2024 is the time for Making Money with Gen-AI
Every year consulting companies make predictions, plans, and surveys. This white paper summarizes the published studies of several major consulting firms, because they indicate that companies are already making good money from Gen-AI. This is very encouraging because in 2019, 7 out of 10 companies reported minimal or no value from their AI investments. One of the reasons projects were research exercises, because they didn’t start by asking the right questions. This is a key point in “SAI6-LCoE™ Disruptive Innovation Leadership training, be curious, and ask Catalytic Questions till you’ve got the project goal ironed out.”
At any rate, in 2024, things are changing as survey by McKinsey, Deloitte, and New Vantage Partners showed 92% of large companies are achieving returns on their data and AI investments. Twenty-six percent of companies have AI systems in widespread production. The survey also asked respondents whether their organizations were data driven, and only 26% said they are.
Deloitte surveys in mid-2021, found that companies are getting value from their investments. They have largely adopted leading practices associated with the strongest AI outcomes, including having an AI strategy, building an ecosystem around AI, and putting organizational structures and processes in place (like machine learning operations, or MLOps) to keep AI on track.
McKinsey reported AI-value was increasing, and AI adoption in at least one function had increased to 56%, and AI’s economic return is growing. Respondents reported at least 5% of earnings (EBIT) that are attributable to AI and survey respondents’ responses suggest high value. Companies seeing the biggest earnings increases from AI were not only following practices that lead to success, including MLOps, but also spending more efficiently on AI and taking advantage of cloud technologies to a greater extent. 80% of companies are already using some form of automation technology or plan to do so over the next year. Just over a third of the organizations surveyed said that the pandemic influenced their decision to adopt and use automation as a means of improving productivity. 58% of all respondents who had participated in an AI implementation agreed that their AI solutions improved efficiency and decision-making among teams, and improved collaboration within teams.
The survey also found that AI yields strategic benefits, but they mostly accrued to companies that use AI to explore new ways of creating value rather than cutting costs. Those that used AI primarily to create new value were 2.5 times more likely to feel that AI is helping their company competitively compared with those that said they are using AI primarily to improve existing processes; they were also 2.7 times more likely to agree that AI helps capture opportunities in adjacent industries. It’s easy to see how these traits could turn into economic value.
For those who want the current “AI spring” to bloom forever, this is all great news. There is still substantial room for improvement in the economic returns from AI, of course, and these surveys tap only subjective perceptions.
According to a recent data scientist survey, the majority of machine learning models are still not deployed in production environments within organizations. This relates to the DYI syndrome. Big pharma has used AWS and Azure to speed up the creation of new FDA-approved drugs Companies and AI leaders still need to work out how to use the cloud, where MLOps has been “solved” for several years.
Still, many business leaders responding to so many surveys on the topic feel that their organizations are capturing substantial value from AI. This is a definite improvement over the recent past, and a strong sign that AI is here to stay, and Gen-AI will increase its dominance in the business landscape.
