Why AI projects fail?
In this article for the IE Big Data club, IE IMBA student Margaret McLeod who previously worked at Booz Allen Hamilton's AI strategy team, shares her thoughts on why AI projects are failing.
Artificial Intelligence (AI) has undoubtedly become a huge buzzword for many organizations who are rushing to invest their limited resources in AI solutions to gain competitive advantages. Gartner reported in 2019 that 14% of global CIOs have already deployed an AI solution and of those who haven’t deployed any AI solutions yet, 48% cited that they plan to do so by 2019 or 2020[i]. While the growing number of AI investments sounds promising, the reality is the number of failed AI investments also continues to increase. In fact, experts estimate that nearly 85% of AI projects won’t succeed – meaning out of 20 AI projects only three will ultimately add value to an organization. MIT Management in partnership with Boston Consulting group released survey findings last year that confirmed the growing rate of failed AI projects. Their survey found that 7 out of 10 companies reported little to no impact from an AI investment[ii]. Why are these expensive investments failing at such high rates? Let’s take a look at a few reasons why.
Challenge 1: Cultural Barriers
We have all heard the phrase “culture eats strategy for breakfast.” Technical transformation always comes with challenges; however, it is next to impossible if an organization has not spent considerable resources developing a culture of innovation to support technical solutions. According to Gartner Report Predicts 2020: Artificial Intelligence – The Road to Production: “The cultural impact of introducing AI to both customers and employees has largely been underestimated…AI projects could fundamentally alter how work is performed and how decisions are made. Without well-thought-out change management efforts, the business users may not accept the AI results (or view them with suspicion) and dampen the overall AI adoption.”[iii]
Interesting Resources: Nine Essentials for Enabling An AI-Ready Culture and Business
Challenge 2: Demystify and Define
Studies have found that 42% of people don’t understand the benefits of AI solutions.[iv] When you have a large percentage of an organization who view a solution as unexplainable, this confusion oftentimes can translate into fear or unrealistic expectations. Either situation – employees viewing AI as a sign of the zombie apocalypse or employees expecting a solution will solve all the problems of the organization – poses a huge risk to the adoption of a solution. One way to combat this problem is to ensure all employees have been upskilled or reskilled in basic digital literacy. The more members of an organization who have awareness and a basic understanding of data, the more likely they are to understand how AI works.
Interesting Resources: Demystifying the Intelligence of AI
Challenge 3: Jumping to Solutions Before Understanding the Problem
We have all been in a meeting where within five minutes a solution is found and the meeting ends. While in some situations, efficiency can be good. When it comes to large technology investments for AI solutions, leaders of an organization need to be beware. While leaders oftentimes may feel as though they are best equipped to identify the right problem to solve with AI, more often than not they aren’t and they need input from employees of all levels to ensure they aren’t creating more problems by investing in a new technology. Additionally, to identify the right AI solution, one must first start by asking the right questions. Creating a formalized process where an organization identifies and selects opportunities based on a formalized rubric is critical to maximize the likelihood the right project testing ground is selected.
Interesting Resources: How To Identify The Best AI Opportunities For Your Business
[i] https://www.gartner.com/smarterwithgartner/3-barriers-to-ai-adoption/
[ii] https://sloanreview.mit.edu/projects/winning-with-ai/
[iii] https://www.gartner.com/en/documents/3975770/predicts-2020-artificial-intelligence-the-road-to-produc
[iv] https://www.gartner.com/smarterwithgartner/3-barriers-to-ai-adoption/
Written by Margaret McLeod