5 Enormous Challenges That Artificial Intelligence Will Face In 2022
Amid COVID-19’s challenges, AI has become a vital resource for many businesses in 2020. Despite the economic downturn, 61% of high-performing companies increased their AI investments in 2020. As the recovery from the pandemic begins, more companies may turn to AI to help them enhance their digital transformation.
Artificial Intelligence (AI) is undeniably popular, and it’s a hot topic in tech circles! Many organisations, including Walmart, Microsoft, and Alibaba, have already implemented it in their business processes with great success. However, many real-world challenges remain, particularly for small and medium-sized businesses, in fully embracing Artificial Intelligence.
Some businesses say this is due to a lack of quality data, while others believe it is due to a lack of AI in their company culture. Other factors could include a lack of access to hiring AI experts or the infrastructure required to sustain high-level AI solutions.
Moving forward can overcome most of the challenges Artificial Intelligence companies experience in the AI market. As a result, this blog explores some of these challenges and how businesses might overcome them to integrate AI into their workplace culture.
Let’s Have A Look at Stats:
Let’s look at some statistics to see how artificial intelligence has impacted the world:
• Experts believe that artificial intelligence will increase a company’s overall productivity by 40%. Since 2000, the number of start-ups has increased.
Artificial Intelligence is a technology that even a layman is interested in because it has a tremendous tendency to disrupt every part of life.
5 Disruptive Challenges AI will face in 2022:
AI is a technology that can change industries such as manufacturing, healthcare, space exploration, and others. Artificial Intelligence is rapidly expanding and gaining popularity. The Role of AI in digital transformation has prompted some businesses to develop various AI applications such as robotics and self-driving automobiles.
However, it is essential to note that AI still faces many challenges. Here are some of the most typical challenges most businesses experience when implementing AI.
- Lack of Technical Knowledge
Deploying and integrating AI applications in the enterprise means the business must thoroughly understand current AI advancements and technologies and their drawbacks. The lack of technical know-how hinders the adoption of this niche sector in most organisations. To identify the obstacles in the deployment process, an enterprise needs a professional. Skilled human resources would also assist the team in tracking the return on investment of AI/ML solutions.
- Algorithm Bias:
Any AI system’s goodness or badness is determined by the amount of trained data. The truth is that organisations have been collecting insufficient data that is irrelevant and meaningless at all. As a result, they are undoubtedly biased and define the characteristics and behaviours of a handful of people who share something in common such as religion, gender, race, etc.
- Data Security and Storage
For learning and making intelligent decisions, most AI applications use a large amount of data. The disadvantage of using significant amounts of data is that it may cause enterprises to run out of storage space. Furthermore, data-driven automation in business operations may result in data security risks. Enterprises must adopt the best and most appropriate data management environment to apply AI. Not only will such a data management environment improve the protection of sensitive data, but it will also make it easier for enterprises to access siloed data for AI and ML projects.
- Rare and Expensive Workforce
Adoption and deployment of AI technologies need data scientists, data engineers, and other SMEs (Subject Matter Experts). In today’s market, these professionals are both costly and rare. Small and medium-sized businesses can’t hire enough people to meet the project’s needs because of their limited budget.
For most companies, replacing outdated infrastructure with traditional legacy systems remains a considerable challenge. The majority of AI-based solutions have a high processing speed. If your company has an extensive infrastructure and high-end processors, AI-based solutions will be able to run faster. Businesses considering implementing AI should consider creating a stable and adaptable infrastructure fully compatible with AI-based apps or solutions.
Wrapping Things Up:
Businesses will need to become more familiar with AI to understand how it works thoroughly. There’s no doubting that implementing AI in businesses may be difficult, and you’ll notice these challenges when you develop an AI strategy for your business. A step-by-step planned approach will simplify implementing AI to some extent.
As a top AI consulting firm in Columbus, we will help you accelerate your business growth. Contact our experts for help in implementing the best AI technology to improve your business processes and provide more value to your employees and customers.
We’re technology experts with a passion for bringing concepts to life. By leveraging a unique, consultative process and an agile development approach, we translate business challenges into technology solutions.
Author: Dash Technologies Inc
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