Foundational Barriers to AI

Interesting ideas from surveys by McKinsey.    About value of AI at scale.  Foundational changes to make it work.   I take it somewhat differently.  This was the same way that earlier attempts at AI suffered in application.   It worked well for small focused contexts.   AI even then  provided some of the foundation for current machine learning.  We used it for adding to learning from classical statistics and optimization technologies.  Machine learning is very useful today, should be broadly practiced against tough problems.  Integrated well with other methods to make it most useful.

AI adoption advances, but foundational barriers remain
Survey respondents report the rapid adoption of AI and expect only a minimal effect on head count. Yet few companies have in place the foundational building blocks that enable AI to generate value at scale.

Survey respondents report the rapid adoption of AI and expect only a minimal effect on head count. Yet few companies have in place the foundational building blocks that enable AI to generate value at scale.

The adoption of artificial intelligence (AI) is rapidly taking hold across global business, according to a new McKinsey Global Survey on the topic.1 AI, typically defined as the ability of a machine to perform cognitive functions associated with human minds (such as perceiving, reasoning, learning, and problem solving), includes a range of capabilities that enable AI to solve business problems. The survey asked about nine in particular,2 and nearly half of respondents say their organizations have embedded at least one into their standard business processes, while another 30 percent report piloting the use of AI. Yet overall, the business world is just beginning to harness these technologies and their benefits. Most respondents whose companies have deployed AI in a specific function report achieving moderate or significant value from that use, but only 21 percent of respondents report embedding AI into multiple business units or functions. Indeed, many organizations still lack the foundational practices to create value from AI at scale—for example, mapping where their AI opportunities lie and having clear strategies for sourcing the data that AI requires.

One critical factor of using AI effectively, the results confirm, is an organization’s progress on transforming the core parts of its business through digitization. At the most digitized firms,3 respondents report higher rates of AI usage in more business functions than their peers, along with greater investment in AI and greater overall value from using AI. Another foundational challenge with AI is finding skilled people to implement it effectively. Many respondents say their organizations are addressing the issue by taking a diversified approach to sourcing talent. On the whole, despite reasonable concerns about AI being used to automate existing work, respondents tend to believe that AI will have only a minor effect on overall company head count in the coming years.
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