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April 21, 2022, 7:51 am
Artificial Intelligence is turning our work and life upside down, as AI-related news constantly hit headlines. Seeking to take AI and machine learning to the next level, some tech giants are scaling up automation to levels they never believed possible.
Yet there’s one aspect of the AI revolution that remains quite blurred: the right business model for AI companies. Whether you launch a new startup or plan to lead an existing organization in a new direction, the business model gives you a strategy to follow.
If you want your organization to grow and stay ahead of the best in the industry, take advantage of the power of AI with the right business model to call the tune in the industry. The best business strategy takes into account not only your target audience and product lines but also how you will add value to your company over time.
A business model is a company’s plan to make a profit. Although the term was coined not so long ago, the concept behind the business model is not new at all. It gives businesses a roadmap to identify their target market, the associated costs, and the products or services to be sold.
Before selecting an AI business model, you have to ensure that the product, people, and process are aligned with your goals of integrating AI and machine learning solutions into your business. Along with that, you have to see how data is to be managed and how the data infrastructure interacts with your business.
Thus, the footing of the business model is made up of several stepping stones:
Identification of your target client will allow you to provide quality customer service and, thereby, work more efficiently. Some of the commonest AI business models include:
Analyze the key players in your niche in the local and international markets:
What makes your business stand out from the crowd and makes your products unique? Define the values your business upholds and tie them to long-term goals.
Determine the revenue streams you expect to earn from clients. This aspect is vital for investors who need to know where and how the organization will produce income.
Consider the resources needed for the day-to-day business workflow. Think beyond the capital – physical property, online space, and intangible assets such as data and intellectual property pay the role as well.
What actions will you need to take to get your business up and run it? This can be the development of your own product, service providing, or employee training.
Finally, calculate the approximate costs required to keep your business model running. Advertising, maintaining relationships, and creating valuable products all come at a cost.
The points above are the essential aspects that determine the right AI business model to be implemented. If you overlook any of them, you’ll find achieving the expected results more challenging and your choice can result in a failure.
There are tens of tested model patterns you can choose from. Let’s study five in-demand business models Artificial Intelligence companies can be guided in creating software.
Previously, this option was suitable mainly for mass media. But thanks to the Internet, the subscription model – which presupposes monthly payments for content – has become widely used by film streaming platforms (Netflix), software services (Adobe), and even retail companies.
This strategy brings a constant income that is easy to predict. In addition, some customers stay subscribed as they often forget it or put it on hold. However, the profit depends on a large customer base, so it’s vital to keep track of the number of refusals and their causes.
The product’s basic version is offered for free, but you have to pay for extra features in the premium version. This is one of the most widespread AI-based business models with the tech giants like Spotify, YouTube, LinkedIn, and others making money on it.
This strategy uses the well-known rule of reciprocity in social psychology. For this reason, if people like the basic version, they agree to purchase the advanced version quite easily. Still, converting free users into premium users requires a significant investment of time and money in it.
As an AI solution provider, you handle the AI project needs of your client from concept to installation. The services provided can be app development or modernization, workflow automation, incorporation of AI and machine learning functions, building software for better efficiency, and many more.
While the products and the industry have changed dramatically, the solution provider model continues to persevere. It remains one of the most important sustainable AI-based business models – both the client and the Artificial Intelligence company InData Labs find such a collaboration fruitful.
The XaaS AI business model shifts the customer-supplier relationship from the conventional model of ownership to a model that implies providing a service on a non-ownership basis. As more and more companies embrace digital transformation, XaaS models are getting more prevalent.
The upsides to this AI model include enormous cost savings, especially for the consumer, and a higher customer lifetime value (CLV) for businesses. It helps the service provider to deliver enhanced value to their clients, improve revenue, and sustain business growth over a longer time frame.
This strategy presupposes earning revenue by the sale of advertising. In a nutshell, a business first establishes a target audience by generating content or facilitating interaction and then generates revenue by selling access to that audience.
By leveraging this AI-based business model, you build up your brand awareness and draw potential clients effectively. Once set up, the model enables AI companies to boost sales revenue and ROI with no hassle of selling a product/service.
No need to use one strategy only. Watch your competitors, find some method of advancing client service that hasn’t been offered yet.
When you choose an AI-based business model for a startup, there’s room for experiments: it’s vital to look at the statistics and be open to changes towards greater efficiency.
The scalability of startups today is more of a necessity than a choice. Once you see there’s much room for scale-up, you’ll be able to boost your business by leaps and bounds. 
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