AI Impact on Revenue, Opex, Capex Could be Significant, But Current Estimates are Too High

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.