Like digital marketing 10 years ago, artificial intelligence is a topic of business today. This is driving the business world into a storm. It’s a feature that automates day-to-day tasks and improves efficiency, and is worth all the attention. Most know the benefits of
cases. But the question that remains in the minds of most founders and CEOs is, “How exactly does AI help our business?”
Here, you’re solving a cloudy mystery about the link between AI and business. I’ve listed some ways you can use AI right away and see the magic spread. Hold
What benefits can AI bring to your business? Let’s look at some examples where
AI can help change the business for the better.
- Efficiently create automation
Over the last few decades, businesses have been moving towards automation. The demand for greater efficiency drives these changes. Although
automation has improved over the years, it still lacks intelligence. It works according to a set of rules hard-coded into the system. Deviations and differences in software can sometimes lead to confusion or errors. This is where self-learning machine learning algorithms can make a big difference. The
ML algorithm can independently clean the data by learning where certain types of data belong. It also quickly finds these deviations and creates automation more efficiently.
- Program Advertising Effectiveness
The Program Advertising AI helps target an audience that is more likely to transform. It also displays ads related to the right people to ensure that the product’s message is consumer-friendly.
Facebook and Google use AI to learn and group consumers based on their behavior. Many companies today are leveraging the power of AI by advertising on these platforms.
- Unleash the full potential of consumer data
Customer feedback comes from a variety of sources or levels in any organization, including call centers, retail outlets, customer complaints, and executives. Of course, it may contain some (human) errors documented in these various file formats.
To gain intelligent insights, data must be compared to correct errors before it can be analyzed. If you’re dealing with a spreadsheet with virtually infinite rows and columns, sorting manually can easily take days to weeks.
The computer algorithm can identify data with little or no surveillance and group them under different labels. Natural language processing, or NLP, can understand the feedback of information entered into a spreadsheet. You can analyze call logs as needed.
AI thus helps to clean up and process data and provide actionable insights. This helps to unleash the full potential of being scattered and hidden in various places in the organization.
- Increasing planning and forecasting accuracy
Business Plans and Annual Forecasts often use historical data for future forecasting. Most small businesses make predictions that take into account several factors such as seasonality, trends and speculation. However, it is not accurate because it depends on more variables.
Fashion Retailer Forecast Example Let’s understand this.
For example, if the Japan Meteorological Agency predicts that winter in the area will be colder than usual, winter clothing sales may change significantly. It’s about influencing the demand for both style and quantity.
Other factors include the emergence of new competitors and discounts offered by e-commerce players. Therefore, the ideal forecast should consider multiple internal and external variables. The number of variables can be a daunting task to manually predict.
The strength of AI is its ability to analyze many variables. AI-based demand forecasting solutions not only help you make accurate forecasts, but also save you time in forecasting practice. At the same time, it gives a logical explanation of the predicted number.
Startup is especially in need of a simple yet more comprehensive tool to help you plan better. A tool like the Lean Startup Canvas can be very beneficial if you are just getting started.
- Reducing risk for contract lifecycle management
With a growing business on your hands, multiple partners, suppliers, customers and other external parties to work together to reduce the risk of contract lifecycle management. Surely you will have contracts defining each of them and the various aspects of the association.
The contract is undergoing several changes from inception to negotiation, and finally to signing. The performance of the contract also includes many moving parts. When there are too many simultaneous contracts, it is difficult to ensure synchronization of the legal and operational elements.
For example, it is not uncommon to find that a contract customer needs “n” artifacts, but a few change. On the other hand, the merits of early updates from certain vendors may remain unused.
These issues are often caused by the lack of an intelligent system for storing and analyzing contract data. The unstructured form of the contract makes it impossible for an existing database to highlight the value locked in it.
You can use the AI-based CLM solution to receive timely notifications of implementations, deviations and changes. Helps you get the most out of the benefits of your contract. An additional benefit is that you can avoid legal hassles and maintain a increasingly transparent relationship with your business partners.
- Leveraging on hiring process to be data-driven and smooth
If the legacy system, which makes the recruitment process smooth and data-driven, is critically lacking in one area, it is the ability to understand humans. Employment is one of the best examples of what human understanding is needed. Algorithms using hard-coded rules don’t work, especially since diversity has become one of the central topics of recruitment. There is also no option to manually find that profile in the application’s large pool. The AI is equipped with self-learning capabilities, which helps to effectively solve this problem. Recruiters can use existing castles and employee data points to find suitable candidates in the pool.
- Cybersecurity Enhancements
Cybersecurity has had a single challenge, based on the fact that more than half of the world works from home and carries out all business and personal activities online.
Companies with sensitive customer data have always been monitored by cybercriminals. The move of all talent online has made them more vulnerable. It is difficult to check continuously using a legacy system. As a result, organizations are now looking for intelligent solutions that can prevent data breaches. The
artificial intelligence-based solution can detect abnormal behavior regardless of the width of the data It can block suspicious activity and provide real-time notifications. Thus, AI is proving to be a key component of modern cybersecurity solutions.
How would you choose and implement an AI solution?
Now that you know the various benefits of AI, the next step is to identify and implement an appropriate solution. Let’s dive right away.
- Identify problems and define goals: A solution cannot be defined without a clear purpose.
- Defining Solutions and Capabilities: Having a clear picture of the ideal solution makes the decision to build or buy. Assess the solutions available in the market and the capabilities of the enterprise. Get the solution that best fits your organization’s needs.
- Pay attention to the features: don’t waste time building solutions already available on the market. Rediscovering the wheel doesn’t do much good unless there is a huge cost-benefit or development of something outstanding.
- Gather and organize usable data: Data is often spread across different locations and levels.
- Do a pilot project: Run AI applications on small datasets before doing all of them to deploy solutions across your organization. Or you can try with a limited number of features in your business. Based on the first response, make the necessary corrections and expand the scope step by step.
Make sure you are gaining approval from all stakeholders at each step. By clearly defining the scope of problems and solutions, AI can avoid the guesswork and concerns that often arise.