Thursday, July 13, 2023

AI Will Have Financial Implications, But How Much?

Estimates of AI impact on almost any industry are likely too optimistic at the moment. Using only studies by McKinsey & Company on "Insurance 2030: The impact of AI on the future of insurance;" HubSpot’s  "How AI Will Revolutionize the Future of Business;" and Gartner’s: "The Top 10 Strategic Technology Trends for 2022,” financial impact could range from a low of five percent to a high of 30 percent changes by 2030, with total impact therefore implied at levels as low as 50 percent and as high as 100 percent.


That seems extremely unlikely over a period spanning less than seven years. Keep in mind most forecasts looking at AI will tend to exclude underlying firm or industry growth rates, and suggest incremental additional effects due specifically to AI.


Outcome or Function

Impact

Estimate

Study by

Revenue

Increased by 10-20%

$100-200 billion

McKinsey & Company

Operating cost

Decreased by 5-10%

$50-100 billion

McKinsey & Company

Capex

Increased by 5-10%

$50-100 billion

Gartner

Marketing cost

Decreased by 5-10%

$25-50 billion

HubSpot

Customer service and support cost

Decreased by 10-20%

$50-100 billion

McKinsey & Company

Research and development

Increased by 20-30%

$25-50 billion

Gartner


As always, it will be difficult to assess the specific impact of AI enhancements unless all other parts of a business remain the same. That is unlikely ever to happen. Firms will make acquisitions, sell assets, make operating cost improvements, add new product lines and adjust distribution and pricing strategies.


It will be difficult to isolate AI impact from all the other changes that could happen between now and 2030, in any firm or industry.


There arguably is much-less disagreement about what use cases could drive changes in the near term.


  • Automated customer service: AI-powered chatbots are being used to answer customer questions and resolve issues 24/7. This can free up human customer service representatives to focus on more complex issues, and it can also improve customer satisfaction.

  • Predictive analytics: AI is being used to analyze customer data to identify patterns and trends. This information can then be used to predict customer behavior, which can help connectivity providers to target their marketing efforts more effectively.

  • Self-optimizing networks: AI is being used to optimize network performance in real time. This can help to improve the quality of service for customers, and it can also help to reduce network costs.

Many believe the promise of artificial intelligence is its ability to improve firm ability to create new products faster, boost customer satisfaction, lower operating costs and perhaps optimize capital investments. 


But most of the current estimates are likely off by two to three orders of magnitude. According to Statista, the estimated total U.S. communications service revenue in 2030 is $356.7 billion. The estimate for 2023 is $332.40 billion. 


But estimates for AI impact in the U.S. communications services industry by some forecasters suggest more than a 100-percent impact (higher revenues, lower costs) between 2023 and 2030. Many would suggest that is extremely unlikely to happen. 


In principle, AI could aid connectivity providers in optimizing their current business models while enabling entry into new lines of business. That could theoretically be quite impactful if AI allows connectivity providers to innovate within the context of historical capex and opex levels. 


In other words, could AI allow entry into new lines of business without upsetting traditional levels of capital investment or operating cost, at the same time limiting the need to increase traditional leverage ratios? 


All that matters as it arguably has been the inability to accomplish innovation without worsening those parameters that has scuttled connectivity provider movement into new lines of business and roles in the value chain. 


While perhaps only suggestive, many analysts believe AI as applied to connectivity businesses could have hundreds of  billions to trillions of dollars in industry impact by 2030. 


Category

Description

Forecast

New products

AI can be used to develop new products and services, such as personalized recommendations, predictive maintenance, and virtual assistants.

Global market for AI-powered telecom products and services is expected to reach $38.8 billion by 2031. (Source: IDC)

Reduced capex

AI can be used to automate tasks, such as network configuration and troubleshooting. This can lead to significant savings in capital expenditures.

AI-driven automation could save telecom providers $1.2 trillion in capex by 2030. (Source: McKinsey)

Reduced opex

AI can be used to improve efficiency, such as by optimizing network traffic and reducing churn. This can lead to significant savings in operating expenses.

AI-driven improvements in efficiency could save telecom providers $200 billion in opex by 2030. (Source: McKinsey)

Boosted revenues

AI can be used to increase customer engagement, such as by providing personalized offers and recommendations. This can lead to increased revenues.

AI-powered customer engagement could generate an additional $1.4 trillion in revenues for telecom providers by 2030. (Source: McKinsey)


The point is that we probably have little idea how much impact AI could have for connectivity service providers. The impact arguably is far less than some presently suggest. 


Benefit

Global forecast

U.S. forecast

Source

New products

$1.2 trillion in new revenue by 2030.

$300 billion in new revenue by 2030.

McKinsey

Reduce capex or opex

$700 billion in cost savings by 2030.

$200 billion in cost savings by 2030.

McKinsey


Much the same likely can be said about AI impact for data center and hyperscale cloud “computing as a service” suppliers. According to Statista, the global revenue of data centers and hyperscale “cloud computing as a service” providers in 2023 is estimated to be $342.10 billion.


According to a report by Allied Market Research, the global data center and hyperscale cloud computing as a service market is expected to reach $585 billion by 2030. 


If AI has $1.9 trillion impact by 2030, then AI impact would be about three times larger than total revenues for those businesses globally. Again, the possible AI impact is unlikely to happen. 

```

Benefit

Global forecast

U.S. forecast

Source

New products

$100 billion in new revenue by 2030.

$30 billion in new revenue by 2030.

McKinsey

Reduce capex or opex

$500 billion in cost savings by 2030.

$150 billion in cost savings by 2030.

McKinsey

Boost revenues

$500 billion in additional revenue by 2030.

$150 billion in additional revenue by 2030.

McKinsey



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