Some Will Benefit from AI More than Others

Though there is as yet no consensus about the degree of artificial intelligence impact on various industries, many could agree that some industries will benefit more, either in terms of process cost reduction or operating costs; others less so. 

Probably nobody would be surprised if financial services wound up seeing direct benefits, as has been the case in the past. But many would guess that healthcare will be a bigger beneficiary from AI than has traditionally been the case for information technology  investments. 

As with so many other metrics, it appears connectivity services and data centers are somewhere in the middle of industries where it comes to the degree of process automation and improvement. 

Industry	Impact on Operating Costs	Reasons
Healthcare	High	AI can automate many tasks in healthcare, such as medical record keeping, diagnosis, and treatment planning. This can free up healthcare workers to focus on more complex tasks and provide better care to patients. AI can also help to reduce the cost of healthcare by improving efficiency and reducing errors.
Financial Services	High	AI can automate many tasks in financial services, such as fraud detection, risk assessment, and investment management. This can free up financial professionals to focus on more complex tasks and provide better service to clients. AI can also help to reduce the cost of financial services by improving efficiency and reducing errors.
Manufacturing	High	AI can automate many tasks in manufacturing, such as assembly line production, quality control, and inventory management. This can help manufacturers to improve efficiency and reduce costs. AI can also help manufacturers to produce higher quality products by identifying and correcting defects early on.
Retail	High	AI can automate many tasks in retail, such as customer service, inventory management, and fraud detection. This can help retailers to improve efficiency and reduce costs. AI can also help retailers to increase sales by personalizing the shopping experience for customers.
Transportation	High	AI can automate many tasks in transportation, such as driving, traffic management, and logistics planning. This can help transportation companies to improve efficiency and reduce costs. AI can also help transportation companies to improve safety by reducing human error.
Telecommunications	Medium	AI can automate many tasks in telecommunications, such as network management, customer service, and fraud detection. This can help telecommunications companies to improve efficiency and reduce costs.
Data Centers	Medium	AI can automate many tasks in data centers, such as server provisioning, cooling system management, and anomaly detection. This can help data center operators to improve efficiency and reduce costs. AI can also help data center operators to improve the reliability and security of their data centers.
Construction	Low	AI can be used to automate some tasks in construction, such as design and planning. However, the construction industry is very labor-intensive, and it is not clear how much AI can automate.
Agriculture	Low	AI can be used to automate some tasks in agriculture, such as crop monitoring and harvesting. However, the agriculture industry is very weather-dependent, and it is not clear how much AI can automate.
Education	Low	AI can be used to personalize learning and provide feedback to students. However, the education industry is very people-centric, and it is not clear how much AI can automate.

In many industries, process improvements are expected to provide the clearest and perhaps most-significant financial benefits. Perhaps more interesting are ways AI can boost revenue, even when AI does affect both operating costs by streamlining processes.

Industry	Impact on Core Business Models	Revenue Impact
Healthcare	AI is transforming healthcare by automating tasks, improving diagnostics, and developing new treatments.	Large: AI-powered systems can help healthcare providers improve efficiency and accuracy, while also reducing costs. This could lead to lower healthcare costs for consumers and businesses. AI could also lead to new treatments.
Financial Services	AI is being used to automate tasks, detect fraud, and make better investment decisions.	Large: AI-powered systems can help financial institutions improve efficiency and reduce costs, while also generating new revenue streams. For example, AI-powered chatbots can provide customer service and answer questions 24/7, while AI-powered trading algorithms can generate profits for financial institutions.
Manufacturing	AI is being used to automate tasks, improve quality control, and optimize production lines.	Large: AI-powered systems can help manufacturers improve efficiency and reduce costs, while also producing higher quality products. For example, AI-powered robots can perform repetitive tasks on assembly lines, while AI-powered quality control systems can identify defects in products before they reach consumers.
Retail	AI is being used to personalize shopping experiences, recommend products, and optimize inventory levels.	Large: AI-powered systems can help retailers improve customer satisfaction and sales, while also reducing costs. For example, AI-powered chatbots can provide personalized recommendations to customers, while AI-powered inventory management systems can help retailers avoid stockouts and overstocking.
Transportation	AI is being used to develop self-driving cars, improve traffic management, and optimize supply chains.	Large: AI-powered systems can help transportation companies improve efficiency and reduce costs, while also offering new services to customers. For example, self-driving cars could revolutionize the taxi and trucking industries, while AI-powered traffic management systems could reduce congestion and travel times.
Telecommunications	AI is being used to improve network performance, detect fraud, and develop new services.	Medium: AI-powered systems can help telecommunications companies improve efficiency and reduce costs, while also generating new revenue streams. For example, AI-powered systems can be used to optimize network traffic and detect fraud. AI can also be used to provide personalized recommendations for customers.
Data Centers	AI is being used to improve energy efficiency, detect anomalies, and automate tasks.	Medium: AI-powered systems can help data center operators improve efficiency and reduce costs. For example, AI-powered systems can be used to optimize cooling systems and detect potential problems. AI can also be used to automate tasks, such as provisioning and managing servers.

That differential pattern of impact has been seen in prior eras of information technology investment as well. Of course, the industry most affected by IT is the IT industry itself, which is the supplier of the platforms and tools. In other industries, the financial services industry virtually always ranks high on any list of IT adopters, early IT adopters and estimated IT impact. 

Industry	Revenue Impact	Operating Cost Impact	Reasons
Technology	High	High	Information technology is the core business model of the technology industry, so new IT has had a profound impact on revenue, as that is the primary product. Technology firms also are early users of IT in most ways.
Financial Services	High	High	IT enabled the development of new financial products and services, as well as new ways to deliver them. This has led to increased revenue for many financial services companies. Additionally, IT has helped financial services companies to automate tasks and improve efficiency, which has reduced operating costs.
Retail	High	Medium	IT has also had a significant impact on the retail industry. IT has enabled the development of new retail channels, such as e-commerce. This has led to increased revenue for some retailers. Additionally, IT has helped retailers to automate tasks and improve efficiency, which has reduced operating costs.
Telecommunications	Medium	Medium	IT has also had a significant impact on the telecommunications industry. IT has enabled the development of new telecommunications services, such as mobile internet and broadband. This has led to increased revenue for many telecommunications companies. Additionally, IT has helped telecommunications companies to automate tasks and improve efficiency, which has reduced operating costs.
Data Centers	Medium	Medium	IT has also had a significant impact on the data center industry. IT has enabled the development of new data center services, such as cloud computing and big data analytics. This has led to increased revenue for many data center companies. Additionally, IT has helped data center companies to automate tasks and improve efficiency, which has reduced operating costs.

As always, other industries, such as agriculture and education, have benefitted more modestly from applied IT.

Has 5G "Failed?" Did 3G and 4G Fail?

It is not hard to find critics of 5G who argue the industry over-promised and under-delivered. But the same could be said about 3G and 4G as well: many futuristic use cases did not develop, even if “possible.”

Consider some predicted innovations that eventually are emerging after 20 years from the time they were deemed by some to be possible for 3G networks. 

Prediction	3G	4G	5G
Self-driving cars	No	No	Not yet, but has the potential to enable them
Augmented reality	No	Limited	Starting to emerge
Virtual reality	No	Limited	Starting to emerge
Mobile streaming	Yes	Yes	Yes
Mobile gaming	Yes	Yes	Yes
Mobile commerce	Yes	Yes	Yes
Internet of Things (IoT)	Limited	Growing	Rapidly growing
Cloud computing	Limited	Growing	Rapidly growing

On the other hand, it also can be argued that new apps, use cases and widespread user behaviors did arise during the 3G and 4G eras. 

Generation	New use cases	New apps	New behaviors
3G	Mobile streaming	YouTube, Netflix	Watching videos on the go
3G	Mobile gaming	Angry Birds, Clash of Clans	Playing games on the go
3G	Mobile commerce	Amazon, eBay	Shopping online on the go
3G	Turn by turn navigation	Google Maps, Waze	Navigation apps
3G	Social media	Facebook	Real-time updates
3G	Mobile web site access	Mobile versions of web sites	“Mobile” web
4G	Mobile video conferencing	Skype, WhatsApp	Video chatting with friends and family on the go
4G	Full web site experience	Every app authored for mobile use	Mobile web a substitute for desktop web
4G	Mobile apps	Substitute for web	App-first user experience

4G High-Def Streaming HD Videos   Mobile entertainment

Some might argue the discrepancies in pace of innovation were almost certainly connected to the mismatch between mobile platform bandwidth and app requirements; the loosely-coupled nature of app development in an internet protocol context; the pace of device innovation and the emergence of revenue models. 

One might note the same issue with fixed networks. Some use cases and apps were not possible when relatively assured bandwidth was at 56 kbps; 1 Mbps or 3 Mbps per user. When assured bandwidth grew to 10 Mbps per user or 100 Mbps per user or higher, lots of use cases then were possible. 

So some might argue that 3G, 4G and 5G fundamentally are about ensuring higher levels of user bandwidth on a routine basis. Then developers can create with those assumptions in place. 

Loosely-coupled innovation also means that, for the most part, it is not the platform suppliers (mobile operators) who create the apps, but third parties. So “what might be possible” only becomes a commercial reality when third party developers decide the addressable market is big enough (one can assume X bandwidth, routinely), devices can support the apps, consumers find value and revenue models are developed. 

So even a casual listing of major innovation during the internet era would note that major innovation that affects economics, industries, firms and people largely happens “other places” than in the core computing and connectivity infrastructure, in the same way that the value of products and services using electricity, roads, fresh water, waste disposal, air and sea transport, education, language, numeracy, nutrition or health practices are largely produced by users of those infrastructures, and not by the providers of infrastructure. 

By design, app creation is separated from the connectivity, transport and computing functions IP-based apps require. Proponents of 3G, 4G and 5G networks can create new connectivity platforms, but it is third parties who then create most of the apps. 

“Over-promising” is a political reality dictated by the need to convince governments to allocate more spectrum (capacity) for the next generation of mobile networks. 

Innovation	Use Cases	Products	Firms
Web browser	Accessing and displaying web pages	Netscape Navigator, Internet Explorer, Chrome, Firefox	Mosaic Communications, Microsoft, Google, Mozilla
Search engine	Finding information on the web	Google, Bing, Yahoo! Search	Google, Microsoft, Yahoo!
Email	Sending and receiving electronic messages	Gmail, Outlook, Yahoo! Mail	Google, Microsoft, Yahoo!
E-commerce	Buying and selling goods and services online	Amazon, eBay, Alibaba	Amazon, eBay, Alibaba
Social media	Connecting and sharing information with others online	Facebook, Twitter, Instagram	Facebook, Twitter, Meta
Cloud computing	Delivering computing services over the internet	Amazon Web Services, Microsoft Azure, Google Cloud Platform	Amazon, Microsoft, Google
Mobile internet	Accessing the internet from mobile devices	iPhone, Android	Apple, Google
Artificial intelligence	Developing machines that can learn and perform tasks like humans	Google AI, Amazon AI, Microsoft AI	Google, Amazon, Microsoft

So none of the next-generation platforms actually “failed.” New apps, use cases and user behaviors did develop. Developers needed more routine bandwidth, and got it. So 5G eventually will lead to new use cases. But it will take a bit of time, and might not match what proponents have been suggesting could happen.