Top 5 Artificial Intelligences (AI) That Should Address Challenges

Artificial intelligence (AI) has the potential to completely redesign the way businesses operate across all functions, including customer service, marketing, and finance. There are numerous AI development companies that can help you develop modern AI-based solutions for your business. But like other emerging technologies, there are challenges and AI is no exception. According to a new survey by MIT-Boston Consulting Group, 85% of executives believe that artificial intelligence will transform the business, but only 20% of companies are using it in some way and only 5% are using it extensively. AI adoption is very low due to obstacles that stand in the way of technology adoption. Let’s take a look at the top five.

  1. Lack of organization and ineffective leadership: The hierarchy of a company can be quite complex. There are several heads of different departments that must be on the same page to make mutual decisions for the betterment of the business. These bosses have to drive their AI efforts together, at the same time and with the same level of effort. Lack of proper organization and ineffective leadership from these bosses lead to unclear and overlapping responsibilities, ultimately hampering all of your company’s investments in AI technology. There must be proper synchronization between all departments to make decisions related to AI adoption.
  1. Not choosing the fundamental problems to solve: For the most part, a fuzzy and innovative analytics team or many analytics teams in your company work on a myriad of smaller projects outside of the core business. But they ignore working on the fundamental ground to achieve the automation efficiency that the core business needs. You should focus on harnessing the power of artificial intelligence solutions in the areas of your business priorities. For example, sectors of your business that generate significant income where automation can improve profit margins or reduce the percentage of errors and failures.
  1. Professionals without experience and without training: In most companies, there is a shortage of artificial intelligence talent and brainpower. In a survey by PwC’s Digital IQ, only 20% of executives said their organizations had the skills to be successful with AI. This lack of necessary experience and potential is one of the biggest challenges in using AI to improve a company’s productivity. Many organizations know their limits and no more than 20% believe that their own IT experts have the expertise to handle AI. The demand for machine learning skills is growing faster, but the right training is not readily available. In such a scenario, where AI talent is scarce but in high demand, most companies seek innovation from third-party sources, such as incubators and accelerators, university labs, the open source community, and hackathons.
  1. Protection of inaccessible data and privacy: To train machine learning algorithms, you need massive, clean data sets with minimal biases. Most of this data is not ready for consumption because it is unstructured. This data contains sensitive information and is stored in a different processing system. As a result, most companies tend to invest heavily in creating the effective infrastructure to collect and store the data they generate and to recruit talent capable of encrypting this information to make it usable and productive.
  1. Trust and credibility factor: It is very difficult to explain a deep learning algorithm in a simple way to a person who is not a programmer or an engineer. With such complexity, those who want to bet on AI to take advantage of new business opportunities can begin to disappear. Most companies that are lagging behind in digital transformation have to revolutionize their entire infrastructure to adopt AI in a meaningful way. The outcome of AI projects may come a little late, as the data must be collected, consumed, and digested before the experiment pays off. Most entrepreneurs lack the required degree of flexibility, resources, and courage it takes to invest in a large-scale, unsecured machine learning project.

Here are the top five challenges you need to overcome if you want to start making effective use of the growing number of AI-powered tools that are available on the market. But these hurdles can’t stop AI from transforming the way businesses operate. In case you need to take advantage of the benefits of artificial intelligence technology to develop a solution to increase your productivity, contact an experienced artificial intelligence consulting company.