Earn Money With Ai – This series of columns looks at the biggest data and analytics challenges facing modern companies and takes a deep dive into successful use cases that can help other organizations accelerate their progress in AI.
At the beginning of each year, forecasts, plans, and surveys arrive from consulting firms. When it comes to artificial intelligence, some recent surveys suggest that companies are only planning to spend serious money on AI in 2022 – they are already making good money from the technology.
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A little context might help. Despite some AI successes, one of the challenges in recent years has been that technology-related projects have often lacked sufficient economic returns. In a 2019 survey by MIT Sloan Management Review and Boston Consulting Group AI, for example, 7 out of 10 companies reported minimal or no value from their AI investments. One of the reasons for poor income is that few projects have been used in production; they were too often research exercises. Sure, production deployments can be difficult, as they generally require integration with existing systems and processes, reskilling of workers, and the ability to scale AI technology.
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A few years later, things are starting to change. In a 2022 survey of senior data and technology executives by NewVantage Partners (where Randy Bean is CEO and co-founder, and Tom Davenport is a partner), 92% of large companies reported that they are realizing gains on their investments data and AI. . This was a significant increase from 48% in 2017. The same percentage (92%) said they are increasing investments in data and AI, the same percentage as last year. Twenty-six percent of companies have AI systems in widespread production – more than double the 12% in last year’s survey. The survey also asked respondents if their organizations were data-driven, and only 26% said they were. However, this doesn’t seem to be stopping them from advancing AI.
NewVantage survey respondents represent mostly North American companies. But other surveys suggest that companies around the world are also registering more value with AI. The State of AI survey by Deloitte (where Tom is a senior consultant for the AI practice), released in mid-2021, found that two types of companies are getting value from their investments. 28 percent of survey respondents were classified as
— companies reporting high business results and a relatively high number of production AI deployments (six on average). This group has largely identified and adopted key practices associated with the strongest AI outcomes, including having an AI strategy, building an ecosystem around AI, and implementing organizational structures and processes (such as operations machine learning, or MLOps) to keep AI running. . binary.
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. They reported high results but a lower number of deployments. They have also adopted capabilities and behaviors that AI has succeeded in, but on fewer projects. They were not to the same scale as transformers.
Still, this is more than half of global respondents who reported positive business outcomes from AI. As we’ve noted, it’s difficult or impossible to take advantage of AI without using it, but these results suggest that you don’t need a lot of deployment to get value.
The McKinsey 2021 global survey on AI also found that the adoption and value of AI is increasing. McKinsey found that the number of companies that reported adopting AI in at least one function increased to 56%, up from 50% in 2020. More importantly, the survey also shows that the economic return of AI is growing. The share of respondents reporting at least 5% of earnings (EBIT) attributable to AI increased to 27%, up from 22% in the previous survey. We’re not sure how survey respondents calculate the percentage of gains attributable to AI, but their answers suggest a high value.
Respondents to the McKinsey survey also reported significantly greater cost savings from AI than before in all functions, with the biggest improvements coming in product and service development, marketing and sales, and corporate strategy and finance.
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Echoing the Deloitte survey, McKinsey found that progressive AI practices are being rewarded. Companies that saw the biggest increases in AI revenue were not only following successful practices, including MLOps, but also spending more effectively on AI and leveraging cloud technologies to a greater extent.
A survey by IBM provides some insight into the impact of the COVID-19 pandemic on AI adoption, with a particular focus on automation-oriented technologies. It found that 80% of companies are already using some form of automation technology or are planning to do so in the next year. Just over a third of organizations surveyed said the pandemic has influenced their decision to adopt and use automation as a means to improve productivity. Respondents to the IBM survey were IT professionals, and may have influenced the results; Automation of IT processes (known as AI for IT operations, or AIOps) is a common use case for the technology.
We should also mention an interesting 2021 survey by the MIT Sloan Management Review and the Boston Consulting Group that tried to assess not the monetary benefits of AI but its cultural enhancement. As no one (as far as we know) has asked these types of questions before, we cannot compare with the past.
In that global survey, 58% of all respondents who participated in an AI implementation agreed that their AI solutions improved efficiency and decision-making among teams. The majority of that group (78%) also reported improved collaboration within teams. Are indicators of improved decision-making and collaboration culturally beneficial? We are not sure, but they can certainly transfer economic value.
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The survey also found that AI provides strategic benefits, but they have mostly accrued to companies that use AI to explore new ways to create value rather than reduce costs. Those who primarily used AI to create new value were 2.5 times more likely to feel that AI was helping their company competitively compared to those who said they were primarily using AI to improve existing processes; they were also 2.7 times more likely to agree that AI would help seize opportunities in nearby industries. It is easy to see how these characteristics can be turned into economic value.
For those who want the current “AI spring” to bloom forever, this is all great news. There is still considerable room for improvement in economic outcomes from AI, of course, and these surveys are only about subjective perceptions. The biggest remaining hurdle, according to a recent small survey of data scientists, is that most machine learning models are not yet deployed in production environments within organizations. AI companies and leaders still need to work on this issue.
However, the fact that so many business leaders who responded to so many surveys feel that their organizations are getting substantial value from AI is a definite improvement over time, and a strong indication that AI is here to stay in the business landscape. . .
Thomas H. Davenport (@tdav) is Distinguished Chair Professor of Information Technology and Management at Babson College, a visiting professor at Oxford’s Saïd Business School, and a member of the -MIT Initiative on the Digital Economy. Randy Bean (@randybeannvp) is an industry thought leader, author, and CEO of NewVantage Partners, a strategic consulting firm now a division of Wavestone, a global consultancy based in Paris. He is the author of There are multiple ways to make money with AI. Some people use AI to create and sell products or services, while others use AI to drive traffic to their websites or businesses. Still, others use AI to create and manage investment portfolios. One way to make money with AI is to create and sell products or services. This can be done by creating a new product or service that uses AI, or by incorporating AI into an existing product or service. For example, a company can use AI to create a new customer service chatbot or improve the accuracy of its product recommendations. Another way to make money with AI is to use AI to drive traffic to your website or business. This can be done by creating and promoting content that is relevant to your target audience, or by using AI to target potential customers with ads. For example, a website can use AI to generate targeted content that users are more likely to click on, or an e-commerce site can use AI to target potential customers with personalized product recommendations. Finally, you can also use AI to create and manage investment portfolios. This can be done by using AI to identify and invest in promising companies.
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Artificial intelligence (AI) is undoubtedly one of the hottest topics in the world of technology today. From self-driving cars to home assistants like the Amazon Echo, it seems everyone wants a piece of the AI pie.
But what does this mean for the average person? There is some way to make money with AI, or is there