Skip to main content

Cognitive System Users will Reach One Million by 2022

Large enterprises have an asset that many SMBs do not. They are in possession of massive quantities of historical and current data. In addition, the business case for employing cognitive systems to analyze that data is more compelling, when compared with smaller companies.

ABI Research predicts the number of businesses adopting artificial intelligence (AI) technologies worldwide will grow significantly, up from 7,000 this year to nearly 900,000 in 2022 -- that's a CAGR of 162 percent.

AI is now making significant strides in cloud processing, storage capacity, and machine learning algorithms to enable cognitive systems and robotics to surpass people in performing some key tasks in manufacturing and other industries.

AI and Machine Learning Market Development

Increasingly, businesses are applying these emerging technological advancements to deliver various forms of automation and innovation that will eventually equal or exceed human capabilities.

"Even though nearly one million businesses will adopt AI by 2022, it will not be a great fit for every company," says Jeff Orr, research director at ABI Research. "Many businesses will have to adapt their corporate governance policies to deal with the lack of a guaranteed outcome when implementing machine learning."

While most enterprises start using machine learning to analyze their existing business data for insights, the technologies have far-reaching application in specific industries -- ranging from reduction of false positives in fraud detection, to powering conversational interfaces for chatbots and virtual assistants.

While some of the world's largest and innovative enterprises -- such as American Express, Coca Cola, Netflix, PayPal, and Uber -- already deploy projects powered by machine learning, ABI Research finds that not all organizations will likely benefit from these cognitive system technologies.

According to the ABI assessment, progressive organizations that are comfortable with uncertainty in outcomes and measuring changes in key performance indicators (KPIs) will find the most to gain from enacting machine learning projects.

On the other hand, more traditional companies that focus only on ROI timetables will find emerging technologies -- including machine learning, cybersecurity, and IoT -- to be somewhat frustrating to implement and difficult to measure.

Outlook for Machine Learning Apps

Several SaaS solutions are available for machine learning and businesses looking to experiment will have many vendors to choose from in the near future.

Best practices include starting off with a pilot project, and requesting case studies about enterprises that have already gone through their first operational deployment.

"It is the companies that choose to ignore AI entirely that will quickly find themselves at a competitive disadvantage," concludes Orr.

Popular posts from this blog

Digital Transformation Investment at $3.4 Trillion

Business technology leadership matters. Across the globe, more leaders have been pursuing bold Digital Transformation (DX) initiatives with the goal of creating new sources of business value through digital products, services, and experiences. As an additional benefit, the COVID-19 pandemic revealed that digital transformation efforts improve an organization's resilience against global market disruptions. Global DX investment is forecast to reach $3.4 trillion in 2026 with a five-year compound annual growth rate (CAGR) of 16.3 percent, according to the latest worldwide market study by International Data Corporation (IDC). Digital Transformation Market Development "Despite strong headwinds from global supply chain constraints, soaring inflation, political uncertainty, and an impending recession, investment in digital transformation is expected to remain robust," said Craig Simpson, senior research manager at IDC . The benefits of investing in DX technology -- including aut

Artificial Intelligence for National Border Security

National border protection agencies are under pressure to provide the highest level of security in the face of growing threats, such as increasing illegal migration and international terrorism. Now, government agencies are embracing advanced border security technologies to aid in effectively and reliably securing national borders. These solutions look to detect and identify potential threats and prevent them from escalating to a point that may jeopardize security. Security Surveillance Market Development Traditional border security patrols and Closed-circuit Television (CCTV) surveillance systems aren't adequate protection, and agencies must increasingly deploy new solutions to stay ahead of criminals and other potential threats to ensure the safety of a country’s borders. According to the latest market study by Juniper Research, the value of the border security technology market will exceed $70 billion globally in 2027 -- that's rising from $48 billion in 2022. Growing by 47 p

Precision Medicine Spend to Reach $132.3 Billion

Precision Medicine uses molecular info to extract the optimum medical method from diagnostic protocols, by merging the impact of environmental and genetic factors. Data access is essential, with genetic metabolic and clinical data used to build a fuller picture of a patient's biology. Moreover, the primary aim of precision medicine is to design and optimize a pathway for diagnosis, therapeutic intervention, and prognosis, using large biological datasets. Personalized, evidence-based medicine uses stored health data, which includes patient diagnosis, laboratory work, insurance claims, and demographic information. The results enable healthcare providers to predict and prevent some illnesses. Precision Medicine Market Development According to the latest worldwide market study by Juniper Research, the total investment in precision medicine will reach $132.3 billion globally by 2027 -- that's increasing from only $35.7 billion in 2022. The significant market growth of 270 percent is