns with the best chance of success and introduce their products and services to new audiences.
Customer service
While automation in customer service might seem like a bit of a paradox, it actually makes perfect sense. It is true that most automation in companies allows them to focus more on that face-to-face (or screen-to-screen) human connection that is needed to drive brand loyalty, but Ai-based decision-making tools have a role in customer service too.
For example, by implementing automated decision-making support systems, such as smart chatbots, designed to assess the information that a client is telling them and respond quickly or refer to a human agent, can improve customer satisfaction as they often get a quick reply to their question.
In addition, smart AI decision-making tools can allow companies to deliver tailored offers to their clients based on need and demand. Or, for example, allow businesses to analyze larger amounts of data that will influence how services are provided in the future.
How to Automate Decision-Making for your Industry?
Even if your sphere isn’t on this list, it doesn’t mean that now isn’t a good time to think about the role AI-based decision-making could play in your company. In fact, failure to do so could leave your business falling behind—almost 75% of C-level staff believe that falling behind on AI could lead to business failure in the next five years. Meanwhile, only 16% have taken steps to put AI integration into the process.
So, which steps should you take to ensure that when you make the decision to onboard automated decision-making systems, you do it the right way?
Step 1: Analyze
Before starting out, it’s vital that you understand the role of automated decision-making in your business. AI shouldn’t be just a trend; it should have a valuable purpose and integrate seamlessly into your overall organizational objectives.
Step 2: Consult
At this stage, it’s a good idea to get the professionals involved. Just as 41% of businesses are seeking to contract for key roles, getting the right consultants is key to understanding the realistic potential of the technology and its timelines.
Step 3: Plan
Now that you know more or less how it will work for your industry, it’s time to plan. For automated decision-making to reach its full potential, it’s vital to include how precisely it will be rolled out, and to take account of any risks. For example, recent concerns include how data protection applies to automated decision-making, and in particular, the role of GDPR.
Step 4: Build and implement
Once you’ve designed and built your automated decision-making system, it’s time to roll it out. Expect the first iteration to come with some bugs. It’s natural that not everything will be perfect the first time around. That’s why it’s vital to analyze and try again.
Step 5: Review and upgrade
With an automated decision-making system in place, you’re probably seeing the first benefits, and that’s great. But chances are there’s something that you want to change at the same time. Now is the stage to review the past and upgrade for the future.
Getting Ready for Tomorrow: What’s Next?
AI-based decision-making is the future for many industries. In fact, it’s difficult to think of an industry that doesn’t require some sort of smart automation in one form or another. Over the coming years, we will see increasing amounts of AI tech and not just in decision-making. The only question that’s left is: when are you going to get on board?
Want to try GiniMachine in action? Get in touch with our team.
