Artificial Intelligence and its financial benefits

Artificial Intelligence and its financial benefits: More than 70% of executives see it as an opportunity for their business, but only 10% of organizations achieve significant financial benefits from it, in particular, those who use multiple forms of human-machine learning.

A recent study by MIT Sloan Management Review in conjunction with Boston Consulting Group (BCG) reveals that the financial benefits of AI are greatly amplified when organizations develop multiple and effective ways for humans and artificial intelligence to learn together.

According to this study, despite increased investment and activity, only 10% of organizations are achieving significant financial benefits with artificial intelligence. The study highlights the often underestimated role of mutual human-machine learning in generating value from AI. Those companies that rely on multiple types of interaction and feedback between humans and artificial intelligence are 6 times more likely to amplify their success with AI.

The study, “Expanding the Impact of AI with Organizational Learning,” is based on a survey of more than 3,000 managers in 29 industries in 112 countries and in-depth interviews with expert leaders. It also includes a four-year longitudinal examination of AI adoption across industries and a variety of case studies. The authors’ analysis found that there are multiple fundamental steps and process improvements that enable companies to generate value with AI, but ultimately companies derive the greatest value when mutual human-machine learning occurs.

“This research reinforces the importance of applying artificial intelligence to generate great value across industries. There are companies that clearly understand how to succeed in their businesses, but others are facing difficulties in taking the necessary steps to make it happen,” said Cristián Carafí, Managing Director and Partner at BCG.

The study also highlights the investments organizations are making to maximize their value:

Building foundational capabilities (infrastructure, talent and AI strategy) increases the probability of achieving significant benefits by 19%.

Scaling AI across different use cases and going beyond automation increases the likelihood by another 18%.

Achieving organizational learning with artificial intelligence (leveraging multiple modes of human-machine interaction) and building feedback loops between humans and AI increases that likelihood by another 34%.

Organizations that learn with AI share three essential characteristics:

1 – They facilitate systematic and continuous human-machine learning.

2 – They develop multiple forms of human-machine interaction.

3 – They change to learn and learn to change.

Organizations that systematically invest in these activities are 73% more likely to achieve significant impact with artificial intelligence.

“AI applications in isolation can be powerful, but we found that organizations leading with AI have not changed processes to use it.  Instead, they have learned with AI to change processes. The key is not to teach the machines, or even learn from the machines, the key is to learn with the machines, systematically and continuously,” says report co-author Sam Ransbotham.

Organizational learning with AI demands builds on and drives significant organizational change. Additional data from the study reveals that as of 2020:

  • 70% of global executives surveyed understand how AI can drive business value, a 57% increase over 2017.
  • 59% of global executives surveyed have an AI strategy, an increase of 39% over 2017.
  • 57% of global executives surveyed say their companies are testing or ramping up AI, a growth of 46%.
  • A growing number of companies recognize a business imperative to improve their AI competencies and data infrastructures.
  • Despite these trends, only 1 in 10 companies generate significant economic benefits from AI.

“The most critical value driver of artificial intelligence is not just the algorithms or the technology, it’s the human in the equation,” says report co-author Shervin Khodabandeh. “We continue to see that despite more companies investing in AI technologies and launching initiatives, only a small fraction derive significant value. What this select group does well is that they create systems that are integrated by artificial intelligence and people, where AI learns from humans and humans learn from AI. And the more different ways the two learn from each other, the more value you can get.”

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