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If your company has yet to embrace AI, youre in a race against the clock. And by my calculations, you have just three years left.

How did I arrive at 2024 as the deadline for AI adoption? My prediction formulated with KUNGFU.AI advisor Paco Nathan is rooted in us noticing that many futurists J curves show innovations typically have a 12-to-15-year window of opportunity, a period between when a technology emerges and when it reaches the point of widespread adoption.

While AI can be traced to the mid-1950s and machine learning dates back to the late 1970s, the concept of deep learning was popularized by the AlexNet paper published in 2012. Of course, its not just machine learning that started the clock ticking.

Though cloud computing was initially introduced in 2006, it didnt take off until 2010 or so. The rise of data engineering can also be traced to the same year. The original paper for Apache Spark was published in 2010, and it became foundational for so much of todays distributed data infrastructure.

Additionally, the concept of data science has a widely reported inception date of 2009. Thats when Jeff Hammerbacher, DJ Patil and others began getting recognized for leading data science teams and helping define the practice.

If you do the math, those 20092012 dates put us within that 12-to-15-year window. And that makes 2024 the cutoff for companies hoping to gain a competitive advantage from AI.

If you look at the graph below from Everett Rogers Diffusion of Innovations youll get a sense of how those who wait to put AI into production will miss out on cornering the market. Here the red line shows successive groups adopting new technology while the purple line shows how market share eventually reaches a saturation level.

Source: Everett Rogers, Diffusion of Innovations

A 2019 survey conducted by the MIT Sloan Management Review and Boston Consulting Group explicitly shows how the Diffusion of Innovations theory applies to AI. Their research was based on a global survey of more than 3,000 executives, managers, and analysts across various industries.

Once the responses to questions around AI understanding and adoption were analyzed, survey respondents were assigned to one of four distinct categories:

Pioneers (20%) These organizations possess a deep knowledge of AI and incorporate it into their offerings and internal processes. Theyre the trailblazers.

Investigators (30%) These organizations understand AI but arent deploying it beyond the pilot stage. Theyre taking more of a look before you leap approach.

Experimenters (18%) These organizations are piloting AI without truly understanding it. Their strategy is fake-it-until-you-make-it.

Passives (32%) These organizations have little-to-no understanding of AI and will likely miss out on the opportunity to profit from it.

The 2020 survey, which uses the same questions and methodology, gives even greater insight into how executives embrace AI. 87% believe AI will offer their companies an advantage over others. Just 59% of companies, however, have an AI strategy.

Comparing the MIT and BCG 2020 survey responses to those since the surveys inception in 2017, a growing number of execs recognize that competitors are using AI. Yet only one in 10 companies are using AI to generate significant financial benefits.

I anticipate this gap between leaders and laggards will continue widening, making this your companys last chance to take action before 2024 (if it hasnt already).

MIT and BCGs 2020 data reveals that companies focused on the initial steps of AI adoption (ensuring data, talent, and a strategy are in place) will have a 21% chance of becoming a market leader. When companies begin to iterate on AI solutions with their organizational users (effectively adopting AI and applying it across multiple use cases) that chance rises to 39%. And those that can orchestrate the macro and micro interactions between humans and machines (sharing knowledge amongst both and smartly structuring those interactions) will have a 73% chance of market leadership.

Building upon MIT and BCGs success predictions, McKinsey & Company has specifically broken down how AI integration impacts revenue in this 2020 chart.

Source: McKinsey & Company Global Survey, 2020

While the ROI for AI integration can be immediate, thats not typically the case. According to MIT and BCGs 2019 data, only two out of three companies that have made some investment in AI (Investigators and Experimenters) report gains within three years. This stat improves to three out of five when companies that have made significant investments in AI (Pioneers) are included.

The 2020 MIT/BCG data builds upon this, claiming companies that use AI to make extensive changes to many business processes are 5X more likely to realize a major financial benefit vs. those making small or no changes to a few business processes.

So where will you be in 2024? On your way to reaping the rewards of AI, or lamenting that you missed an opportunity for market advantage?

Steve Meier is a co-founder and Head of Growth at AI services firm KUNGFU.AI.

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Deadline 2024: Why you only have 3 years left to adopt AI - VentureBeat