Google as an entity has become synonymous with answers. “Just google it” is a common response to any kind of question. But now a new challenger has arisen, and it takes on an unlikely form. ChatGPT is threatening the way Google searches. It’s inciting all kinds of discussion regarding AI, ML, and what the future of this technology looks like. With AI offering so many possibilities, how do you know if AI can be applied to your business?
As a business owner, your vested interest is the success of the company, but if there was a way to heighten productivity and efficiency, wouldn’t you jump at that chance? AI has become a tool that can increase efficiency, but there are some pitfalls to avoid when approaching this decision-making process. The main benefit of utilizing AI is that it takes repetitive, menial tasks and completes them for you. Implementing AI enables team members to spend their valuable time on more complex tasks, and there are plenty of ways this new tool can change the landscape of a growth-stage company. So let’s dig in, and see just how AI enables businesses to reach new heights of productivity and capability.
Here Are Examples Of How AI Has Been Applied To Businesses
At a large recruitment firm, hundreds of thousands of candidate resumes were being processed manually during a screening step before being submitted for interviews. Utilizing access to historical data, a custom ML-based candidate screener was built, reducing the workload of the recruiters by up to 600%. Such a drastic change in workflow enabled team members to focus on challenges more specific to their area of expertise, and in turn comprehensively improve overall results.
At a financial firm, team members would review hundreds of financial line items manually to identify and flag potential financial expenditures that were anomalous. This was a tedious and time-consuming process. Since the reviews were looking for patterns in the data, the process was replaced by an ML model that would be trained by the reviewers to look for the same patterns. The resulting model could review with 99% accuracy and could process thousands of lines in seconds.
A large financial outsourcing firm involved in reviewing bills and submitting them to clients for billing was spending hundreds of hours manually reviewing the documents for potential rejection reasons. After identifying the fact that there are patterns in the data, the ML model was used to automatically review and flag bills that could be rejected. The model is 70% accurate with its predictions that assist new team members in reviewing rejections.
How Do I Apply AI To My Business?
The first step in figuring out how AI can help your business is to identify the data that you have or may be generating. Here are a few questions to get you started.
- Do you have a central database where all of your user actions are logged internally?
- This is the ideal starting point for data science. You can start by exploring the database, and then the data can guide you.
- What kind of models and use cases are there? You need a business analyst or a data scientist to start this project.
- Example: You have a database full of sales data or customer bills. You can build models that tell you if a potential lead will close. You can also construct a model that can predict if a customer will default on a payment.
- Do you have people doing repetitive tasks?
- Processes that include repetitive work serve as prime candidates for automation since they have repeated patterns associated with them. The problem with this kind of process is that data is often unreliable, scattered, or non-existent.
- Step number one to solve this problem is to build a data collection mechanism that logs all user actions, which can then be used to build an ML. The ideal starting point for this would be a business analyst or data engineer.
- Example: If you are a customer service firm and tackle inquiries or support tickets that are of a repeated nature, step one would be to log all the tickets that come in and what actions took place. Record keeping can be in the form of call recordings, tickets in a ticketing system, or both. Over a few weeks to months, you will have enough data to start implementing data science.
Benefits of Properly Utilizing AI
Better Decision Making – using data to make informed decisions means a better path can be chosen. If you know what steps to take and what information is necessary to inform those steps, then the final result will oftentimes align more accurately with business interests.
Increased Efficiency And Productivity – Team members no longer have to spend time completing monotonous, pattern-driven tasks. Instead, AI will handle the data-driven processes, and teammates can focus on more complex problems.
Fewer Errors – Humans are error-prone, but the probability of a mistake occurring decreases drastically when utilizing AI. The model is purposefully built and trained to minimize mistakes of any kind, and such a boon can’t be understated in the grand scale of the business as a whole.
Just A Drop In The Ocean
The focus here has been on how AI can positively impact your business, and the ways it can be utilized. However, the reality is that an organization’s wants, needs, and capabilities will truly determine how AI could be used. There’s plenty to learn when it comes to the capabilities of AI, and that’s where confusion can set in. The variation from organization to organization means that having a partner to guide you on this journey of utilizing AI can be integral to the success of this tool’s implementation. But, how do you go about choosing this partner? That’s a question for a future blog.