Companies today have access to more data than ever before. According to Forbes, the amount of data created and consumed increased by 5000% between 2010 and 2020. With the help of emerging technologies, companies are now able to capture user data that can help them make informed business decisions.
There are many ways that AI can be used by businesses, but most applications focus on driving growth. By embracing AI and machine learning, companies are finding innovative ways to help business performance. Some business benefits of AI include:
In a similar vein to recommending products, advertising departments can use AI to segment audiences and create targeted campaigns. In highly competitive industries, it is extremely important to get in front of the right audience. To make marketing campaigns more effective, companies use data to decide which types of users will see which ads. AI comes into play in terms of predicting how customers will respond to specific advertisements.
AI can also be used to help companies detect and respond to fraud threats. In the financial industry, there are tools available that identify suspicious transactions through the use of machine learning algorithms. When a fraud risk is detected, the application stops the transaction from going through and alerts the appropriate parties.
If your company is struggling to consistently deliver its products on time, AI may be able to help. AI-driven solutions can assist companies by predicting the price of materials and shipping and estimating how fast products will be able to move through the supply chain. These types of insights help supply chain professionals make decisions about the most optimal way to ship their products. On a smaller scale, AI can be used to help delivery drivers find faster routes.
A bit of context might be helpful. Despite some AI successes, one of the challenges in recent years has been that projects involving the technology have frequently lacked sufficient economic returns. In a 2019 MIT Sloan Management Review and Boston Consulting Group AI survey, for example, 7 out of 10 companies reported minimal or no value from their AI investments. One of the reasons for poor returns was that relatively few projects were deployed into production; they were too often research exercises. Production deployments admittedly can be difficult, since they usually require integration with existing systems and processes, worker reskilling, and the ability to scale AI technology.
A survey by IBM offers some insight into the impact of the COVID-19 pandemic on AI adoption, with a particular focus on automation-oriented technologies. It found that 80% of companies are already using some form of automation technology or plan to do so over the next year. Just over a third of the organizations surveyed said that the pandemic influenced their decision to adopt and use automation as a means of improving productivity. The respondents to the IBM survey were IT professionals, which may have influenced the results; IT process automation (known as AI for IT operations, or AIOps) is a popular use case for the technology.
JD.com is the Chinese version of Amazon. Its founder Richard Liu expects and is driving toward having his company be 100% automated in the future. Right now, its warehouse is already fully automated, and they have been making drone deliveries of packages for the last for years. JD.com is driving business with artificial intelligence revolution, big data, and robotics while building the retail infrastructure for the 4th industrial revolution.
In stark contrast, very few of the companies we surveyed were using AI to eliminate jobs altogether. For example, only 2% are using artificial intelligence to monitor internal legal compliance, and only 3% to detect procurement fraud (e.g., bribes and kickbacks).
What about the automation of the production line Whether assembling automobiles or insurance policies, only 7% of manufacturing and service companies are using AI to automate production activities. Similarly, only 8% are using AI to allocate budgets across the company. Just 6% are using AI in pricing.
JD.com is the Chinese version of Amazon. Its founder Richard Liu expects and is driving toward having his company be 100% automated in the future. Right now, its warehouse is already fully automated, and they have been making drone deliveries of packages for the last four years. JD.com is driving business with artificial intelligence revolution, big data, and robotics while building the retail infrastructure for the 4th industrial revolution.
Other data points from the \"Global AI Adoption Index 2022,\" conducted by Morning Consult on behalf of IBM, reveal this growth was due to companies recognizing the value of AI as they emerged from the challenges of the COVID-19 pandemic and invested in their digital transformation, while dealing with talent and skills shortages. In fact, the study shows that AI adoption was up 4 percentage points compared with 2021.
For the first time, the report also polled companies about their plans to use AI in their sustainability initiatives and found that AI is poised to play a significant role. 66% of IT professionals surveyed said that their company is either currently applying AI, or plans to apply AI, to accelerate ESG initiatives.
\"More than one-third of organizations polled in the IBM Global AI Adoption Index 2022 say they are using AI today to respond to a myriad of different factors and pressures,\" said Tom Rosamilia, Senior Vice President, IBM Software. \"They're looking to AI to help them address skills and labor shortages, respond to competitive pressures and, increasingly to respond to environmental pressures as well. Most respondents said they either are already using or plan to use AI as part of their sustainability initiatives. These trends all point to the growing role that AI is playing both within organizations but also in society.\"
Google, a leader in AI and data analytics, is on a massive AI acquisition binge, having acquired a number of AI startups in the last several years. Google is deeply invested in furthering artificial intelligence capabilities. In addition to using AI to improve its services, Google Cloud sells several AI and machine learning services to businesses. It has an industry-leading software project in TensorFlow as well as its own Tensor AI chip project.
A leading cloud platform in Asia, Alibaba offers clients a sophisticated machine learning platform for AI. Significantly, the platform offers a visual interface for ease of use, so companies can drag and drop various components into a canvas to assemble their AI functionality. Also included in the platform are scores of algorithm components that can handle any number of chores, enabling customers to use pre-built solutions.
Neurala claims that it helps users improve visual inspection problems using AI technology. The company manages The Neurala Brain, a deep learning neural network software that makes devices, like cameras, phones, and drones, smarter and easier to use. AI tends to be power hungry, but the Neurala Brain uses audio and visual input in low-power settings to make simple devices more intelligent.
iCarbonX is a Chinese biotech startup that uses artificial intelligence to provide personalized health analyses and health index predictions. It has formed an alliance with several technology companies from around the world that specialize in gathering different types of healthcare data and will use algorithms to analyze genomic, physiological, and behavioral data. It also works to provide customized health and medical advice.
Pony.ai develops software for autonomous vehicles. The company was created by ex-Google and Baidu engineers who felt that the big companies were moving too slowly in this arena. It has already made its first fully autonomous driving demonstration and now operates a self-driving ride-sharing fleet in Guangzhou, China, using cars from a local automaker. The company raised $400 million in funding from Toyota.
DataVisor uses machine learning to detect fraud and financial crime, using unsupervised machine learning to identify attack campaigns before they result in any damage. DataVisor protects companies from attacks, such as account takeovers, fake account creation, money laundering, fake social posts, and fraudulent transactions.
Ayasdi was acquired by the SymphonyAI Group. Symphony AyasdiAI is a machine intelligence software company that offers intelligent applications to its clients around the world for big data and complex data analytics problems. Its goal is to help customers automate what would be manual processes of using their own unique data. Symphony AyasdiAI also partnered with Sionic, leading to a greater focus on financial crime detection.
Cybersecurity company Darktrace is based in the U.K., focusing on how to help customers keep their data and infrastructure secure. Using self-learning AI, Darktrace can detect specific needs of their customers. Darktrace works to prevent, detect, respond, and heal from cyberattacks all at once.
Focusing on enterprise AI, C3.ai offers a wide array of pre-built applications, along with a PaaS solution, to enable the development of enterprise-level AI, IoT applications, and analytics software. These AI-fueled applications serve a wide array of sectors and industry verticals, from supply chains to health care to anti-fraud efforts. The goal is to speed up and optimize the process of digital transformation.
Tetra Tech uses AI to take notes on phone calls, so people working in call centers can focus on discussions with the callers. It uses AI to generate a detailed script of dialogues using its speech recognition technology. Given the large market for call centers, and the need to make them more effective at low cost, this is a big market for AI.
Element AI was acquired by ServiceNow. Originally based in Montreal, Element AI provides a platform for companies