Artificial Intelligence in Business


Artificial Intelligence in Business

The use of artificial intelligence in business is very important. Recent surveys shows that the companies are growing in experimenting with AI. For example, in April 2023 254 technology firms’ leaders including professional services firm EY found that 90% of respondents are exploring AI platforms such as ChatGPT and Bing Chat and 80% are planning to increase their investments in AI in the coming year.

Executives have indicated to EY researchers and others that they're looking at AI to increase efficiencies, boost productivity, lower costs, create competitive advantages and changing market expectations. They've also credited advances in AI tools for making the technology more accessible to businesses and organizations.

Enterprise leaders said data security, process automation and customer care are the top areas where their companies have been applying AI. Natural language processing (NLP) is at the forefront of AI adoption.

Here are 15 top applications of Artificial Intelligence in the business.

1. AI-enabled innovations, products and services

Businesses are harnessing the potential of artificial intelligence; some are already using the technology for innovation and create new products and services.

Amazon Alexa and other similar virtual assistants are some of the most well-known examples.

The businesses are also employing machine learning and other AI technologies to improve the quality of the speaker's voice and image.

2. Automating routine work

Businesses for years have used AI to automate many manual tasks, such as data entry.

3. AI for levelling up workers

Ms. Kavita Ganeshan, an AI advisor, strategist and founder of consultancy Opinosis Analytics, cited Grammarly and similar services that use AI to note or catch misspellings in the text. It will correct grammar and offer preferred phrasings to improve a user's writing.

Others noted that generative AI brings even more aid to workers, who with little or no experience can use the tool to write software code, design a logo or craft a marketing strategy.

4. AI as a creative force

Artificial intelligence is now capable of creating compositions of all kinds, including visual art, music, poetry and prose, and computer code.

5. Accessing and organizing knowledge via AI

Accessing and organizing knowledge is another area where AI -- in particular, generative AI -- is demonstrating its potential to organizations and their workers.

6. AI for optimization

It stretches in industries and business functions.

AI-based business applications can use algorithms and modelling to turn data into actionable insights. Business can optimize a range of functions and business processes -- from worker schedules to production and product pricing. AI systems can use data, identify bottlenecks and offer optimized options to implement.

7. Higher productivity and more efficient operations

Top business organizations are adopting AI to boost productivity and generate more efficiencies, said Mr. Sreekar Krishna, U.S. leader of AI at professional services firm KPMG.

He said AI can be plugged into many processes that require human labour either fully or partially perform that process --- faster and accurately.

8. More effective learning and training through AI

Many organizations are using or exploring how to use intelligence software to improve learning.

Intelligent tools can be used to customize educational plans to each worker's learning needs and understanding levels based on their experience and knowledge. Because of this organizations implement more effective training programs.

9. AI as coach and monitor

In a related application, organizations are deploying AI-powered systems that coach employees as they work. The technology experts explained, it has the capability to monitor and analyse actions in near real time and provide feedback, thereby coaching or guiding workers through the process.

For example, many logistics and transportation companies use systems featuring cameras, eye-tracking technology and other AI algorithms to monitor for distracted driving, alerting workers to the problematic behaviour and offering corrective actions.

10. Decision support

A similar application of AI in the enterprise is the use of an intelligent decision support system (DSS). These systems sort and analyse data and based on that analysis, offer suggestions and guidance to humans as they make decisions.

Doctors, accountants and researchers are among the professionals who use such software.

11. AI-enabled quality control and quality assurance

Manufacturers have been using machine vision, a form of AI, for decades. They're now advancing such uses by adding quality control software with deep learning capabilities to improve the speed and accuracy of their quality control functions while keeping costs in check.

12. AI for personalized customer services, experiences and support

Delivering personalized customer services and experiences is one of the most prevalent enterprise use cases for AI.

13. Safer operations

AI is being used by number of industries to improve safety.

Construction companies, utilities, farms, mining interests and other entities working in outside locales or in spacious geographical areas are gathering data from end point devices such as cameras, thermometers, motion detectors and weather sensors. Organizations then feed that data into intelligent systems that identify problematic behaviours, dangerous conditions, business opportunities and make recommendations or even take preventative or corrective actions.

14. AI for functional area improvements

The functional areas within the typical enterprise are also putting AI to good use for their own specific needs.

Customer service uses chatbots powered by machine learning algorithms and NLP to understand customer requests and respond both faster and cheaper.

Marketing uses intelligent systems to understand users and their buying patterns, so they can create targeted marketing campaigns with a higher success rate than their generic counterparts. Some organizations are also combining intelligent technologies -- including facial recognition, geospatial software and analytics.

The supply-chain function uses algorithms to forecast what will be needed when and the optimal time to move supplies. In this, AI helps business leaders create more efficient, cost-effective supply chains by minimizing and even possibly eliminating overstocking and the risk of running short of in-demand products.

The HR function uses AI-powered systems to help write more interesting and accurate job postings, identify and screen potential candidates, and create personalized training and development programs for employees.

Cyber security uses AI to more efficiently and effectively monitor the enterprise IT environment to detect anomalies that could indicate a cyberthreat.

IT can use AI systems to write and document code.

15. AI for addressing industry-specific needs

Although many AI applications span industry sectors, other AI use cases are specific to individual industry needs. Here are some examples:

Healthcare: The healthcare industry employs artificial intelligence and machine learning products to analyse the vast troves of data collected over recent decades to uncover patterns and insights that humans aren't able to find on their own. Algorithms in diagnostic tools are helping doctors make more accurate diagnoses earlier in a disease's progression. Other intelligent tools help physicians develop more individualized treatment plans designed for maximum efficiency for each patient.

Financial services: The financial services sector uses AI and machine learning for fraud detection, digital and data security, and to analyse historical and real-time data to make near-instant decisions about the legitimacy of individual transactions. Financial services firms also use AI for more niche applications, such as wealth management, loan approvals and trading decisions.

Industrial maintenance:  The industrial sector uses AI for predictive machine maintenance to identify the most probable time equipment and to optimize the scheduling of maintenance work. AI is also used in factories to increase efficiency.

Transportation: AI is enabling a growing fleet of self-driving vehicles that are becoming smarter as they gain navigation experience. AI is also being used for smarter traffic management operations and transportation logistics.

Let’s keep our fingers crossed.

Top AI Companies

  • AI Giants
  • AI Pioneers
  • AI Visionaries
  • Generative AI Companies
  • AI Enterprise Majors
  • AI Robotics and Automation Companies
  • Conversational AI Companies
  • Healthcare AI Companies
  • Financial AI Companies
  • Education AI Companies
  • Cybersecurity AI Companies
  • Retail AI Companies
  • AI Industry Organizations
  • The Bottom Line: AI Companies

AI Giants

It’s coincidence that this top AI companies list is comprised mostly of cloud providers. Artificial intelligence requires massive storage and compute power at the level provided by the top cloud platforms.

Additionally, these cloud leaders all offer a growing menu of AI solutions to their existing clients. This gives them an enormous competitive advantage in the battle for AI market share. Furthermore, the cloud leaders all have deep pockets, and AI development is exceptionally expensive.


As a dominant provider of enterprise solutions and a cloud leader — its Azure Cloud is second only to AWS — Microsoft is investing heavily in AI. For example, it has significantly expanded its relationship with OpenAI, the creator of ChatGPT. Leveraging its massive supercomputing platform, its goal is to enable customers to build AI applications on a global scale. It’s likely that Microsoft will be the leading provider of AI solutions to the enterprise.

Amazon Web Services

As the top rank in the all-important world of cloud computing, few companies are better positioned than AWS to provide AI services and machine learning to a massive customer base. In true AWS fashion, its profusion of new tools is endless and intensely focused on making AI accessible to enterprise buyers. AWS’s long list of AI services includes quality control, machine learning, chatbots, automated speech recognition, and online fraud detection.


The search giant’s historic strength is in algorithms, which is the very foundation of AI.  Google Cloud is perennially in the cloud market, its platform is a natural conduit to offer AI services to customers. Demonstrating its competitive focus on AI, Google rolled out the AI platform. It’s a safe bet that Google will be a leader in AI in the years ahead.  


A top hybrid and multicloud vendor, boosted by its acquisition of Red Hat in 2019, IBM’s deep-pocketed global customer base has the resources to invest heavily in AI. IBM has an extensive AI portfolio, highlighted by the Watson platform, with strengths in conversational AI, machine learning, and automation. The company invests deeply in R&D and has a treasure trove of patents; its AI alliance with MIT will also likely to advance Computing.


All roads lead to Nvidia as AI grows ever more important. At the centre of Nvidia’s strength is the company’s wicked-fast GPUs, which provide the power and speed for compute-intensive AI applications. Additionally, Nvidia offers a full suite of software solutions, from generative AI to AI training to AI cybersecurity. It also has a network of partnerships with large businesses to develop AI and frequently funds AI startups.



Meta — the parent company of Facebook, Instagram, and many other popular platforms — has had a slightly slower start on generative AI than some of the other tech giants, but it has nonetheless blazed through to create some of the most ubiquitous and innovative solutions on the market today. Meta’s Llama, for example, is one of the largest and easiest to access the market today, as it is open source and available for research and commercial use. The company is also very transparent with its own AI research and resources.


Little known in the U.S., Baidu owns the majority of the internet search market in China. The company’s AI platform, Baidu Brain, processes text and images and builds user profiles. Baidu has announced plans to use its AI technology to create an autonomous ride-hailing service. It has also launched its own ChatGPT-like tool, a generative AI chatbot called Ernie Bot.


Oracle’s cloud platform has leapt forward over the past few years — it’s now one of the top cloud vendors — and its cloud strength will be a major conduit for AI services. To bulk up its AI credentials, Oracle has partnered with Nvidia to boost enterprise AI adoption. The company stresses its machine learning and automation offerings and also sells a menu of prebuilt models to enable faster AI deployment.


Alibaba, a Chinese e-commerce giant and leader in Asian cloud computing, announced in early 2023 that it will split into six divisions, each empowered to raise capital. Of particular note is the newly formed Cloud Intelligence Group, which handles cloud and AI. Notably, Alibaba’s CEO will lead this group. Alibaba has been greatly hampered by government crackdowns, but early news reports suggest this new formation is in keeping with government wishes, allowing the Cloud Intelligence Group to grow its AI rapidly. The company is also developing a ChatGPT-like tool.

 AI Pioneers

Think of these AI companies as the forward-looking cohort that is inventing and supporting the systems that propel AI forward. It’s a mixed bunch with diverse approaches to AI, some more directly focused on AI tools than others.

These companies are at the centre of a debate in the tech industry: which group of companies will have the most control over the future of AI?

Will it be these pioneers, these agile and innovative players? Or will it be the giant cloud vendors (see above) that have the deep infrastructure that AI needs and can sell their AI tools to an already-captive customer base?

Let’s wait and watch.


Dr. Priya Das, PhD


Image: Getty images/istockphoto