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If your company has yet to embrace AI, you are in a race against the clock. And by my reckoning, you only have three years left.
I am A.E. How do I reach 2024 as the deadline for adoption? My prediction – KungFU.A.I. Designed with consultant Paco Nathan – taking us into account that the turn of many futurists who show innovations usually have a 12 to 15 year window of opportunity, when a technology emerges and when it arrives. The issue of widespread adoption.
While AI can be traced back to the mid-1950s and machine learning in the late 1970s, the concept of deep learning was popularized by the “Alexnet” paper published in 2012. .
Although cloud computing was first introduced in 2006, it did not take off until 2010 or later. The rise of data engineering can also be traced back to the same year. The original paper for Apache Spark was released in 2010, and has become the foundation for many of today’s distributed data infrastructure.
In addition, the widely restricted establishment date of the concept of data science is 2009. Jeff Hammerbaker, D.J. Patil and others when it comes to gaining recognition for leading data science teams and will help define the practice.
If you do the math, those 2009-2012 dates put us within that 12 to 15 year window. And it sets a 2024 cutoff for companies hoping to gain a competitive advantage from AI.
You can still get the edge – if you work right now
If you look at the graph below – Everett Rogers Spread of innovations – You will get a sense of how those who are waiting to put AI into production will lose corners in the market. The red line here shows the sequential groups adopting the new technique while the purple line shows how the market share eventually reaches the level of saturation.
Source: Everett Rogers, Spread of innovations
A 2019 survey conducted by MIT Sloan Management Review and Boston Consulting Group clearly shows how the difference of innovative theory applies to AI. His research was based on a global survey of more than 20,000,000 executives, managers and analysts from various industries.
Once the AI understanding and answers to the adoption questions were analyzed, the survey respondents were assigned one of four different categories:
Pioneers (20%) These organizations have a deep knowledge of AI and incorporate it into their offerings and internal processes. They are trailblazers.
Investigators (30%) These organizations understand AI but are not deploying it beyond the pilot stage they are taking a more “look before you jump” approach.
Experiments (18%) These organizations are piloting AI without really understanding it. Their strategy is fake-do-you-do-it.
Passives (32%) These organizations have very little understanding of AI and will probably miss the opportunity to benefit from it.
The 2020 survey, which uses the same questions and methodology, gives even more insight into how officials accept AI. 87% believe that AI will benefit their companies for others. However, only 59% of companies have an AI strategy.
MIT and BCG 2020 survey responses have been compared since the survey began in 2017, with a growing number of executives acknowledging that competitors are more likely to use AI. Yet only one in 10 companies is using AI to generate significant financial gain.
I expect this gap between leaders and laggards to widen, giving your company one last chance to take action before 2024 (if it hasn’t already).
What it takes to realize success
2020 data from MIT and BCG show that companies focused on the early steps of adopting AI (data, talent and a strategy are in place) will have a 21% chance of becoming a market leader. When companies begin to revisit AI solutions with their organizational users (effectively adopting AI and applying it to multiple use cases) the chance increases to 39%. And people who can organize macro and micro interactions between humans and machines (both sharing knowledge and shaping interactions smartly) will have a 73% chance of market leadership.
Given the success predictions of MIT and BCG, McKinsey & Co. in particular have broken down how AI integration affects revenue in this 2020 chart.
Source: McKinsey & Company Global Survey, 2020
While the ROI for AI integration may be immediate, this is not usually the case. According to MIT and BCG’s 2019 figures, only two of the three companies that have made some investments in the AI (Investigators and Experimenters) report have benefited in three years. The state improves in three out of five when it includes companies that have made significant investments in AI (pioneers).
2020 MIT / BCG data builds on this, claiming companies that use AI to make extensive changes to many business processes are likely to experience 5X greater financial gain. Vs.
So where do you live in 2024? On the way to cutting AI rewards, or mourning that you will lose the opportunity to gain in the market?
Steve Meyer is a co-founder and head of growth at AI Services Company KUNGFU.AI.
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