AI Already is in Widespread Business Use

Perhaps contrary to some opinion, use of AI already is rather extensive in business operations.

Since many forms of machine learning are widely used for making recommendations, providing search results and assessing risk, while other forms of AI already are used for developing prototypes, it would not be surprising if “more” AI seems to be in commercial use than one might have thought. Common uses already include:

• Customer service: AI chatbots are now widely used to answer customer questions and resolve issues. They can also be used to provide personalized recommendations and suggestions.

• Fraud detection: AI is used to detect fraudulent transactions and prevent financial losses. This is done by analyzing large amounts of data to identify patterns that are indicative of fraud.

• Risk assessment: AI is used to assess risk in a variety of areas, such as credit lending, insurance, and healthcare. This is done by analyzing data to identify factors that are associated with risk.

• Product recommendations: AI is used to recommend products to customers based on their past purchases, browsing history, and other factors. This can help businesses increase sales and improve customer satisfaction.

• Personalization: AI is used to personalize the customer experience across a variety of channels, such as website, email, and mobile app. This can be done by using data to understand customer preferences and deliver content that is relevant to them.

• Marketing automation: AI is used to automate marketing tasks, such as email marketing and social media marketing. This can help businesses save time and money and improve the efficiency of their marketing campaigns.

• Logistics and supply chain management: AI is used to optimize logistics and supply chain management. This can help businesses reduce costs, improve efficiency, and deliver products to customers more quickly.

• Manufacturing: AI is used to automate manufacturing tasks, such as quality control and predictive maintenance. This can help businesses improve efficiency and productivity.

• Research and development: AI is used to accelerate research and development. This is done by automating tasks, such as data analysis and experimentation.

Also, fads develop for enterprises just like they do for consumers. Few indeed might be the ranks of enterprises that have not concluded they have to investigate use of artificial intelligence in their operations. 

Anyone familiar with the producing and taking of surveys knows results must always be filtered and compared with what one already knows, conditioned by the ways questions are asked and placed within the obvious realities of business politics. 

But it is not surprising that a recent survey conducted for S&P Global Market Intelligence found 69 percent of surveyed organizations have at least one AI project in production (“AI pioneers”), whereas 31 percent of respondents’ AI projects are still in pilot or proof-of-concept stages (“AI explorers”). As noted above, many business processes already embody AI and machine learning.

Some 28 percent of survey respondents cite reaching enterprise scale with AI projects widely implemented and driving significant business value. 

Also, since the easiest way to get any information technology project, product launch or expansion approved is to argue it “increases revenue,” it is hardly surprising that survey respondents say their generative AI investments will “increase revenue.” 

The other obvious reason for undertaking an IT project or change in business processes is that it “reduces our costs.” All other values are less important. 

So the S&P Global Market Intelligence survey finds respondents arguing that AI has shifted from a cost-saving measure to a revenue driver. 

. 

Of 5,400-plus responses received from over 1,500 survey respondents, 69 percent of responses 

regarding the motivations behind AI/ML projects cite revenue-focused drivers, as opposed 

to 31 percent that are cost-focused. 

source: S&P Global 

And, of course, there are many studies illustrating use cases for AI in areas ranging from customer service to manufacturing. 

Use Case	Study	Year	Publishing Venue
Customer service	Gartner	2022	"Gartner Says 80% of Customer Service Interactions Will Be Handled by Chatbots by 2022"
Fraud detection	IBM	2020	"AI Can Reduce Fraud Losses by Up to 90%"
Risk management	McKinsey	2021	"How AI Can Help Businesses Reduce Risk"
Product recommendations	Amazon	2020	"How AI Is Personalizing the Shopping Experience"
Personalized marketing	Experian	2019	"How AI Is Personalizing Marketing Campaigns"
Healthcare	University of Pennsylvania	2020	"AI Can Help Doctors Diagnose Skin Cancer More Accurately"
Manufacturing	Boston Consulting Group	2020	"How AI Can Transform Manufacturing"

What seems the case now is that generative AI has highlighted the many ways AI already is being used by businesses.