Beyond the Hype The 4 Biggest Barriers To AI Adoption

Beyond the Hype: The 4 Biggest Barriers to AI Adoption

AI adoption at several organizations across industries is speeding up like never before.

According to the McKinsey’s State of AI in 2021 Survey, AI adoption is continuing its steady rise. As per the report, 56 percent of all respondents report AI adoption in at least one function, up from 50 percent in 2020.

The report also found that AI adoption has helped organizations grow their bottom line and reduce business costs. Additionally, AI enhances speed, scalability of business operations, and consistency in processing information. According to a survey of business leaders by The AI Journal,

  • 72% of them feel positive about the role that AI will play in the future, with the number one expectation being that it will make business processes more efficient (74%).

  • 55% anticipate AI will help to create new business models.

  • 54% expect it to enable the creation of new products and services

Unsurprisingly, organizations across the sectors are increasing their investments in AI.

Though AI investments are rapidly rising, the fact remains that there are still a few significant challenges to organizations wishing to adopt intelligent, cognitive computing processes into their day-to-day business operations. What are such challenges? Let’s find out.

The 4 biggest barriers to AI adoption
  1. Lack of a strategic approach
  2. Lack of a skilled workforce
  3. Lack of structured data
  4. Fear of the unknown
Here are the four most significant barriers to AI adoption.  

1. Lack of a strategic approach

In a survey conducted by McKinsey & Company, only 18% of participating organizations mentioned that they have a clear strategy for sourcing data that enabled the implementation of artificial intelligence (AI). The survey also revealed that nearly 25% of organizations are yet to develop the core practices required to tap into the true potential of AI. Organizations need to map where possible AI solutions can be implemented. It would help them build a clear AI strategy. This is only possible when an organization has made efforts to digitize its core business processes. The survey also revealed that companies with digitized core processes have a higher chance of adopting AI practices. Organizations must invest in a well-thought-out plan to adopt AI successfully.

2. Lack of a skilled workforce

Research conducted by Juniper Networks revealed that 73% of organizations are struggling to prepare their existing workforce to work in sync with artificial intelligence (AI) systems. In fact, the research also found that 41% of the organizations are worried about digitally upskilling their existing workforce. This proves how important it is to lay a cultural foundation that embraces and acknowledges upskilling. Employees must be trained and upskilled to harness the power of AI and machine learning (ML) in the coming future.

3. Lack of structured data

AI and machine learning (ML) thrive on the availability of more significant volumes and data sources. Data is the new oil, and organizations have started to assimilate high volumes of data. But it becomes challenging to integrate and synthesize that data. Information collected is present across multiple applications and in numerous formats such as – images, videos, and audio. This makes it incredibly hard for organizations to derive meaningful learnings and results. The success of AI and machine learning (ML) initiatives is contingent on the quality and quantity of information available. Unfortunately, data is often incomplete or missing in several circumstances, making it even more challenging for organizations to adopt Artificial Intelligence.

4. Fear of the unknown

Organizations adopting artificial intelligence (AI) are able to quantify the benefits of AI partially. For example, an increase in revenue and time saved is easy to track, but factors such as customer experience are difficult to measure and define. A report by Gartner forecasts that by 2024, 50% of AI investments will be quantified and will have a direct correlation with ROI generated. The report by Gartner also concluded that 42% of participating organizations are yet to understand the capabilities and uses of AI. This makes it difficult for such organizations to adopt modern advanced technologies that leverage artificial intelligence (AI) and machine learning (ML).


Though there are few barriers to AI adoption, organizations adopting AI, overcome several such barriers with expert help and derive considerable benefits. Successful AI adoption with deep expertise would increase productivity and efficiency and help gain accurate insights to drive better business decisions. Technology companies like Carvewing are assisting organizations across sectors to leverage such world-class expertise and harness the power of AI to enhance their workflows, augment their customer experience and improve their business outcomes. Carvewing provides cutting-edge AI solutions that help prepare organizations to embrace the future dominated by technology.

Talk to our experts today for more information on how Carvewing can help your organization adopt AI successfully.

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