Why Companies Are Failing at AI
Wed, April 21, 2021

Why Companies Are Failing at AI

The adoption of artificial intelligence has rapidly taken hold across businesses worldwide / Photo by: tiagozr via 123RF

 

The adoption of artificial intelligence has rapidly taken hold across businesses worldwide. A recent McKinsey Global Survey reported that 57 percent of organizations stated that they have embedded at least one AI capability into their standard business processes while another 30 percent reported piloting the use of AI. The most common AI capabilities deployed in these companies are machine learning, computer vision, and robotic process automation.

Microsoft’s “Accelerating Competitive Advantage with AI” report also tackled how businesses are integrating the technology. It showed that there will be more awareness and adoption of AI overall among businesses on a global scale in the next five years. In an interview, Microsoft’s UK COO Clare Barclay said, “Based on the progress we’re seeing, we believe that every company will be an AI company in five years. As organizations start to use or think about using [AI], we want to encourage more open dialogue on this topic.”

According to the Evening Standard, a local, free daily newspaper published in tabloid format in London, about 24 percent of businesses have an AI strategy while 96 percent of employees surveyed reported that their bosses are adding AI without consulting them on the technology. Unfortunately, this has fueled anxiety around the technology and concerns over job security. Barclay emphasized the need for open communication among the company heads and the employees on the subject. 

A similar survey conducted by tech giant Samsung showed that 51 percent of 5,250 people in the UK and Ireland feel AI will have a positive impact on society as a whole. However, around 90 percent of them feel it is too complex to understand. Nonetheless, reports showed higher rates of AI usage in more business functions than in any other industry, along with greater investment in AI and on overall value from using AI as shown by a study conducted by McKinsey & Company, the trusted advisor and counselor to many of the world's most influential businesses and institutions.

Half of AI Projects Fail

While the adoption of AI is rapidly growing in businesses across the world, most companies are not seeing enough progress with their AI projects and investments. A recent study by research firm IDC discovered that half of AI projects have failed for one out of four companies due to two major reasons: a lack of required skills and unrealistic expectations. Of the organizations that are using AI, only 25 percent of them have developed an “enterprise-wide” AI strategy.

The processes and a substantial number of projects initiated by these companies are doomed to fail. According to AI News, an online site that brings the latest in artificial intelligence news from around the world, Ritu Jyoti, program VP of Artificial Intelligence Strategies at IDC, stated that organizations should evaluate their vision, and at the same time, they need to transform their employees, processes, technology, and data readiness to make the most out of AI.

“For many organizations, the rapid rise of digital transformation has pushed AI to the top of the corporate agenda. However, as AI accelerates toward the mainstream, organizations will need to have an effective AI strategy aligned with business goals and innovative business models to thrive in the digital era,” Jyoti added. 

While the adoption of AI is rapidly growing in businesses across the world, most companies are not seeing enough progress with their AI projects and investments / Photo by: Aleksandr Davydov via 123RF

 

Not Much Success With AI So Far

Today’s companies have the knowledge, resources, and incentive to create effective strategies behind their AI implementations. Despite these capabilities, a lot of companies are still failing. TechRepublic, an online trade publication and social community for IT professionals, reported that one of the biggest mistakes these companies make is implementing technology for the sake of technology. It was reported that only 16 percent of the businesses are focusing on pain points and defining use cases before AI deployment. Not only does this result in failed AI initiatives but it is also a waste of time and money. 

Suman Nambiar, head of the strategy, partner alliances, and offerings at Mindtree, stated that while organizations are appreciating the need for data to train AI models, most of them still don’t understand the data infrastructures and architectures required to industrialize AI at scale. Research firm Gartner’s “Leverage Augmented Intelligence to Win with AI” report stated that businesses must develop agile and rapid innovation methodologies and experiment with multiple use cases to execute successful AI projects. 

Today’s companies have the knowledge, resources, and incentive to create effective strategies behind their AI implementations. Despite these capabilities, a lot of companies are still failing / Photo by: Daniil Peshkov via 123RF

 

Reports also showed that most companies using AI have yet to gain any value from their AI investments because they only see it as merely a “technology thing” instead of a business overhaul. An MIT Sloan Management Review and Boston Consulting Group’s survey showed that 7 out of 10 companies report little to no impact from their AI projects so far. According to Fortune, a global leader in business journalism, companies are also struggling with their data-crunching initiatives. This is because there has been an existing knowledge gap between having a data strategy and understanding one. 

While over 85 percent of organizations have a data strategy, 51 percent of large enterprises and 74 percent of smaller enterprises said they don't understand the data infrastructures necessary to deliver AI use cases. Also, some companies believe that AI applications lack practicality for their business. 

One of the key solutions to those problems is to use AI strategies to fulfill a specific need. Companies should identify a few key areas that could benefit from AI tools before finding the tools that fit those needs. This will determine if your business is ready for AI. 

Indeed, companies must thoroughly plan first before integrating AI into their businesses. They must consider the long-term, real-world ramifications of AI investments before making the leap.