Top 5 Artificial Intelligence (AI) Challenges That Need To Be Addressed

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-powered solutions for your business. But as is the case with 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 AI will transform business, but only 20% of companies use it in any way and only 5% make extensive use of it . The adoption of AI is very low due to the obstacles that stand in the way of adopting the technology. Let’s take a look at the top five of them.

1. Lack of organization and ineffective leadership: The hierarchy of a company can be quite complex. There are multiple heads of different departments who need to 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.

2. Not choosing the fundamental problems to solve: For the most part, one analytics team or many diffuse and innovative analytics teams in your company work on a myriad of smaller projects outside of the core business. But they neglect to work on the fundamental ground to achieve the automation efficiencies that the core business needs. You need to focus on harnessing the power of AI solutions in the areas of your business priorities. For example, significant revenue-generating sectors of your business where automation can improve profit margins or reduce the rate of errors and failures.

3. Professionals without experience and without training: In most companies, there is a shortage of AI brainpower and talent. In a survey conducted by PwC’s Digital IQ, only 20% of executives said their organizations had the necessary 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 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.

4. Inaccessible data and privacy protection: To train machine learning algorithms, you need massive, clean data sets with minimal bias. Most of this data is not ready for consumption because it is unstructured. These data contain sensitive information and are stored in a different processing system. As a result, most companies tend to invest heavily in creating an effective infrastructure to collect and store the data they generate and recruit talent capable of encrypting this information to make it usable and productive.

5. 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 so much complexity, those who want to bet on AI to take advantage of new business opportunities can start to disappear. Most companies that are falling behind in digital transformation have to revolutionize their entire infrastructure to adopt AI in a meaningful way. The outcome of AI projects can come a bit late, as data needs to be collected, consumed, and digested before the experiment bears fruit. Most entrepreneurs lack the requisite degree of flexibility, resources, and courage needed to invest in a large-scale machine learning project without collateral.

These are the five biggest 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 obstacles cannot stop AI from transforming the way businesses work. In case you need to harness the benefits of AI technology to develop a solution to increase your productivity, contact an experienced AI consulting firm.